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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
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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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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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KEYWORDS
Bone
Magnetism
Neural networks
Pathology
Shape analysis
Statistical modeling
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