Fritz Albregtsen

• Skrede, Ole-Johan; Pradhan, Manohar; Isaksen, Maria; Hveem, Tarjei Sveinsgjerd; Vlatkovic, Ljiljana & Nesbakken, Arild [Show all 23 contributors for this article] (2026). Generalisation of automatic tumour segmentation in histopathological whole-slide images across multiple cancer types. NPJ precision oncology. 10. doi: 10.1038/s41698-026-01311-6. Full text in Research Archive Show summary

  Deep learning is expected to aid pathologists in tasks such as tumour segmentation. We developed a general tumour segmentation model for histopathological images and examined its performance in different cancer types. The model was developed using over 20,000 whole-slide images from over 4000 patients with colorectal, endometrial, lung, or prostate carcinoma. Performance was validated in pre-planned analyses on external cohorts with over 3000 patients across six cancer types. Exploratory analyses included over 1500 additional patients from The Cancer Genome Atlas. Average Dice coefficient was over 80% in all validation cohorts with en bloc resection specimens and in The Cancer Genome Atlas cohorts. No performance loss was observed when comparing the general model with single-cancer models specialised in cancer types from the development set. In conclusion, extensive and rigorous evaluations demonstrate that generic tumour segmentation by a single model is possible across cancer types, patient populations, sample preparations and slide scanners.

• Nainamalai, Varatharajan; Prasad, Pravda Jith Ray; Pelanis, Egidijus; Edwin, Bjørn von Gohren; Albregtsen, Fritz & Elle, Ole Jakob [Show all 7 contributors for this article] (2022). Evaluation of clinical applicability of automated liver parenchyma segmentation of multi-center magnetic resonance images. European Journal of Radiology Open (EJR Open). 9. doi: 10.1016/j.ejro.2022.100448. Full text in Research Archive
• Prasad, Pravda Jith Ray; Survarachakan, Shanmugapriya; Khan, Zohaib Amjad; Lindseth, Frank; Elle, Ole Jacob & Albregtsen, Fritz [Show all 7 contributors for this article] (2021). Numerical evaluation on parametric choices influencing segmentation results in radiology images—a multi-dataset study. Electronics (Basel). 10:431(4), p. 1–25. doi: 10.3390/electronics10040431. Full text in Research Archive Show summary

  Medical image segmentation has gained greater attention over the past decade, especially in the field of image-guided surgery. Here, robust, accurate and fast segmentation tools are important for planning and navigation. In this work, we explore the Convolutional Neural Network (CNN) based approaches for multi-dataset segmentation from CT examinations. We hypothesize that selection of certain parameters in the network architecture design critically influence the segmentation results. We have employed two different CNN architectures, 3D-UNet and VGG-16, given that both networks are well accepted in the medical domain for segmentation tasks. In order to understand the efficiency of different parameter choices, we have adopted two different approaches. The first one combines different weight initialization schemes with different activation functions, whereas the second approach combines different weight initialization methods with a set of loss functions and optimizers. For evaluation, the 3D-UNet was trained with the Medical Segmentation Decathlon dataset and VGG-16 using LiTS data. The quality assessment done using eight quantitative metrics enhances the probability of using our proposed strategies for enhancing the segmentation results. Following a systematic approach in the evaluation of the results, we propose a few strategies that can be adopted for obtaining good segmentation results. Both of the architectures used in this work were selected on the basis of general acceptance in segmentation tasks for medical images based on their promising results compared to other state-of-the art networks. The highest Dice score obtained in 3D-UNet for the liver, pancreas and cardiac data was 0.897, 0.691 and 0.892. In the case of VGG-16, it was solely developed to work with liver data and delivered a Dice score of 0.921. From all the experiments conducted, we observed that two of the combinations with Xavier weight initialization (also known as Glorot), Adam optimiser, Cross Entropy loss (GloAdamCE) and LeCun weight initialization, cross entropy loss and Adam optimiser LecAdamCE worked best for most of the metrics in a 3D-UNet setting, while Xavier together with cross entropy loss and Tanh activation function (GlotanhCE) worked best for the VGG-16 network. Here, the parameter combinations are proposed on the basis of their contributions in obtaining optimal outcomes in segmentation evaluations. Moreover, we discuss that the preliminary evaluation results show that these parameters could later on be used for gaining more insights into model convergence and optimal solutions.The results from the quality assessment metrics and the statistical analysis validate our conclusions and we propose that the presented work can be used as a guide in choosing parameters for the best possible segmentation results for future works.

• Skrede, Ole-Johan; Raedt, Sepp De; Kleppe, Andreas; Hveem, Tarjei Sveinsgjerd; Liestøl, Knut & Maddison, John [Show all 20 contributors for this article] (2020). Deep learning for prediction of colorectal cancer outcome: a discovery and validation study. The Lancet. ISSN 0140-6736. 395:10221, p. 350–360. doi: 10.1016/S0140-6736(19)32998-8. Full text in Research Archive Show summary

  Background Improved markers of prognosis are needed to stratify patients with early-stage colorectal cancer to refine selection of adjuvant therapy. The aim of the present study was to develop a biomarker of patient outcome after primary colorectal cancer resection by directly analysing scanned conventional haematoxylin and eosin stained sections using deep learning. Methods More than 12 000 000 image tiles from patients with a distinctly good or poor disease outcome from four cohorts were used to train a total of ten convolutional neural networks, purpose-built for classifying supersized heterogeneous images. A prognostic biomarker integrating the ten networks was determined using patients with a non-distinct outcome. The marker was tested on 920 patients with slides prepared in the UK, and then independently validated according to a predefined protocol in 1122 patients treated with single-agent capecitabine using slides prepared in Norway. All cohorts included only patients with resectable tumours, and a formalin-fixed, paraffin-embedded tumour tissue block available for analysis. The primary outcome was cancer-specific survival. Findings 828 patients from four cohorts had a distinct outcome and were used as a training cohort to obtain clear ground truth. 1645 patients had a non-distinct outcome and were used for tuning. The biomarker provided a hazard ratio for poor versus good prognosis of 3·84 (95% CI 2·72–5·43; p<0·0001) in the primary analysis of the validation cohort, and 3·04 (2·07–4·47; p<0·0001) after adjusting for established prognostic markers significant in univariable analyses of the same cohort, which were pN stage, pT stage, lymphatic invasion, and venous vascular invasion. Interpretation A clinically useful prognostic marker was developed using deep learning allied to digital scanning of conventional haematoxylin and eosin stained tumour tissue sections. The assay has been extensively evaluated in large, independent patient populations, correlates with and outperforms established molecular and morphological prognostic markers, and gives consistent results across tumour and nodal stage. The biomarker stratified stage II and III patients into sufficiently distinct prognostic groups that potentially could be used to guide selection of adjuvant treatment by avoiding therapy in very low risk groups and identifying patients who would benefit from more intensive treatment regimes.

• Kleppe, Andreas; Albregtsen, Fritz; Trovik, Jone; Kristensen, Gunnar S Balle & Danielsen, Håvard Emil (2020). Prognostic value of the diversity of nuclear chromatin compartments in gynaecological carcinomas. Cancers. 12:3838(12), p. 1–16. doi: 10.3390/cancers12123838. Full text in Research Archive Show summary

  Statistical texture analysis of cancer cell nuclei stained for DNA has recently been used to develop a pan-cancer prognostic marker of chromatin heterogeneity. In this study, we instead analysed chromatin organisation by automatically quantifying the diversity of chromatin compartments in cancer cell nuclei. The aim was to investigate the prognostic value of such an assessment in relation to chromatin heterogeneity and as a potential supplement to pathological risk classifications in gynaecological carcinomas. The diversity was quantified by calculating the entropy of both chromatin compartment sizes and optical densities within compartments. We analysed a median of 281 nuclei (interquartile range (IQR), 273 to 289) from 246 ovarian carcinoma patients and a median of 997 nuclei (IQR, 502 to 1452) from 791 endometrial carcinoma patients. The prognostic value of the entropies and chromatin heterogeneity was moderately strongly correlated (r ranged from 0.68 to 0.73), but the novel marker was observed to provide additional prognostic information. In multivariable analysis with clinical and pathological markers, the hazard ratio associated with the novel marker was 2.1 (95% CI, 1.3 to 3.5) in ovarian carcinoma and 2.4 (95% CI, 1.5 to 3.9) in endometrial carcinoma. Integration with pathological risk classifications gave three risk groups with distinctly different prognoses. This suggests that the novel marker of diversity of chromatin compartments might possibly contribute to the selection of high-risk stage I ovarian carcinoma patients for adjuvant chemotherapy and low-risk endometrial carcinoma patients for less extensive surgery.

• Nielsen, Birgitte; Kleppe, Andreas; Hveem, Tarjei Sveinsgjerd; Pradhan, Manohar; Syvertsen, Rolf Anders & Nesheim, John Arne [Show all 11 contributors for this article] (2018). Association Between Proportion of Nuclei With High Chromatin Entropy and Prognosis in Gynecological Cancers. Journal of the National Cancer Institute. ISSN 0027-8874. 110(12), p. 1400–1408. doi: 10.1093/jnci/djy063. Full text in Research Archive Show summary

  Background: Nuclear texture analysis measuring differences in chromatin structure has provided prognostic biomarkers in several cancers. There is a need for improved cell-by-cell chromatin analysis to detect nuclei with highly disorganized chromatin. The purpose of this study was to develop a method for detecting nuclei with high chromatin entropy and to evaluate the association between the presence of such deviating nuclei and prognosis. Methods: A new texture-based biomarker that characterizes each cancer based on the proportion of high–chromatin entropy nuclei (<25% vs ≥25%) was developed on a discovery set of 175 uterine sarcomas. The prognostic impact of this biomarker was evaluated on a validation set of 179 uterine sarcomas, as well as on independent validation sets of 246 early-stage ovarian carcinomas and 791 endometrial carcinomas. More than 1 million images of nuclei stained for DNA were included in the study. All statistical tests were two-sided. Results: An increased proportion of high–chromatin entropy nuclei was associated with poor clinical outcome. The biomarker predicted five-year overall survival for uterine sarcoma patients with a hazard ratio (HR) of 2.02 (95% confidence interval [CI] = 1.43 to 2.84), time to recurrence for ovarian cancer patients (HR = 2.91, 95% CI = 1.74 to 4.88), and cancer-specific survival for endometrial cancer patients (HR = 3.74, 95% CI = 2.24 to 6.24). Chromatin entropy was an independent prognostic marker in multivariable analyses with clinicopathological parameters (HR = 1.81, 95% CI = 1.21 to 2.70, for sarcoma; HR = 1.71, 95% CI = 1.01 to 2.90, for ovarian cancer; and HR = 2.03, 95% CI = 1.19 to 3.45, for endometrial cancer). Conclusions: A novel method detected high–chromatin entropy nuclei, and an increased proportion of such nuclei was associated with poor prognosis. Chromatin entropy supplemented existing prognostic markers in multivariable analyses of three gynecological cancer cohorts.

• Kleppe, Andreas; Albregtsen, Fritz; Vlatkovic, Ljiljana; Pradhan, Manohar; Nielsen, Birgitte & Hveem, Tarjei Sveinsgjerd [Show all 16 contributors for this article] (2018). Chromatin organisation and cancer prognosis: a pan-cancer study. The Lancet Oncology. ISSN 1470-2045. 19(3), p. 356–369. doi: 10.1016/S1470-2045(17)30899-9. Full text in Research Archive Show summary

  Background: Chromatin organisation affects gene expression and regional mutation frequencies and contributes to carcinogenesis. Aberrant organisation of DNA has been correlated with cancer prognosis in analyses of the chromatin component of tumour cell nuclei using image texture analysis. As yet, the methodology has not been sufficiently validated to permit its clinical application. We aimed to define and validate a novel prognostic biomarker for the automatic detection of heterogeneous chromatin organisation. Methods Machine learning algorithms analysed the chromatin organisation in 461 000 images of tumour cell nuclei stained for DNA from 390 patients (discovery cohort) treated for stage I or II colorectal cancer at the Aker University Hospital (Oslo, Norway). The resulting marker of chromatin heterogeneity, termed Nucleotyping, was subsequently independently validated in six patient cohorts: 442 patients with stage I or II colorectal cancer in the Gloucester Colorectal Cancer Study (UK); 391 patients with stage II colorectal cancer in the QUASAR 2 trial; 246 patients with stage I ovarian carcinoma; 354 patients with uterine sarcoma; 307 patients with prostate carcinoma; and 791 patients with endometrial carcinoma. The primary outcome was cancer-specific survival. Findings: In all patient cohorts, patients with chromatin heterogeneous tumours had worse cancer-specific survival than patients with chromatin homogeneous tumours (univariable analysis hazard ratio [HR] 1·7, 95% CI 1·2–2·5, in the discovery cohort; 1·8, 1·0–3·0, in the Gloucester validation cohort; 2·2, 1·1–4·5, in the QUASAR 2 validation cohort; 3·1, 1·9–5·0, in the ovarian carcinoma cohort; 2·5, 1·8–3·4, in the uterine sarcoma cohort; 2·3, 1·2–4·6, in the prostate carcinoma cohort; and 4·3, 2·8–6·8, in the endometrial carcinoma cohort). After adjusting for established prognostic patient characteristics in multivariable analyses, Nucleotyping was prognostic in all cohorts except for the prostate carcinoma cohort (HR 1·7, 95% CI 1·1–2·5, in the discovery cohort; 1·9, 1·1–3·2, in the Gloucester validation cohort; 2·6, 1·2–5·6, in the QUASAR 2 cohort; 1·8, 1·1–3·0, for ovarian carcinoma; 1·6, 1·0–2·4, for uterine sarcoma; 1·43, 0·68–2·99, for prostate carcinoma; and 1·9, 1·1–3·1, for endometrial carcinoma). Chromatin heterogeneity was a significant predictor of cancer-specific survival in microsatellite unstable (HR 2·9, 95% CI 1·0–8·4) and microsatellite stable (1·8, 1·2–2·7) stage II colorectal cancer, but microsatellite instability was not a significant predictor of outcome in chromatin homogeneous (1·3, 0·7–2·4) or chromatin heterogeneous (0·8, 0·3–2·0) stage II colorectal cancer. Interpretation: The consistent prognostic prediction of Nucleotyping in different biological and technical circumstances suggests that the marker of chromatin heterogeneity can be reliably assessed in routine clinical practice and could be used to objectively assist decision making in a range of clinical settings. An immediate application would be to identify high-risk patients with stage II colorectal cancer who might have greater absolute benefit from adjuvant chemotherapy. Clinical trials are warranted to evaluate the survival benefit and cost-effectiveness of using Nucleotyping to guide treatment decisions in multiple clinical settings.

• Kumar, Rahul Prasanna; Barkhatov, Leonid; Edwin, Bjørn; Albregtsen, Fritz & Elle, Ole Jakob (2017). Portal and hepatic vein segmentation with leak restriction: A pilot study. International Federation for Medical and Biological Engineering Proceedings. ISSN 1680-0737. 65, p. 823–826. doi: 10.1007/978-981-10-5122-7_206. Full text in Research Archive
• Hveem, Tarjei Sveinsgjerd; Njølstad, Tormund Salvesen; Nielsen, Birgitte; Syvertsen, Rolf Anders; Nesheim, John Arne & Kjæreng, Marna Lill [Show all 25 contributors for this article] (2016). Changes in Chromatin Structure in Curettage Specimens Identifies High-Risk Patients in Endometrial Cancer. Cancer Epidemiology, Biomarkers and Prevention. ISSN 1055-9965. 26(1), p. 61–67. doi: 10.1158/1055-9965.EPI-16-0215. Full text in Research Archive
• Hveem, Tarjei Sveinsgjerd; Kleppe, Andreas; Vlatkovic, Ljiljana; Ersvær, Elin; Wæhre, Haakon & Nielsen, Birgitte [Show all 13 contributors for this article] (2016). Chromatin changes predict recurrence after radical prostatectomy. British Journal of Cancer. ISSN 0007-0920. 114(11), p. 1243–1250. doi: 10.1038/bjc.2016.96. Full text in Research Archive
• Holmen, Sigve; Galappaththi-Arachchige, Hashini Nilushika; Kleppa, Elisabeth; Pillay, Pavitra; Naicker, Thajasvarie & Taylor, Myra [Show all 9 contributors for this article] (2016). Characteristics of Blood Vessels in Female Genital Schistosomiasis: Paving the Way for Objective Diagnostics at the Point of Care. PLoS Neglected Tropical Diseases. ISSN 1935-2727. 10(4). doi: 10.1371/journal.pntd.0004628. Full text in Research Archive Show summary

  Background The mucosal changes associated with female genital schistosomiasis (FGS) encompass abnormal blood vessels. These have been described as circular, reticular, branched, convoluted and having uneven calibre. However, these characteristics are subjective descriptions and it has not been explored which of them are specific to FGS. Methods In colposcopic images of young women from a schistosomiasis endemic area, we performed computerised morphologic analyses of the cervical vasculature appearing on the mucosal surface. Study participants where the cervix was classified as normal served as negative controls, women with clinically diagnosed FGS and presence of typical abnormal blood vessels visible on the cervical surface served as positive cases. We also included women with cervical inflammatory conditions for reasons other than schistosomiasis. By automating morphological analyses, we explored circular configurations, vascular density, fractal dimensions and fractal lacunarity as parameters of interest. Results We found that the blood vessels typical of FGS are characterised by the presence of circular configurations (p < 0.001), increased vascular density (p = 0.015) and increased local connected fractal dimensions (p = 0.071). Using these features, we were able to correctly classify 78% of the FGS-positive cases with an accuracy of 80%. Conclusions The blood vessels typical of FGS have circular configurations, increased vascular density and increased local connected fractal dimensions. These specific morphological features could be used diagnostically. Combined with colourimetric analyses, this represents a step towards making a diagnostic tool for FGS based on computerised image analysis.

• Nielsen, Birgitte; Hveem, Tarjei Sveinsgjerd; Kildal, Wanja; Abeler, Vera Maria; Kristensen, Gunnar S Balle & Albregtsen, Fritz [Show all 7 contributors for this article] (2015). Entropy-based adaptive nuclear texture features are independent prognostic markers in a total population of uterine sarcomas. Cytometry Part A. ISSN 1552-4922. 87(4), p. 315–325. doi: 10.1002/cyto.a.22601. Full text in Research Archive
• Kumar, Rahul Prasanna; Albregtsen, Fritz; Reimers, Martin; Edwin, Bjørn; Langø, Thomas & Elle, Ole Jakob (2015). Blood vessel segmentation and centerline tracking using local structure analysis. International Federation for Medical and Biological Engineering Proceedings. ISSN 1680-0737. 45, p. 122–125. doi: 10.1007/978-3-319-11128-5_31. Full text in Research Archive Show summary

  Blood vessel visualization is important for improving planning and navigation of several interventional procedures. In this paper, we present a novel method for simultaneous blood vessel segmentation, centerline tracking and radius estimation. Our method is based on local structure analysis within the connected regions of the blood vessels. The proposed method is mainly divided into trunk analysis and bifurcation analysis. In the trunk analysis, the vessel is segmented using 2D cross-section analysis while in the bifurcation analysis, the vessel is segmented using modified vesselness. Our method was evaluated on angiogram images. When comparing the processing time for finding the blood vessel centerline, our proposed method was found to be on average more than 20 times faster than multiscale vesselness with thinning and more than 7 times faster than our own earlier method of blood vessel centerline extraction. Also, the centerline extraction was found to be accurate with a mean error less than 1 voxel in comparison to the corresponding geometric centers.

• Holmen, Sigve; Kjetland, Eyrun Floerecke; Taylor, Myra; Kleppa, Elisabeth; Lillebø, Kristine & Gundersen, Svein Gunnar [Show all 8 contributors for this article] (2015). Colourimetric image analysis as a diagnostic tool in female genital schistosomiasis. Medical Engineering and Physics. ISSN 1350-4533. 37(3), p. 309–314. doi: 10.1016/j.medengphy.2014.12.007. Full text in Research Archive Show summary

  Female genital schistosomiasis (FGS) is a highly prevalent waterborne disease in some of the poorest areas of sub-Saharan Africa. Reliable and affordable diagnostics are unavailable. We explored colourimetric image analysis to identify the characteristic, yellow lesions caused by FGS. We found that the method may yield a sensitivity of 83% and a specificity of 73% in colposcopic images. The accuracy was also explored in images of simulated inferior quality, to assess the possibility of implementing such a method in simple, electronic devices. This represents the first step towards developing a safe and affordable aid in clinical diagnosis, allowing for a point-of-care approach.

• Holmen, Sigve; Kleppa, Elisabeth; Lillebø, Kristine; Pillay, Pavitra; Lieshout, Lisette Van & Taylor, Myra [Show all 10 contributors for this article] (2015). The first step toward diagnosing female genital schistosomiasis by computer image analysis. American Journal of Tropical Medicine and Hygiene. ISSN 0002-9637. 93(1), p. 80–86. doi: 10.4269/ajtmh.15-0071. Full text in Research Archive Show summary

  Schistosoma haematobium causes female genital schistosomiasis (FGS), which is a poverty-related disease in sub-Saharan Africa. Furthermore, it is co-endemic with human immunodeficiency virus (HIV), and biopsies from genital lesions may expose the individual to increased risk of HIV infection. However, microscopy of urine and hematuria are nonspecific and insensitive predictors of FGS and gynecological investigation requires extensive training. Safe and affordable diagnostic methods are needed. We explore a novel method of diagnosing FGS using computer color analysis of colposcopic images. In a cross-sectional study on young women in an endemic area, we found strong associations between the output from the computer color analysis and both clinical diagnosis (odds ratio [OR] = 5.97, P < 0.001) and urine microscopy for schistosomiasis (OR = 3.52, P = 0.004). Finally, using latent class statistics, we estimate that the computer color analysis yields a sensitivity of 80.5% and a specificity of 66.2% for the diagnosis of FGS.

• Landmark, Knut; Solberg, Anne H Schistad; Albregtsen, Fritz; Austeng, Andreas & Hansen, Roy Edgar (2015). A Radon-Transform-Based Image Noise Filter - With Applications to Multibeam Bathymetry. IEEE Transactions on Geoscience and Remote Sensing. ISSN 0196-2892. doi: 10.1109/TGRS.2015.2436380. Full text in Research Archive Show summary

  This paper describes a linear-image-transform-based algorithm for reducing stripe noise, track line artifacts, and motion-induced errors in remote sensing data. Developed for multibeam bathymetry (MB), the method has also been used for removing scalloping in synthetic aperture radar images. The proposed image transform is the composition of an invertible edge detection operator and a fast discrete Radon transform (DRT) due to Götz, Druckmüller, and Brady. The inverse DRT is computed by using an iterative method and exploiting an approximate inverse algorithm due to Press. The edge operator is implemented by circular convolution with a Laplacian point spread function modified to render the operator invertible. In the transformed image, linear discontinuities appear as high-intensity spots, which may be reset to zero. In MB data, a second noise signature is linked to motion-induced errors. A Chebyshev approximation of the original image is subtracted before applying the transform, and added back to the denoised image; this is necessary to avoid boundary effects. It is possible to process data faster and suppress motion-induced noise further by filtering images in nonoverlapping blocks using a matrix representation for the inverse DRT. Processed test images from several MB data sets had less noise and distortion compared with those obtained with standard low-pass filters. Denoising also improved the accuracy in statistical classification of geomorphological type by 10-28% for two sets of invariant terrain features.

• Simone, Gabriele; Audino, Giuseppe; Farup, Ivar; Albregtsen, Fritz & Rizzi, Alessandro (2014). Termite retinex: A new implementation based on a colony of intelligent agents. Journal of Electronic Imaging (JEI). ISSN 1017-9909. 23(1). doi: 10.1117/1.JEI.23.1.013006. Full text in Research Archive Show summary

  Abstract. The original presentation of Retinex, a spatial color correction and image enhancement algorithm modeling the human vision system, as proposed by Land and McCann in 1964, uses paths to explore the image in search of a local reference white point. The interesting results of this algorithm have led to the development of many versions of Retinex. They follow the same principle but differ in the way they explore the image, with, for example, random paths, random samples, convolution masks, and variational formulations. We propose an alternative way to explore local properties of Retinex, replacing random paths by traces of a specialized swarm of termites. In presenting the spatial characteristics of the proposed method, we discuss differences in path exploration with other Retinex implementations. Experiments, results, and comparisons are presented to test the efficacy of the proposed Retinex implementation.

• Kumar, Rahul Prasanna; Albregtsen, Fritz; Reimers, Martin; Edwin, Bjørn; Langø, Thomas & Elle, Ole Jakob (2014). Three-Dimensional Blood Vessel Segmentation and Centerline Extraction based on Two-Dimensional Cross-Section Analysis. Annals of Biomedical Engineering. ISSN 0090-6964. 43(5), p. 1223–1234. doi: 10.1007/s10439-014-1184-4. Full text in Research Archive Show summary

  The segmentation of tubular tree structures like vessel systems in volumetric datasets is of vital interest for many medical applications. In this paper we present a novel, semi-automatic method for blood vessel segmentation and centerline extraction, by tracking the blood vessel tree from a user-initiated seed point to the ends of the blood vessel tree. The novelty of our method is in performing only two-dimensional cross-section analysis for segmentation of the connected blood vessels. The cross-section analysis is done by our novel single-scale or multi-scale circle enhancement filter, used at the blood vessel trunk or bifurcation, respectively. The method was validated for both synthetic and medical images. Our validation has shown that the cross-sectional centerline error for our method is below 0.8 pixels and the Dice coefficient for our segmentation is 80% ± 2.7%. On combining our method with an optional active contour post-processing, the Dice coefficient for the resulting segmentation is found to be 94% ± 2.4%. Furthermore, by restricting the image analysis to the regions of interest and converting most of the three-dimensional calculations to two-dimensional calculations, the processing was found to be more than 18 times faster than Frangi vesselness with thinning, 8 times faster than user-initiated active contour segmentation with thinning and 7 times faster than our previous method.

• Kumar, Rahul Prasanna; Albregtsen, Fritz; Reimers, Martin; Langø, Thomas; Edwin, Bjørn & Elle, Ole Jakob (2013). 3D multiscale vessel enhancement based centerline extraction of blood vessels. In Ourselin, Sebastien & Haynor, David (Ed.), SPIE Medical Imaging 2013: Image Processing. SPIE - The International Society for Optics and Photonics. ISSN 9780819494436. doi: 10.1117/12.2006779. Full text in Research Archive Show summary

  Extraction of blood vessel structure is important for improving planning, navigation and tracking in several interventional procedures. Centerline based registration methods have proven to be fast for clinical applications and an effective way of registering multi-modal images. Here, we present a novel blood vessel centerline extraction method in 3D. Our method consists of two parts, namely Multiscale Vessel Enhancement Filtering (MVEF) and Centerline Extraction using Vessel Direction (CEVD). Our proposed MVEF has an improved noise reduction and better Gaussian profile at the vessel cross-sections compared to conventional MVEF. The CEVD is our novel method for tracing the peaks of the Gaussian profile of the local MVEF at the vessel cross-sections. The peak of the Gaussian profile provides the center position of the blood vessels. The novelty of this method is in effectively finding only the connected centerlines of the blood vessels of interest. The proposed method was evaluated using both synthetic and medical images. On comparing with Frangi's vesselness filtering combined with thinning, our method is shown to be approximately 5 times faster. The results also show that our method is customized to detect only the desired blood vessels, thereby eliminating the detection of unwanted vessel-like structures. The centerline accuracy was evaluated by comparing with ground truth data created by finding Hough circle centers at each cross-section of the vessel structure. The modified symmetric Hausdorff distance between our result and the ground truth was approximately 1 pixel for both synthetic and medical images. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

• Nielsen, Birgitte; Albregtsen, Fritz; Kildal, Wanja; Abeler, Vera Maria; Kristensen, Gunnar S Balle & Danielsen, Håvard Emil (2012). The prognostic value of adaptive nuclear texture features from patient gray level entropy matrices in early stage ovarian cancer. Analytical Cellular Pathology. ISSN 2210-7177. 35(4), p. 305–314. doi: 10.3233/ACP-2012-0065. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard Emil (2012). Automatic segmentation of cell nuclei in Feulgen-stained histological sections of prostate cancer and quantitative evaluation of segmentation results. Cytometry. ISSN 0196-4763. 81A(7), p. 588–601. doi: 10.1002/cyto.a.22068. Full text in Research Archive
• Pedersen, Marius; Bonnier, Nicolas; Hardeberg, Jon Yngve & Albregtsen, Fritz (2011). Image quality metrics for the evaluation of print quality. Proceedings of SPIE, the International Society for Optical Engineering. ISSN 0277-786X. 7867. doi: 10.1117/12.876472. Full text in Research Archive Show summary

  Image quality metrics have become more and more popular in the image processing community. However, so far, no one has been able to define an image quality metric well correlated with the percept for overall image quality. One of the causes is that image quality is multi-dimensional and complex. One approach to bridge the gap between perceived and calculated image quality is to reduce the complexity of image quality, by breaking the overall quality into a set of quality attributes. In our research we have presented a set of quality attributes built on existing attributes from the literature. The six proposed quality attributes are: sharpness, color, lightness, artifacts, contrast, and physical. This set keeps the dimensionality to a minimum. An experiment validated the quality attributes as suitable for image quality evaluation. The process of applying image quality metrics to printed images is not straightforward, because image quality metrics require a digital input. A framework has been developed for this process, which includes scanning the print to get a digital copy, image registration, and the application of image quality metrics. With quality attributes for the evaluation of image quality and a framework for applying image quality metrics, a selection of suitable image quality metrics for the different quality attributes has been carried out. Each of the quality attributes has been investigated, and an experimental analysis carried out to find the most suitable image quality metrics for the given quality attributes. For the sharpness attributes the Structural SIMilarity index (SSIM) by Wang et al. (2004) is the the most suitable, and for the other attributes further evaluation is required.

• Dunn, J. M.; Hveem, Tarjei Sveinsgjerd; Pretorius, Mikkel; Oukrif, D.; Nielsen, Birgitte & Albregtsen, Fritz [Show all 9 contributors for this article] (2011). Comparison of nuclear texture analysis and image cytometric DNA analysis for the assessment of dysplasia in Barrett's oesophagus. British Journal of Cancer. ISSN 0007-0920. 105(8), p. 1218–1223. doi: 10.1038/bjc.2011.353. Full text in Research Archive
• Nussbaum, Peter Stefan; Hardeberg, Jon Yngve & Albregtsen, Fritz (2011). Regression based characterization of color measurement instruments in printing applications. Proceedings of SPIE, the International Society for Optical Engineering. ISSN 0277-786X. 7866. doi: 10.1117/12.872381. Full text in Research Archive Show summary

  In the context of print quality and process control colorimetric parameters and tolerance values are clearly defined. Calibration procedures are well defined for color measurement instruments in printing workflows. Still, using more than one color measurement instrument measuring the same color wedge can produce clearly different results due to random and systematic errors of the instruments. In certain situations where one instrument gives values which are just inside the given tolerances and another measurement instrument produces values which exceed the predefined tolerance parameters, the question arises whether the print or proof is approved or not accepted with regards to the standard parameters. The aim of this paper was to determine an appropriate model to characterize color measurement instruments for printing applications in order to improve the colorimetric performance and hence the inter-instrument agreement. The method proposed is derived from color image acquisition device characterization methods which have been applied by performing polynomial regression with a least square technique. Six commercial color measurement instruments were used for measuring color patches of a control color wedge on three different types of paper substrates. The characterization functions were derived using least square polynomial regression, based on the training set of 14 BCRA tiles colorimetric reference values and the corresponding colorimetric measurements obtained by the measurement instruments. The derived functions were then used to correct the colorimetric values of test sets of 46 measurements of the color control wedge patches. The corrected measurement results obtained from the applied regression model was then used as the starting point with which the corrected measurements from other instruments were compared to find the most appropriate polynomial, which results in the least color difference. The obtained results demonstrate that the proposed regression method works remarkably well with a range of different color measurement instruments used on three types of substrates. Finally, by extending the training set from 14 samples to 38 samples the obtained results clearly indicate that the model is robust.

• Pedersen, Marius; Bonnier, Nicolas; Hardeberg, Jon Yngve & Albregtsen, Fritz (2010). Attributes of image quality for color prints. Journal of Electronic Imaging (JEI). ISSN 1017-9909. 19(1). doi: 10.1117/1.3277145. Full text in Research Archive Show summary

  The evaluation of perceived image quality in color prints is a complex task due to its subjectivity and dimensionality. The perceived quality of an image is influenced by a number of different quality attributes. It is difficult and complicated to evaluate the influence of all attributes on overall image quality, and their influence on other attributes. Because of this difficulty, the most important attributes of a color image should be identified to achieve a more efficient and manageable evaluation of the image's quality. Based on a survey of the existing literature and a psychophysical experiment, we identify and categorize existing image quality attributes to propose a refined selection of meaningful ones for the evaluation of color prints.

• Pedersen, Marius; Bonnier, Nicolas; Hardeberg, Jon Yngve & Albregtsen, Fritz (2010). Validation of quality attributes for evaluation of color prints. In NN, . (Eds.), Eighteenth Color Imaging Conference : Color Science and Engineering Systems, Technologies and Applications ; Final program and proceedings, November 8 - 12, 2010, San Antonio, Texas / sponsored by Society for Imaging Science and Technology and Society for Information Display. The Society for Imaging Science and Technology. ISSN 9780892082940. p. 74–79. Full text in Research Archive Show summary

  Image quality assessment is a difficult and complex task. Quality attributes have been used in the evaluation of perceived image quality in an attempt to reduce the complexity and the dimensionality. Recently, Pedersen et al. (CIC, 2009) proposed a set of quality attributes for the evaluation of color prints. In this paper we perform an experimental validation of these quality attributes to ensure that the criteria on which they were selected are fulfilled. The results show a correspondence between the quality attributes and the criteria. The quality attributes are therefore considered as a good starting point to describe overall image quality.

• Pedersen, Marius; Bonnier, Nicolas; Hardeberg, Jon Yngve & Albregtsen, Fritz (2010). Estimating print quality attributes by image quality metrics. In NN, . (Eds.), Eighteenth Color Imaging Conference : Color Science and Engineering Systems, Technologies and Applications ; Final program and proceedings, November 8 - 12, 2010, San Antonio, Texas / sponsored by Society for Imaging Science and Technology and Society for Information Display. The Society for Imaging Science and Technology. ISSN 9780892082940. p. 68–73. Full text in Research Archive Show summary

  Image quality assessment is a difficult and complex task due to its subjectivity and dimensionality. Attempts have been made to make image quality assessment more objective, such as the introduction of image quality metrics. However, it has been proven difficult to create an image quality metric correlated with perceived overall image quality. Because of this, and to reduce the dimensionality, quality attributes have been proposed to help linking subjective and objective image quality. Recently, Pedersen et al. (CIC, 2009) proposed a set of meaningful quality attributes for the evaluation of color prints with the intention of being used with image quality metrics. In this paper we evaluate image quality metrics for the quality attributes, and propose a set of suitable image quality metrics for each attribute. The experimental results indicate that the Structural SIMilarity index (SSIM) by Wang et al. (2004) is the most suitable metric for measuring the sharpness quality attribute. For the other quality attributes the results are not as conclusive.

• Akbari, Akbar; Albregtsen, Fritz & Jakobsen, Kjetill Sigurd (2010). Automatic lane detection and separation in one dimensional gel images using continuous wavelet transform. Analytical Methods. ISSN 1759-9660. 2(9), p. 1360–1371. doi: 10.1039/c0ay00167h. Full text in Research Archive
• Pedersen, Marius; Albregtsen, Fritz & Hardeberg, Jon Yngve (2009). Detection of worms in error diffusion halftoning. In Farnand, Susan P. & Gaykema, Frans (Ed.), Image quality and system performance VI 19-21 January 2009, San Jose, California, USA. SPIE - The International Society for Optics and Photonics. ISSN 9780819474926. Full text in Research Archive Show summary

  Digital halftoning is used to reproduce a continuous tone image with a printer. One of these halftoning algorithms, error diffusion, suffers from certain artifacts. One of these artifacts is commonly denoted as worms. We propose a simple measure for detection of worm artifacts. The proposed measure is evaluated by a psychophysical experiment, where 4 images were reproduced using 5 different error diffusion algorithms. The results indicate a high correlation between the predicted worms and perceived worms.

• Pedersen, Marius; Bonnier, Nicolas; Hardeberg, Jon Yngve & Albregtsen, Fritz (2009). Attributes of a New Image Quality Model for Color Prints. In N, N (Eds.), Seventeenth Color Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications; Final Program and Proceedings. The Society for Imaging Science and Technology. ISSN 9780892082889. p. 204–209. Full text in Research Archive Show summary

  Evaluation of perceived image quality in color prints is a complex task, due to its subjectivity and dimensionality. Perceived image quality is influenced by a number of quality attributes. Evaluation of all attributes influence, and their influence on other attributes, is is a difficult and complex task. Because of this the most important attributes should be identified in order to achieve a more effective and manageable evaluation of image quality. In this paper we identify and categorize existing quality attributes, and we propose a refined selection of meaningful quality attributes for the evaluation of color prints. Experimental data verify the proposed set of quality attributes.

• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard Emil (2009). Statistical Nuclear Texture Analysis in Cancer Research: A Review of Methods and Applications. Critical reviews in oncogenesis. ISSN 0893-9675. 14(2-3), p. 89–164. Full text in Research Archive
• Pedersen, Marius; Albregtsen, Fritz & Hardeberg, Jon Yngve (2009). Detection of worms in error diffusion halftoning. Proceedings of SPIE, the International Society for Optical Engineering. ISSN 0277-786X. Full text in Research Archive
• Akbari, Akbar; Marthinsen, Gunnhild; Lifjeld, Jan Terje; Albregtsen, Fritz; Wennerberg, Liv & Stenseth, Nils Christian [Show all 7 contributors for this article] (2008). Improved DNA fragment length estimation in capillary electrophoresis. Electrophoresis. ISSN 0173-0835. 29(6), p. 1273–1285. doi: 10.1002/elps.200700523. Full text in Research Archive Show summary

  In CE the charged DNA strands are fractionated according to fragment lengths as they migrate through the capillary, since shorter DNA fragments pass through the sieving matrix faster. Multiplexed internal size standards are used to estimate the size of unknown DNA fragments. In the literature there are statements about migration abnormalities for the 250 and 340 bp fragments in the GeneScan-500 (GS500) internal size standards. Such anomalous migration of size standards could obviously introduce errors in the estimation of unknown fragments. Therefore, a number of analysis programs simply exclude some of these fragments. In the present work we first evaluate the effect of excluding each of the fragments in the internal size standards used in CE. Next, a method which is based on estimating the true values of the anomalous fragments is presented. The results obtained by the new method indicate a significant improvement compared to results obtained when one (or both) of the anomalous fragments in GS500 is (are) excluded or included when estimating the size of unknown DNA fragments. In the higher-molecular-weight region, the average error is reduced from 1.91 bp in ABI GeneMapper (excluding 250 bp) to 0.15 bp in the new method (using the estimated values for 250 and 340 bp). In the lower-molecular-weight region, excluding both fragments will improve the results by an average of 0.74 bp compared to ABI GeneMapper.

• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard E. (2005). Fractal analysis of monolayer cell nuclei from two different prognostic classes of early ovarian cancer. In Losa, G.A.; Nonnenmacher, T.F. & Weibel, E.R. (Ed.), Fractals in Biology and Medicine. Birkhäuser Verlag. ISSN 9783764371722. p. 175–186. Full text in Research Archive
• Cvancarova, Milada; Albregtsen, Fritz; Brabrand, Knut & Samset, Eigil (2005). Segmentation of ultrasound images of liver tumors applying snake algorithms and GVF. Excerpta Medica: International Congress Series. ISSN 0531-5131. p. 218–223. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard Emil (2004). Low dimensional adaptive texture feature vectors from class distance and class difference matrices. IEEE Transactions on Medical Imaging. ISSN 0278-0062. 23, p. 73–84. Full text in Research Archive
• Schulerud, Helene & Albregtsen, Fritz (2004). Many are called, but few are chosen. Feature selection and error estimation in high dimensional spaces. Computer Methods and Programs in Biomedicine. ISSN 0169-2607. 73, p. 91–99. Full text in Research Archive
• Akbari, Akbar & Albregtsen, Fritz (2003). Normalizing the background and removing the trend in one-dimensional DNA fingerprint images. Journal of Chromatography A. ISSN 0021-9673. 1014, p. 11–19. Full text in Research Archive
• Albregtsen, Fritz; Nielsen, Birgitte & Danielsen, Håvard E. (2003). Cancer Diagnostics and Prognostics by Low Dimensional Adaptive Texture Features from Fractal Signature and Lacunarity Matrices. In Capasso, V. (Eds.), Mathematical Modelling & Computing in Biology and Medicine. Milan Research Centre for Industrial and Applied Mathematics. ISSN 9788874880553. p. 511–517. Full text in Research Archive
• Schulerud, Helene & Albregtsen, Fritz (2002). Effects of many feature candidates in feature selection and classification, Lecture Notes in Computer Science. p. 480–487. Full text in Research Archive
• Akbari, Akbar; Albregtsen, Fritz & Lingjærde, Ole Christian (2002). Adaptive weighted least squares method for estimation of DNA fragment lenghts from agaros gels. Electrophoresis. ISSN 0173-0835. 23(2), p. 176–181. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard E. (2002). Fractal signature vectors and lacunarity class distance matrices to extract new adaptive texture features from cell nuclei. Mathematics and bioscience in interaction. Fractals in biology and medicine. 3, p. 55–65. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz; Kildal, Wanja & Danielsen, Håvard E. (2001). Prognostic classification of early ovarian cancer based on very low dimensionality adaptive texture feature vectors from cell nuclei from monolayers and histological sections. Analytical Cellular Pathology. ISSN 0921-8912. 23, p. 75–88. Full text in Research Archive
• Albregtsen, Fritz & Nielsen, Birgitte (2000). Texture classification based on cooccurrence of gray level run length matrices. Australian Journal of Intelligent Information Processing Systems. ISSN 1321-2133. 6(1), p. 38–45. Full text in Research Archive Show summary

  We introduce the 4D Cooccurrence of Gray Level Run Length Matrix. Adaptive texture features are obtained by weighted summations of the associated 2D sum and difference matrix elements, using class distance matrices as weights, and the positive/negative parts of the class difference matrices as the domains of the summation. This is applied to about 2000 liver cell nuclei from two classes.

• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard E. (1999). The use of Fractal Features from the Periphery of Cell Nuclei as a Classification Tool. Analytical Cellular Pathology. ISSN 0921-8912. 19(1), p. 21–37. Full text in Research Archive
• Baheerathan, Sivalingam; Albregtsen, Fritz & Danielsen, Håvard E. (1999). New texture features based on the complexity curve. Pattern Recognition. ISSN 0031-3203. 32, p. 605–618. Full text in Research Archive
• Baheerathan, Sivalingam; Albregtsen, Fritz & Danielsen, Håvard E. (1998). Registration of serial sections of mouse liver cell nuclei. Journal of Microscopy. ISSN 0022-2720. 192, p. 37–53. Full text in Research Archive
• Kristensen, Gunnar B.; Liestøl, Knut; Vlatkovic, L.; Reith, Albrecht; Albregtsen, Fritz & Danielsen, Håvard E. (1998). A review of caveats in statistical nuclear image analysis. Analytical Cellular Pathology. ISSN 0921-8912. 16, p. 63–82. Full text in Research Archive
• Yogesan, Kanagasingam; Schulerud, Helene; Albregtsen, Fritz & Danielsen, Håvard E. (1998). Ultrastrctural texture analysis as a diagnostic tool in mouse liver carcinogenesis. Ultrastructural Pathology. ISSN 0191-3123. p. 27–37. Full text in Research Archive
• Yang, Luren; Albregtsen, Fritz & Taxt, Torfinn (1997). Fast computation of three-dimensional geometric moments using a discrete divergence theorem and a generalization to higher dimensions. Graphical Models and Image Processing. ISSN 1077-3169. 59(2), p. 97–108. Full text in Research Archive
• Yogesan, Kanagasingam; Jørgensen, Trond; Albregtsen, Fritz; Tveter, Kjell & Danielsen, Håvard E. (1996). Entropy-based texture analysis of chromatin structure in advanced prostate cancer. Cytometry. ISSN 0196-4763. 24, p. 268–276. Full text in Research Archive
• Yang, Luren & Albregtsen, Fritz (1996). Fast and exact computation of Cartesian geometric moments using discrete Green's theorem. Pattern Recognition. ISSN 0031-3203. 29(7), p. 1061–1073. Full text in Research Archive
• Yang, Luren; Albregtsen, Fritz; Lønnestad, T; Grøttum, Per; Iversen, Jens Gustav & Røtnes, Jan Sigurd [Show all 7 contributors for this article] (1995). Measuring shape and motion of white blood cells from a sequence of fluorescence microscopy images. In Borgefors, G (Eds.), Theory and applications of image analysis II. World Scientific, Singapore. p. 305–316. Full text in Research Archive

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• Albregtsen, Fritz & Skagestein, Gerhard (2007). Digital representasjon av tekster, tall, former, lyd, bilder og video, 2. utgave. Unipub forlag. ISBN 9788274773189. 387 p. Full text in Research Archive
• Albregtsen, Fritz & Skagestein, Gerhard (2006). Digital representasjon av tekster, tall, former, lyd, bilder og video. Unipub forlag. ISBN 9788274772656. 387 p. Full text in Research Archive

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• Kumar, Rahul Prasanna; Albregtsen, Fritz; Reimers, Martin; Edwin, Bjørn & Elle, Ole Jakob (2013). Novel blood vessel segmentation method. Full text in Research Archive
• Holmen, Sigve Dhondup; Kleppa, Elisabeth; Lillebø, Kristine; Taylor, M.; Albregtsen, Fritz & Kjetland, Eyrun Floerecke (2013). Diagnosing female genital schistosomiasis. Tropical medicine & international health. ISSN 1360-2276. 18, p. 56–56. Full text in Research Archive
• Kumar, Rahul Prasanna; Albregtsen, Fritz; Reimers, Martin; Langø, Thomas; Edwin, Bjørn & Elle, Ole Jakob (2013). 3D multiscale vessel enhancement based centerline extraction of blood vessels. Full text in Research Archive
• Holmen, Sigve Dhondup; Kleppa, Elisabeth; Lillebø, Kristine; Moodley, Jayeshnee; Taylor, Myra & Albregtsen, Fritz [Show all 9 contributors for this article] (2013). A Novel, Diagnostic Tool for Female Genital Schistosomiasis in Low-Resource Settings. Full text in Research Archive
• Holmen, Sigve Dhondup; Kleppa, Elisabeth; Lillebø, Kristine; Taylor, Myra; Albregtsen, Fritz & Kjetland, Eyrun Flørecke (2013). Diagnosing Female Genital Schistosomiasis. Full text in Research Archive
• Kumar, Rahul Prasanna; Albregtsen, Fritz & Elle, Ole Jakob (2012). 3D blood vessel centreline extraction for catheter based navigation. Full text in Research Archive
• Holmen, Sigve; Lillebø, Kristine; Kleppa, Elisabeth; Kjetland, Eyrun Flørecke & Albregtsen, Fritz (2012). Computerized image analysis as a tool for identification of clinical manifestations in Female Genital Schistosomiasis. Full text in Research Archive
• Kumar, Rahul Prasanna; Albregtsen, Fritz; Reimers, Martin; Langø, Thomas & Elle, Ole Jakob (2012). A faster centreline tracking of blood vessels. Full text in Research Archive
• Nielsen, B; Albregtsen, Fritz & Danielsen, Håvard Emil (2010). AUTOMATIC SEGMENTATION OF CELL NUCLEI IN HISTOLOGICAL SECTIONS. Cellular Oncology. ISSN 1570-5870. 32(3), p. 180–180. Full text in Research Archive
• Dunn, J. M.; Lovat, L. B.; Pretorius, M; Oukrif, D.; Hveem, Tordis & Nielsen, Bettina [Show all 9 contributors for this article] (2010). COMBINATION OF NUCLEAR TEXTURAL ANALYSIS AND IMAGE CYTOMETRIC DNA ANALYSIS IS MORE ACCURATE THAN IMAGE CYTOMETRIC DNA PLOIDY ANALYSIS ALONE FOR RISK STRATIFICATION IN BARRETT'S OESOPHAGUS. Gut. ISSN 0017-5749. 59, p. A114–A115. doi: 10.1136/gut.2009.208983r. Full text in Research Archive
• Albregtsen, Fritz (2009). How to calculate the goodness-of-fit of a fractal dimension. Cellular Oncology. ISSN 1570-5870. 31(6), p. 501–501. doi: 10.3233/CLO-2009-0506. Full text in Research Archive
• Nielsen, B; Albregtsen, Fritz & Danielsen, HE (2008). A review of statistical nuclear texture analysis in cancer research. Cellular Oncology. ISSN 1570-5870. 30, p. 165–165. Full text in Research Archive
• Cvancarova, Milada & Albregtsen, Fritz (2007). Towards a method to compare and evaluate segmentation results of image processing methods applied on medical images. International Journal of Computer Assisted Radiology and Surgery. ISSN 1861-6410. 2, p. 476–476. Full text in Research Archive
• Cvankarova, Milada; Albregtsen, Fritz; Braband, Knut & Samset, Eigil (2005). Segmentation of ultrasound images of liver tumors applying snake algorithms and GVF. Full text in Research Archive
• Nielsen, Birgitte & Albregtsen, Fritz (2004). Fractal analysis of monolayer cell nuclei from two different prognostic classes of early ovarian cancer. Full text in Research Archive
• Akbari, Akbar & Albregtsen, Fritz (2004). Evaluation of Noise in DNA Fingerprint Images Produced by Hybridization Techniques. Full text in Research Archive
• Akbari, Akbar & Albregtsen, Fritz (2004). Automatic Lane Detection and Separation in One Dimensional DNA gel images. Full text in Research Archive
• Akbari, Akbar & Albregtsen, Fritz (2004). Automatic segmentation of DNA bands in one dimensional gel images produced by hybridizing techniques. Full text in Research Archive
• Albregtsen, Fritz & Nygreen, Thomas (2003). On the variability of the CCR in ML classification. Full text in Research Archive
• Albregtsen, Fritz & Schulerud, Helene (2003). Leave-one-out classification error estimation in high dimensional feature spaces - the usual way, and the right way. Full text in Research Archive
• Baheerathan, Sivalingam; Albregtsen, Fritz; Nielsen, Birgitte & Danielsen, Håvard E. (2003). Complexity graylevel matrix - a new texture analysis method. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard E. (2003). Nuclear texture analysis of two different prognostic classes of early ovarian cancer based on gray level entropy matrices. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard E. (2003). Local binary pattern matrix - a new approach to nuclear texture analysis. Full text in Research Archive
• Albregtsen, Fritz & Nielsen, Birgitte (2002). Adaptive low dimensional texture features from fractal signature vectors and lacunarity matrices. Full text in Research Archive
• Akbari, Akbar & Albregtsen, Fritz (2002). Normalizing Background Trend in One-Dimensional DNA Fingerprint Images. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard E. (2002). Transforming 2D images to 1D signals to obtain radially differentiated fractal features from early ovarian cancer cell nuclei. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard E. (2002). Statistical texture analysis - robustness versus number of gray levels. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard E. (2002). Two adaptive texture features based on multidimensional gray level cooccurrence marices. Full text in Research Archive
• Schulerud, Helene & Albregtsen, Fritz (2002). Effects of many feature candidates in feature selection and classification. Full text in Research Archive
• Albregtsen, Fritz; Nielsen, Birgitte & Danielsen, Håvard E. (2002). A compact set of adaptive features from cooccurrence of gray level run length matrices. Full text in Research Archive
• Albregtsen, Fritz; Nielsen, Birgitte & Danielsen, Håvard E. (2002). Computing adaptive fractal features from gray level images of cell nuclei. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz; Kildal, Wanja & Danielsen, Håvard E. (2001). The extraction of low dimensionality adaptive texture feature vectors from the periphery and center of ovarian cell nuclei from monolayers and histological sections. Full text in Research Archive
• Akbari, Akbar & Albregtsen, Fritz (2001). BACKGROUND NORMALIZATION OF DNA FINGERPRINT IMAGES. Full text in Research Archive
• Akbari, Akbar; Albregtsen, Fritz & Lingjærde, Ole Christian (2001). ADAPTIVE WEIGHTED LEAST SQUARES METHOD FOR ESTIMATION OF DNA FRAGMENT LENGHTS FROM AGAROS GELS. Full text in Research Archive
• Albregtsen, Fritz; Nielsen, Birgitte & Danielsen, Håvard E. (2001). A unified approach to low dimensionality adaptive texture feature extraction applied to ovarian cancer prognosis estimation. Full text in Research Archive
• Albregtsen, Fritz; Nielsen, Birgitte & Danielsen, Håvard E. (2000). Adaptive gray level run length features obtained from class distance matrices. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz; Baheerathan, Sivalingam & Danielsen, Håvard E. (2000). Peel-off-scanning to obtain radial differentiation of fractal and complexity features in cell nuclei. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard E. (2000). Using fractal signature vectors and lacunarity distance matrices to extract new adaptive features from cell nuclei. Full text in Research Archive
• Nielsen, Birgitte; Albregtsen, Fritz; Baheerathan, Sivalingam & Danielsen, Håvard E. (2000). Peel-off-scanning to obtain radial differentiation of fractal and complexity features in cell nuclei. Full text in Research Archive Show summary

  A polygonization-based method is used to estimate fractal features from digitized transmission electron micrographs (TEM) of mouse liver cell nuclei. In order to obtain separate estimates of the development of fractal features in the center and periphery of a cell nucleus during carcinogenesis, the fractal features have been estimated from 1D curves obtained by scanning the 2D cell nuclei in a spiral-like fashion called ``peel-off-scanning''. The peripheral part (outer $30\%$) of the cell nuclei contained important texture information about the differences between the classes. The classification performance of five complexity features were also enhanced when separate estimates were made in the center and periphery of the cell nuclei. The combination of two features and two segments, one feature from the 30% peripheral part and one feature from the 70\% central part of the cell nuclei, gave good classification results for the four class problem of normal, regenerating, noduli and tumor classes.

• Albregtsen, Fritz; Nielsen, Birgitte & Danielsen, Håvard E. (2000). Adaptive gray level run length features obtained from class distance matrices. Full text in Research Archive Show summary

  We have constructed class distance matrices for the Gray Level Run Length texture analysis method. For a four-class problem of liver cell nuclei, we have found that there exist areas of consistently high values in the class distance matrices. We have combined the information from the entries of the normalized run length matrix, based on the class distance matrices, to obtain adaptive features for texture classification. Using this procedure, we have extracted only two features, which halved the classification error when compared to the best pair of classical GLRLM features.

• Nielsen, Birgitte; Albregtsen, Fritz & Danielsen, Håvard E. (1999). Diagnostic classification based on fractal features in the periphery of cell nuclei from liver lesions. Full text in Research Archive
• Yang, Luren; Albregtsen, Fritz; Lønnestad, Tor; Grøttum, Per & Borgefors, Gunilla (1999). Measuring shape and motion of white blood cells from sequences of fluorescence microskopy. Full text in Research Archive
• Schulerud, Helene; Kristensen, Gunnar B.; Albregtsen, Fritz; Liestøl, Knut & Danielsen, Håvard E. (1997). Prognosis of cervix cancer. Full text in Research Archive
• Schulerud, Helene; Kristensen, Gunnar B.; Albregtsen, Fritz; Liestøl, Knut & Danielsen, Håvard E. (1996). Prognosis of cervix cancer using texture analysis. Full text in Research Archive
• Yang, Luren; Albregtsen, Fritz; Lønnestad, Tor; Grøttum, Per; Hlavác, Václav & Sára, Radim (1996). A supervised approach to the evaluation of image segmentation methods. Full text in Research Archive

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