Displaying similar documents to “Nuclei segmentation for computer-aided diagnosis of breast cancer”

Segmentation of breast cancer fine needle biopsy cytological images

Maciej Hrebień, Piotr Steć, Tomasz Nieczkowski, Andrzej Obuchowicz (2008)

International Journal of Applied Mathematics and Computer Science

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This paper describes three cytological image segmentation methods. The analysis includes the watershed algorithm, active contouring and a cellular automata GrowCut method. One can also find here a description of image pre-processing, Hough transform based pre-segmentation and an automatic nuclei localization mechanism used in our approach. Preliminary experimental results collected on a benchmark database present the quality of the methods in the analyzed issue. The discussion of common...

Classification of breast cancer malignancy using cytological images of fine needle aspiration biopsies

Thomas Fevens, Adam Krzyżak (2008)

International Journal of Applied Mathematics and Computer Science

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According to the World Health Organization (WHO), breast cancer (BC) is one of the most deadly cancers diagnosed among middle-aged women. Precise diagnosis and prognosis are crucial to reduce the high death rate. In this paper we present a framework for automatic malignancy grading of fine needle aspiration biopsy tissue. The malignancy grade is one of the most important factors taken into consideration during the prediction of cancer behavior after the treatment. Our framework is based...

Texture analysis in perfusion images of prostate cancer - A case study

Jacek Śmietański, Ryszard Tadeusiewicz, Elżbieta Łuczyńska (2010)

International Journal of Applied Mathematics and Computer Science

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The analysis of prostate images is one of the most complex tasks in medical images interpretation. It is sometimes very difficult to detect early prostate cancer using currently available diagnostic methods. But the examination based on perfusion computed tomography (p-CT) may avoid such problems even in particularly difficult cases. However, the lack of computational methods useful in the interpretation of perfusion prostate images makes it unreliable because the diagnosis depends mainly...

Circular object detection using a modified Hough transform

Marcin Smereka, Ignacy Dulęba (2008)

International Journal of Applied Mathematics and Computer Science

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A practical modification of the Hough transform is proposed that improves the detection of low-contrast circular objects. The original circular Hough transform and its numerous modifications are discussed and compared in order to improve both the efficiency and computational complexity of the algorithm. Medical images are selected to verify the algorithm. In particular, the algorithm is applied to localize cell nuclei of cytological smears visualized using a phase contrast microscope. ...

Fusion based analysis of ophthalmologic image data

Jiří Jan, Radim Kolář, Libor Kubečka, Jan Odstrčilík, Jiří Gazárek (2011)

Kybernetika

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The paper presents an overview of image analysis activities of the Brno DAR group in the medical application area of retinal imaging. Particularly, illumination correction and SNR enhancement by registered averaging as preprocessing steps are briefly described; further mono- and multimodal registration methods developed for specific types of ophthalmological images, and methods for segmentation of optical disc, retinal vessel tree and autofluorescence areas are presented. Finally, the...

4D Embryogenesis image analysis using PDE methods of image processing

Paul Bourgine, Róbert Čunderlík, Olga Drblíková-Stašová, Karol Mikula, Mariana Remešíková, Nadine Peyriéras, Barbara Rizzi, Alessandro Sarti (2010)

Kybernetika

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In this paper, we introduce a set of methods for processing and analyzing long time series of 3D images representing embryo evolution. The images are obtained by in vivo scanning using a confocal microscope where one of the channels represents the cell nuclei and the other one the cell membranes. Our image processing chain consists of three steps: image filtering, object counting (center detection) and segmentation. The corresponding methods are based on numerical solution of nonlinear...

Selecting differentially expressed genes for colon tumor classification

Krzysztof Fujarewicz, Małgorzata Wiench (2003)

International Journal of Applied Mathematics and Computer Science

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DNA microarrays provide a new technique of measuring gene expression, which has attracted a lot of research interest in recent years. It was suggested that gene expression data from microarrays (biochips) can be employed in many biomedical areas, e.g., in cancer classification. Although several, new and existing, methods of classification were tested, a selection of proper (optimal) set of genes, the expressions of which can serve during classification, is still an open problem. Recently...