Výsledky vyhledávání - "Kakavand, Reza"

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OpenCap markerless motion capture estimation of lower extremity kinematics and dynamics in cycling

Autor: Kakavand, Reza, Ahmadi, Reza, Parsaei, Atousa, Edwards, W. Brent, Komeili, Amin

Markerless motion capture offers several benefits over traditional marker-based systems by eliminating the need for physical markers, which are prone to misplacement and artifacts. Utilizing computer vision and deep learning algorithms, markerless sy

Externí odkaz: http://arxiv.org/abs/2409.03766

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Swin UNETR segmentation with automated geometry filtering for biomechanical modeling of knee joint cartilage

Autor: Kakavand, Reza, Tahghighi, Peyman, Ahmadi, Reza, Edwards, W. Brent, Komeili, Amin

Simulation studies, such as finite element (FE) modeling, offer insights into knee joint biomechanics, which may not be achieved through experimental methods without direct involvement of patients. While generic FE models have been used to predict ti

Externí odkaz: http://arxiv.org/abs/2407.06403

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Integration of Swin UNETR and statistical shape modeling for a semi-automated segmentation of the knee and biomechanical modeling of articular cartilage

Autor: Kakavand, Reza, Palizi, Mehrdad, Tahghighi, Peyman, Ahmadi, Reza, Gianchandani, Neha, Adeeb, Samer, Souza, Roberto, Edwards, W. Brent, Komeili, Amin

Simulation studies like finite element (FE) modeling provide insight into knee joint mechanics without patient experimentation. Generic FE models represent biomechanical behavior of the tissue by overlooking variations in geometry, loading, and mater

Externí odkaz: http://arxiv.org/abs/2312.00169

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