Computer-aided diagnosis of mammographic microcalcification clusters

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Computer-aided diagnosis of mammographic microcalcification clusters.

Computer-aided diagnosis techniques in medical imaging are developed for the automated differentiation between benign and malignant lesions and go beyond computer-aided detection by providing cancer likelihood for a detected lesion given image and/or patient characteristics. The goal of this study was the development and evaluation of a computer-aided detection and diagnosis algorithm for mammo...

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Modelling mammographic microcalcification clusters using persistent mereotopology

In mammographic imaging, the presence of microcalcifications, small deposits of calcium in the breast, is a primary indicator of breast cancer. However, not all microcalcifications are malignant and their distribution within the breast can be used to indicate whether clusters of microcalcifications are benign or malignant. Computer-aided diagnosis (CAD) systems can be employed to help classify ...

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A novel approach to computer-aided diagnosis of mammographic images

-This is a work-in-progress report of a research endeavor that deals with the design and development of a novel approach to computer-aided diagnosis (CAD) of mammographic images. With the initial emphasis being on the analysis of microcalcifications, the proposed approach defines a synergistic paradigm that utilizes new methodologies together with previously developed techniques. The new paradi...

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Topological Modelling and Classification of Mammographic Microcalcification Clusters

Goal: The presence of microcalcification clusters is a primary sign of breast cancer; however, it is difficult and time consuming for radiologists to classify microcalcifications as malignant or benign. In this paper, a novel method for the classification of microcalcification clusters in mammograms is proposed. Methods: The topology/connectivity of individual microcalcifications is analysed wi...

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ژورنال

عنوان ژورنال: Medical Physics

سال: 2004

ISSN: 0094-2405

DOI: 10.1118/1.1637972