Advancing mammography breast mass detection through diffusion segmentation-Reference-Cited by-同舟云学术

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Advancing mammography breast mass detection through diffusion segmentation

Published:2024-03-27 Issue: Volume: Page:
ISSN:1573-7721
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Guerroudji Mohamed Amine,Amara Kahina,Zenati Nadia

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11042-024-18840-6.pdf

Reference36 articles.

1. Touil A, Kalti K, Conze PH, Solaiman B, Mahjoub MA (2020) Automatic detection of microcalcification based on morphological operations and structural similarity indices. Biocybernetics Biomed Eng 40(3):1155–1173

2. Loizidou K, Elia R, Pitris C (2023) Computer-aided breast cancer detection and classification in mammography: a comprehensive review. Computers in Biology and Medicine, 106554

3. Huffpost Maghreb (2015) http://www.huffpostmaghreb.com/2015/04/05/cancer-sein-algerie-n_7007174.html. Accessed 03 Dec 2015

4. Guerroudji MA, Ameur Z (2015) New approaches for contrast enhancement of calcifications in mammography using morphological enhancement. In: Proceedings of the international conference on intelligent information processing, security and advanced communication, pp 1–5

5. Diaz-Huerta CC, Felipe- Riveron EM, Montaño- Zetina LM (2014) Quantitative analysis of morphological techniques for automatic classification of micro-calcifications in digitized mammograms. Expert Syst Appl 41(16):7361–7369

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