Displaying similar documents to “Classification of breast cancer malignancy using cytological images of fine needle aspiration biopsies”

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...

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...

Towards spike-based speech processing: A biologically plausible approach to simple acoustic classification

Ismail Uysal, Harsha Sathyendra, John G. Harris (2008)

International Journal of Applied Mathematics and Computer Science

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Shortcomings of automatic speech recognition (ASR) applications are becoming more evident as they are more widely used in real life. The inherent non-stationarity associated with the timing of speech signals as well as the dynamical changes in the environment make the ensuing analysis and recognition extremely difficult. Researchers often turn to biology seeking clues to make better engineered systems, and ASR is no exception with the usage of feature sets such as Mel frequency cepstral...

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. ...

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...

Comparison of speaker dependent and speaker independent emotion recognition

Jan Rybka, Artur Janicki (2013)

International Journal of Applied Mathematics and Computer Science

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This paper describes a study of emotion recognition based on speech analysis. The introduction to the theory contains a review of emotion inventories used in various studies of emotion recognition as well as the speech corpora applied, methods of speech parametrization, and the most commonly employed classification algorithms. In the current study the EMO-DB speech corpus and three selected classifiers, the k-Nearest Neighbor (k-NN), the Artificial Neural Network (ANN) and Support Vector...