Author(s): Kafian Safari M; Mirzae M; Gheflati B; Sharifzade M; Zuhars J; Rottoo S; Rivaz H;

Purpose: Computer- and robotic-assisted technologies improve total knee arthroplasty (TKA) through intraoperative bone registration. However, limited bone exposure restricts point collection to the distal femur, omitting key geometric features and reducing registration accuracy and the surgical outcomes. Methods: We introduce a deep learning-based method ...

Article GUID: 41984365

Author(s): Gheflati B; Mirzaei M; Zuhars J; Rottoo S; Rivaz H;

Purpose: Computer-assisted surgical navigation systems have been developed to improve the precision of total knee arthroplasty (TKA) by providing real-time guidance on implant alignment relative to patient anatomy. However, surface registration remains a key source of error that can propagate through the surgical workflow. This study investigates how pati ...

Article GUID: 41495592

Author(s): Gheflati B; Mirzaei M; Rottoo S; Rivaz H;

Purpose: Statistical shape models (SSMs) are widely used for morphological assessment of anatomical structures. However, a key limitation is the need for a clear relationship between the model's shape coefficients and clinically relevant anatomical parameters. To address this limitation, this paper proposes a novel deep learning-based anatomically par ...

Article GUID: 39953355