Publications by Elham Taghizadeh

Deep learning for the rapid automatic quantification and characterization of rotator cuff muscle degeneration from shoulder CT datasets

Alexandre Terrier, Alain Farron, Elham Taghizadeh, Philippe Büchler

Objectives This study aimed at developing a convolutional neural network (CNN) able to automatically quantify and characterize the level of degeneration of rotator cuff (RC) muscles from shoulder CT images including muscle atrophy and fatty infiltration. M ...

SPRINGER2020

Automated CT bone segmentation using statistical shape modelling and local template matching

Alexandre Terrier, Alain Farron, Elham Taghizadeh, Philippe Büchler

Accurate CT bone segmentation is essential to develop chair-side manufacturing of implants based on additive manufacturing. We herewith present an automated method able to accurately segment challenging bone regions, while simultaneously providing anatomic ...

2019

Patellar bone strain after total knee arthroplasty is correlated with bone mineral density and body mass index

Dominique Pioletti, Alexandre Terrier, Adeliya Latypova, Elham Taghizadeh, Philippe Büchler

Patella-related complications after total knee arthroplasty (TKA) remain a major clinical concern. Previous studies have suggested that increased postoperative patellar bone strain could be related to such complications, but there is limited knowledge on p ...

2019

Biomechanical Role of Bone Anisotropy Estimated on Clinical CT Scans by Image Registration

Alexandre Terrier, Adeliya Latypova, Elham Taghizadeh, Philippe Büchler

Image-based modeling is a popular approach to perform patient-specific biomechanical simulations. Accurate modeling is critical for orthopedic application to evaluate implant design and surgical planning. It has been shown that bone strength can be estimat ...

Springer Verlag2016

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