Multi-agent shape models for hip landmark detection in MR scans

Imad Eddine Ibrahim Bekkouch; Tamerlan Aidinovich; Tomaz Vrtovec; Ramil Kuleev; Bulat Ibragimov

doi:10.1117/12.2580862

15 February 2021 Multi-agent shape models for hip landmark detection in MR scans

Imad Eddine Ibrahim Bekkouch, Tamerlan Aidinovich, Tomaz Vrtovec, Ramil Kuleev, Bulat Ibragimov

Author Affiliations +

Proceedings Volume 11596, Medical Imaging 2021: Image Processing; 115960O (2021) https://doi.org/10.1117/12.2580862
Event: SPIE Medical Imaging, 2021, Online Only

Abstract

Landmark detection is an essential step in the diagnosis of bone pathologies and pelvis morphometry. Hence, we propose a Deep Learning based method for automatic landmark detection on multi-modality hips magnetic resonance (MR) scans. Our method is based on a synergistic analysis of appearance and shape information by using deep networks for the detection of landmark candidate locations and then adjusting these locations using inter-landmark spatial properties. Our best model gives an average of 1.74 mm over all the landmarks, where 67% of the proposed landmarks are within the spatial matching error of at most 2mm.

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Citation Download Citation

Imad Eddine Ibrahim Bekkouch, Tamerlan Aidinovich, Tomaz Vrtovec, Ramil Kuleev, and Bulat Ibragimov "Multi-agent shape models for hip landmark detection in MR scans", Proc. SPIE 11596, Medical Imaging 2021: Image Processing, 115960O (15 February 2021); https://doi.org/10.1117/12.2580862

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