Attention Based Multiple Instance Learning for Classification of Blood Cell Disorders

Sadafi A, Makhro A, Bogdanova A, Navab N, Peng T, Albarqouni S, Marr C (2020)

Publication Type: Conference contribution

Publication year: 2020

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Science and Business Media Deutschland GmbH

Book Volume: 12265 LNCS

Pages Range: 246-256

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

Event location: Lima, PER

ISBN: 9783030597214

DOI: 10.1007/978-3-030-59722-1_24

Abstract

Red blood cells are highly deformable and present in various shapes. In blood cell disorders, only a subset of all cells is morphologically altered and relevant for the diagnosis. However, manually labeling of all cells is laborious, complicated and introduces inter-expert variability. We propose an attention based multiple instance learning method to classify blood samples of patients suffering from blood cell disorders. Cells are detected using an R-CNN architecture. With the features extracted for each cell, a multiple instance learning method classifies patient samples into one out of four blood cell disorders. The attention mechanism provides a measure of the contribution of each cell to the overall classification and significantly improves the networks classification accuracy as well as its interpretability for the medical expert.

Involved external institutions

Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich DE Germany (DE) University of Zurich / Universität Zürich (UZH) CH Switzerland (CH) Technische Universität München (TUM) DE Germany (DE)

How to cite

APA:

Sadafi, A., Makhro, A., Bogdanova, A., Navab, N., Peng, T., Albarqouni, S., & Marr, C. (2020). Attention Based Multiple Instance Learning for Classification of Blood Cell Disorders. In Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 246-256). Lima, PER: Springer Science and Business Media Deutschland GmbH.

MLA:

Sadafi, Ario, et al. "Attention Based Multiple Instance Learning for Classification of Blood Cell Disorders." Proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, Lima, PER Ed. Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz, Springer Science and Business Media Deutschland GmbH, 2020. 246-256.

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