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Proceedings ArticleDOI

A novel shape and boundary extraction image processing technique for detecting the breast abnormalities using digital mammogram - labview implementation

N.M. Sangeetha, +1 more
- pp 1-4
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TLDR
This research paper describes a novel method for detection of breast abnormalities using image processing techniques that reduces the mortality rate and improve the human awareness.
Abstract
Computer Aided Detection (CAD) increases the early detection of breast abnormalities in digital mammogram. Digital mammogram is the low energy and efficient screening tool to detect the breast abnormalities detective of breast abnormalities is carried out by using digital mammogram. The micro calcification and masses are the important sign to detect the breast abnormalities due to low contrast nature of these images, it is difficult to detect. This research paper describes a novel method for detection of breast abnormalities using image processing techniques are 1. Shape extraction 2. Boundary of mass or lesion So that signatures can be assigned for detection of breast abnormalities on masses and micro calcification of breast. The main aim of this paper to reduces the mortality rate and improve the human awareness.

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References
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Journal ArticleDOI

Lesion contrast enhancement in medical ultrasound imaging

TL;DR: Methods for improving the contrast-to-noise ratio (CNR) of low-contrast lesions in medical ultrasound imaging are described and Automated graylevel mapping is used in combination with a contrast-weighted form of frequency-diversity speckle reduction.
Book ChapterDOI

A stochastic model for automated detection of calcifications in digital mammograms

TL;DR: A stochastic model is developed to enable pattern classification in mammograms based on Bayesian decision theory to ensure that faint spots are only interpreted as calcifications if they are in the neighborhood of others.
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