Car-Dcros: A Dataset and Benchmark for Enhancing Cardiovascular Artery Segmentation Through Disconnected Components Repair and Open Curve Snake

The segmentation of cardiovascular arteries in 3D medical images holds significant promise for assessing vascular health. Despite the progress in current methodologies, there remain significant challenges, especially in the precise segmentation of smaller vascular structures and those affected by arterial plaque, which often present as disconnected in images. Addressing these issues, we introduce an innovative refinement method that utilizes a data-driven strategy to correct the appearance of disconnected arterial structures. Initially, we create a synthetic dataset designed to mimic the appearance of disconnected cardiovascular structures. Our method then re-frames the segmentation issue as a task of detecting disconnected points, employing a neural network trained to identify points that can link the disconnected components. We further integrate an open curve active contour model, which facilitates the seamless connection of these points while ensuring smoothness. The effectiveness and clinical relevance of our methodology are validated through an application on an actual dataset from a medical institution.