Datasets › IntrA

IntrA

Introduced by Xi Yang et al. in IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning archive 2025-07-28

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

Benchmarks archive 2025-07-28

All 2 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

Papers archive 2025-07-28

13 shown of 13 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 27. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis 1 2 9 Dec 2021 not harvested
Adaptive Graph Convolution for Point Cloud Analysis 1 1 18 Aug 2021 ran 1 of 2 samples (1 unverified; 2 pointer-only for licence)
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds 2 1 26 Mar 2021 ran 4 of 5 samples (1 unverified)
PCT: Point cloud transformer 11 1 17 Dec 2020 ran 2 of 2 samples (0 unverified)
Geometry Sharing Network for 3D Point Cloud Classification and Segmentation 1 1 23 Dec 2019 not harvested
PointCNN: Convolution On X-Transformed Points 1 1 1 Dec 2018 not harvested
PointConv: Deep Convolutional Networks on 3D Point Clouds 9 2 17 Nov 2018 ran 11 of 15 samples (4 unverified; 1 pointer-only for licence)
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters 1 2 30 Mar 2018 ran 2 of 8 samples (6 unverified)
SO-Net: Self-Organizing Network for Point Cloud Analysis 3 2 12 Mar 2018 ran 0 of 7 samples (7 unverified)
Dynamic Graph CNN for Learning on Point Clouds 21 1 24 Jan 2018 ran 16 of 44 samples (28 unverified; 31 pointer-only for licence)
PointCNN: Convolution On 𝒳-Transformed Points 16 1 23 Jan 2018 not harvested
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space 68 2 7 Jun 2017 ran 36 of 67 samples (31 unverified; 26 pointer-only for licence)
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation 110 2 2 Dec 2016 ran 89 of 164 samples (75 unverified; 90 pointer-only for licence)

Dataset loaders archive 2025-07-28

1 loader as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • IntrA

1 variant name, as the archive lists them.

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