Rib Segmentation

Rib segmentation, the automated identification and delineation of ribs in medical images (primarily CT and X-ray), aims to improve the speed and accuracy of diagnosis and treatment planning. Current research focuses on developing deep learning models, often employing hierarchical loss functions and geometric refinement techniques, to achieve highly accurate multi-label segmentation and instance segmentation of ribs, including fracture detection and classification. These advancements are crucial for applications such as automated rib fracture detection, improved image registration for comparing chest X-rays, and optimizing the design of internal cooling channels in engineering. The resulting improvements in efficiency and diagnostic accuracy have significant implications for radiology and related fields.