3 citations · 3 across the 2 of their papers we have counts for
5 papers
Reinforcement Learning of Musculoskeletal Control from Functional Simulations
Emanuel Joos, Fabien Péan, Orcun Goksel
To diagnose, plan, and treat musculoskeletal pathologies, understanding and reproducing muscle recruitment for complex movements is essential. With muscle activations for movements…
Mitosis Detection Under Limited Annotation: A Joint Learning Approach
Pushpak Pati, Antonio Foncubierta-Rodriguez, Orcun Goksel +1
Mitotic counting is a vital prognostic marker of tumor proliferation in breast cancer. Deep learning-based mitotic detection is on par with pathologists, but it requires large labe…
Extending Pretrained Segmentation Networks with Additional Anatomical Structures
Firat Ozdemir, Orcun Goksel
Comprehensive surgical planning require complex patient-specific anatomical models. For instance, functional muskuloskeletal simulations necessitate all relevant structures to be s…
Generative Adversarial Networks for MR-CT Deformable Image Registration
Christine Tanner, Firat Ozdemir, Romy Profanter +3
Deformable Image Registration (DIR) of MR and CT images is one of the most challenging registration task, due to the inherent structural differences of the modalities and the missi…
Learn the new, keep the old: Extending pretrained models with new anatomy and images
Firat Ozdemir, Philipp Fuernstahl, Orcun Goksel
Deep learning has been widely accepted as a promising solution for medical image segmentation, given a sufficiently large representative dataset of images with corresponding annota…