Pancreas Segmentation

Pancreas segmentation, the automated identification and delineation of the pancreas in medical images (CT and MRI), is crucial for diagnosis and treatment planning of pancreatic diseases. Current research focuses on improving segmentation accuracy using deep learning architectures like U-Net and its variants, often incorporating multi-scale/resolution processing, multimodal fusion (combining CT and MRI data), and shape-based constraints to address challenges posed by the pancreas's small size, variable shape, and low contrast. These advancements aim to improve the speed and accuracy of diagnosis, ultimately leading to better patient outcomes and facilitating more efficient clinical workflows.