PhD Defense: Osman Berk Satir Brings Deep Learning into Shoulder Arthroplasty

On January 7, 2025, Osman Berk Satir successfully defended his PhD thesis titled: “Deep learning for automatic characterization of shoulder bone and muscle morphology and degeneration from CT images.” In this work, Osman presented a series of novel deep learning-based methods designed to enhance the automatic quantification of bone and muscle morphology in the shoulder, offering significant advancements for the success of total shoulder arthroplasty. In his dissertation, he demonstrated the feasibility and benefits of integrating deep learning-based techniques to accurately and efficiently measure anatomical parameters, assess muscle degeneration, reconstruct the premorbid anatomy, and quantify the trabecular structure. Congratulations to Dr. Osman Berk Satir on this incredible achievement and for contributing to the advancement of AI’s role within healthcare!