IntrA is an open-access 3D intracranial aneurysm dataset that makes the application of points-based and mesh-based classification and segmentation models available. This dataset can be used to diagnose intracranial aneurysms and to extract the neck for a clipping operation in medicine and other areas of deep learning, such as normal estimation and surface reconstruction.
103 3D models of entire brain vessels are collected by reconstructing scanned 2D MRA images of patients (the raw 2D MRA images are not published due to medical ethics).
1909 blood vessel segments are generated automatically from the complete models, including 1694 healthy vessel segments and 215 aneurysm segments for diagnosis.
116 aneurysm segments are divided and annotated manually by medical experts; the scale of each aneurysm segment is based on the need for a preoperative examination.
Geodesic distance matrices are computed and included for each annotated 3D segment, because the expression of the geodesic distance is more accurate than Euclidean distance according to the shape of vessels.
Source: https://github.com/intra3d2019/IntrA
Image Source: https://github.com/intra3d2019/IntrA
Variants: IntrA
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| 3D Point Cloud Classification | 3DMedPT | 3D Medical Point Transformer: Introducing … | 2021-12-09 |
| 3D Point Cloud Classification | AdaptConv | Adaptive Graph Convolution for Point … | 2021-08-18 |
| 3D Point Cloud Classification | PAConv | PAConv: Position Adaptive Convolution with … | 2021-03-26 |
| 3D Point Cloud Classification | PCT | PCT: Point cloud transformer | 2020-12-17 |
| 3D Point Cloud Classification | GS-Net | Geometry Sharing Network for 3D … | 2019-12-23 |
| 3D Point Cloud Classification | PointConv | PointConv: Deep Convolutional Networks on … | 2018-11-17 |
| 3D Point Cloud Classification | SpiderCNN | SpiderCNN: Deep Learning on Point … | 2018-03-30 |
| 3D Point Cloud Classification | SO-Net | SO-Net: Self-Organizing Network for Point … | 2018-03-12 |
| 3D Point Cloud Classification | DGCNN | Dynamic Graph CNN for Learning … | 2018-01-24 |
| 3D Point Cloud Classification | PointNet++ | PointNet++: Deep Hierarchical Feature Learning … | 2017-06-07 |
| 3D Point Cloud Classification | PointNet | PointNet: Deep Learning on Point … | 2016-12-02 |
Recent papers with results on this dataset: