Classification and detection in mammograms with weak supervision via dual branch deep neural net

Ran Bakalo; Rami Ben-Ari; Jacob Goldberger

doi:10.1109/ISBI.2019.8759458

Classification and detection in mammograms with weak supervision via dual branch deep neural net

Ran Bakalo, Rami Ben-Ari, Jacob Goldberger

Bar-Ilan University - The Alexander Kofkin Faculty of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

The high cost of generating expert annotations, poses a strong limitation for supervised machine learning methods in medical imaging. Weakly supervised methods may provide a solution to this tangle. In this study, we propose a novel deep learning architecture for multi-class classification of mammograms according to the severity of their containing anomalies, having only a global tag over the image. The suggested scheme further allows localization of the different types of findings in full resolution. The new scheme contains a dual branch network that combines region-level classification with region ranking. We evaluate our method on a large multi-center mammography dataset including 3,000 mammograms with various anomalies and demonstrate the advantages of the proposed method over a previous weakly-supervised strategy.

Original language	English
Title of host publication	ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
Publisher	IEEE Computer Society
Pages	1905-1909
Number of pages	5
ISBN (Electronic)	9781538636411
DOIs	https://doi.org/10.1109/ISBI.2019.8759458
State	Published - Apr 2019
Event	16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 - Venice, Italy Duration: 8 Apr 2019 → 11 Apr 2019

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2019-April
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
Country/Territory	Italy
City	Venice
Period	8/04/19 → 11/04/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Deep learning
Mammography
Weakly supervision

Access to Document

10.1109/ISBI.2019.8759458

Cite this

Bakalo, R., Ben-Ari, R., & Goldberger, J. (2019). Classification and detection in mammograms with weak supervision via dual branch deep neural net. In ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging (pp. 1905-1909). Article 8759458 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2019-April). IEEE Computer Society. https://doi.org/10.1109/ISBI.2019.8759458

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title = "Classification and detection in mammograms with weak supervision via dual branch deep neural net",

abstract = "The high cost of generating expert annotations, poses a strong limitation for supervised machine learning methods in medical imaging. Weakly supervised methods may provide a solution to this tangle. In this study, we propose a novel deep learning architecture for multi-class classification of mammograms according to the severity of their containing anomalies, having only a global tag over the image. The suggested scheme further allows localization of the different types of findings in full resolution. The new scheme contains a dual branch network that combines region-level classification with region ranking. We evaluate our method on a large multi-center mammography dataset including 3,000 mammograms with various anomalies and demonstrate the advantages of the proposed method over a previous weakly-supervised strategy.",

keywords = "Deep learning, Mammography, Weakly supervision",

author = "Ran Bakalo and Rami Ben-Ari and Jacob Goldberger",

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year = "2019",

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doi = "10.1109/ISBI.2019.8759458",

language = "אנגלית",

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Bakalo, R, Ben-Ari, R & Goldberger, J 2019, Classification and detection in mammograms with weak supervision via dual branch deep neural net. in ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging., 8759458, Proceedings - International Symposium on Biomedical Imaging, vol. 2019-April, IEEE Computer Society, pp. 1905-1909, 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019, Venice, Italy, 8/04/19. https://doi.org/10.1109/ISBI.2019.8759458

Classification and detection in mammograms with weak supervision via dual branch deep neural net. / Bakalo, Ran; Ben-Ari, Rami; Goldberger, Jacob.
ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, 2019. p. 1905-1909 8759458 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Classification and detection in mammograms with weak supervision via dual branch deep neural net

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