What question did this study set out to answer?

To develop an automated contrast enhancement and segmentation framework using quantile separated histogram equalisation to assist radiologists in mammogram evaluation.

April 24, 2019CAAI Transactions on Intelligence TechnologyOpen Access

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

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Authors

BGB. M. GuptaCentral Drug Research Institute MTMayank TiwariInstitute of Management Technology SLSubir Singh LambaIndian Institute of Information Technology Design and Manufacturing Jabalpur

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Implication

Computational study demonstrates improved contrast enhancement and mass segmentation in mammograms, highlighting enhanced visual clarity for radiological diagnosis.

Key Points

To develop an automated contrast enhancement and segmentation framework using quantile separated histogram equalisation to assist radiologists in mammogram evaluation.
Designed a software pipeline combining linearly quantile separated histogram equalisation with grey relational analysis for global and local contrast enhancement.
Evaluated enhancement and breast-region segmentation performance on mammogram images from the Mammographic Image Analysis Society (MIAS) dataset.
Enhanced local and global contrast across mammogram images, improving the visibility and interpretation of hidden anatomical details.
Achieved superior breast-region and mass segmentation performance compared to existing state-of-the-art techniques.

Cite This Study

Gupta et al. (2019) studied this question.

synapsesocial.com/papers/6a76a98233def31403adf445 https://doi.org/10.1049/trit.2018.1006

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Implication

Computational study demonstrates improved contrast enhancement and mass segmentation in mammograms, highlighting enhanced visual clarity for radiological diagnosis.

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

Discussion

Member takes

Implication

Key Points

Cite This Study

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

Discussion

Member takes

Implication

Key Points

Cite This Study

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