Segmentation is highly important both for examination and planning of knee replacement, hip replacement, shoulder surgery, lesion detection, osteotomy and many other orthopedic procedures. RSIP Vision's CTO Ilya Kovler explains how to improve the segmentation in orthopedics with deep learning. Deep learning is repeatedly being proven to be the most powerful framework for various tasks, and segmentation in orthopedics is no exception. Generic out-of-the-box solutions exist and can produce fair results, but carefully crafted and tailored solutions are needed to make the most out of a deep learning approach. Choosing the correct input, selecting the most suitable neural network architecture and incorporating task-specific prior knowledge into the model can all significantly improve the results.

Two time winner of the MORE award Ms. Hofheinz was the first writer employed by Orthopedics This Week. The MORE award is granted annually by the American Academy of Orthopaedic Surgeons to recognize excellence in journalism. Ms. Hofheinz is currently the Director of Communications for Ortho Spine Partners (OSP) and resides in New Orleans, Louisiana with her entrepreneur husband and delightful daughter.