Visibility improvement and mass segmentation of mammogram images using quantile separated histogram equalisation with local contrast enhancement

CAAI Transactions on Intelligence Technology

article

Bhupendra Gupta¹  Mayank Tiwari¹  Subir Singh Lamba¹ 

[1] PDPM Indian Institute of Information Technology

关键词: mammography;    image segmentation;    image enhancement;    medical image processing;    mass segmentation;    mammogram image;    local contrast enhancement;    specific end goal;    visual elucidation;    mammogram masses;    basic breast-region segmentation;    software-based approach;    visibility improvement;    linearly quantile separated histogram equalisation;    grey relational analysis;    mamographic image analysis society-MI;    MIAS-MI;    A8760J X-rays and particle beams (medical uses);    A8770E Patient diagnostic methods and instrumentation;    B6135 Optical;    image and video signal processing;    B7510P X-ray techniques radiography and computed tomography (biomedical imaging/measurement);    C5260B Computer vision and image processing techniques;    C7330 Biology and medical computing;   

DOI  :  10.1049/trit.2018.1006

学科分类：数学（综合）

来源: Wiley

【 摘 要 】

In this work, the authors develop a working software-based approach named ‘linearly quantile separated histogram equalisation-grey relational analysis’ for mammogram image (MI). This approach improves overall contrast (local and global) of given MI and segments breast-region with a specific end goal to acquire better visual elucidation, examination, and grouping of mammogram masses to help radiologists in settling on more precise choices. The fundamental commitment of this work is to demonstrate that results of good quality of breast-region segmentation can be accomplished from basic breast-region segmentation if the input image has good contrast and a better interpretation of hidden details. They have evaluated the proposed strategy for MIAS-MIs. Experimental results have shown that the proposed approach works better than state-of-the-art.

【 授权许可】

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