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Abstract

A method and system to detect the microcalcifications (MC) in different type of images viz. X-ray images/mammograms/computer tomography with varied densities using nonlinear energy operator (NEO) is disclosed to favor precise detection of early breast cancer. Such Microcalcifications are associated with both high intensity and high frequency content. The same NEO output is useful to detect and remove the irrelevant curvilinear structures (CLS) thereby helps in reducing the false alarms in micro calcification detection technique. This is effective on different dataset (scanned film, mammograms with large spatial resolution such as CR and DR) of varied breast composition (viz. dense, fatty glandular, fatty), demonstrated quantitatively by Free-response receiver operating characteristic (FROC). Importantly, the method and apparatus of the invention can be used in conjunction with machine learning techniques viz. SVM to favor detection of incipient or small microcalcifications, thus benefiting radiologists in confirming detection of micro-calcifications in X-rays images/mammograms and reducing death rates.

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First Claim