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Breast cancer is the most commonly diagnosed and the second leading cause of cancer death among women. In this paper we have proposed a multi stage system for detection of microcalcification using adaptive algorithms. Conventional image processing techniques do not perform well on mammographic images. The large variation in feature size and shape reduces the effectiveness of classical fixed neighborhood...
HER-2/neu, a protein often giving higher aggressiveness in breast cancers, has been shown that if the gene is expanded for some reason, the Her-2 protein produced by the cells will be over-expressed to enhance the cancer cells reproduced ability, the prognosis will be also relatively less, too. The HER-2 immunohistochemical stained provides a simple and reliable method for pathologist in clinical...
In this paper we present a high accuracy computer-aided diagnosis scheme. The goal of the developed system is to classify benign and malignant microcalcifications on mammograms. It is mainly based on a combination of wavelet decomposition, feature extraction and classification methodology using Fisherpsilas linear discriminant. The contribution of wavelet decomposition is to denoise and to enhance...
Hormone receptors have been used in prognosis of breast carcinomas and their positive status is of clinical value in hormonal therapy. Determination of this status is based on the subjective visual inspection of the stained nuclei in the specimens. The aim of this study was the assessment of the estrogen receptor's (ER) positive status of breast carcinomas, by means of colour-texture based image analysis...
A new algorithm by using geometric active contour model with the fusion of color and intensity priors to segment medical images has been presented in this paper. The prior knowledge used here are firstly defined in different color spaces and represented as thresholds searched by genetic algorithm. Then the prior knowledge is merged into active contour model with its contour evolution by the level...
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