Deep multiple instance hashing for scalable medical image retrieval

Conjeti S, Paschali M, Katouzian A, Navab N (2017)

Publication Type: Conference contribution

Publication year: 2017

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Verlag

Book Volume: 10435 LNCS

Pages Range: 550-558

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Quebec City, QC, CAN

ISBN: 9783319661780

DOI: 10.1007/978-3-319-66179-7_63

Abstract

In this paper, for the first time, we introduce a multiple instance (MI) deep hashing technique for learning discriminative hash codes with weak bag-level supervision suited for large-scale retrieval. We learn such hash codes by aggregating deeply learnt hierarchical representations across bag members through an MI pool layer. For better trainability and retrieval quality, we propose a two-pronged approach that includes robust optimization and training with an auxiliary single instance hashing arm which is down-regulated gradually. We pose retrieval for tumor assessment as an MI problem because tumors often coexist with benign masses and could exhibit complementary signatures when scanned from different anatomical views. Experimental validations demonstrate improved retrieval performance over the state-of-the-art methods.

Involved external institutions

Technische Universität München (TUM) DE Germany (DE) IBM Research - Almaden US United States (USA) (US)

How to cite

APA:

Conjeti, S., Paschali, M., Katouzian, A., & Navab, N. (2017). Deep multiple instance hashing for scalable medical image retrieval. In Lena Maier-Hein, Alfred Franz, Pierre Jannin, Simon Duchesne, Maxime Descoteaux, D. Louis Collins (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 550-558). Quebec City, QC, CAN: Springer Verlag.

MLA:

Conjeti, Sailesh, et al. "Deep multiple instance hashing for scalable medical image retrieval." Proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, Quebec City, QC, CAN Ed. Lena Maier-Hein, Alfred Franz, Pierre Jannin, Simon Duchesne, Maxime Descoteaux, D. Louis Collins, Springer Verlag, 2017. 550-558.

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