MedShapeNet — A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

arXiv:2308.16139v5 [cs.CV] 12 Dec 2023

In this paper, we present MedShapeNet, (1) a unique dataset for medical imaging shapes that serve complementary to existing shape benchmarks in computer vision, (2) a gap-bridger between the medical imaging and computer vision communities, and (3) a publicly available, continuous extending resource for benchmarking, education, extended reality (XR) applications, and the investigation of anatomical shape variations.

While existing datasets, such as ShapeNet are comprised of 3D computer-aided design (CAD) models of real-world objects (e.g., plane, car, chair, desk), MedShapeNet provides 3D shapes extracted from the imaging data of real patients including healthy as well as pathological subjects.

Full paper here: https://doi.org/10.48550/arXiv.2308.16139