Automatic classification of proximal femur fractures based on attention models

Anees Kazi, Shadi Albarqouni, Amelia Jimenez Sanchez, Sonja Kirchhoff, Peter Biberthaler, Nassir Navab, Diana Mateus

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

We target the automatic classification of fractures from clinical X-Ray images following the Arbeitsgemeinschaft Osteosynthese (AO) classification standard. We decompose the problem into the localization of the region-of-interest (ROI) and the classification of the localized region. Our solution relies on current advances in multi-task end-to-end deep learning. More specifically, we adapt an attention model known as Spatial Transformer (ST) to learn an image-dependent localization of the ROI trained only from image classification labels. As a case study, we focus here on the classification of proximal femur fractures. We provide a detailed quantitative and qualitative validation on a dataset of 1000 images and report high accuracy with regard to inter-expert correlation values reported in the literature.

Original languageEnglish
Title of host publicationMachine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Proceedings
EditorsYinghuan Shi, Heung-Il Suk, Kenji Suzuki, Qian Wang
PublisherSpringer Verlag
Pages70-78
Number of pages9
ISBN (Print)9783319673882
DOIs
StatePublished - 2017
Event8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017 held in conjunction with the 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: 10 Sep 201710 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10541 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017 held in conjunction with the 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
Country/TerritoryCanada
CityQuebec City
Period10/09/1710/09/17

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