# IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning

arXiv: https://arxiv.org/abs/2003.02920 · HTML: https://mlsanity.com/paper/2003.02920/

## Key facts

- Cited by 41 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Mar 2020.

## Built on by (most cited first, 30 of 41)

- [MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification](https://mlsanity.com/paper/2110.14795/) (2021)
- [Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives](https://mlsanity.com/paper/2206.01136/) (2022)
- [3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis](https://mlsanity.com/paper/2112.04863/) (2021)
- [RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans](https://mlsanity.com/paper/2109.09521/) (2021)
- [VesselVAE: Recursive Variational Autoencoders for 3D Blood Vessel Synthesis](https://mlsanity.com/paper/2307.03592/) (2023)
- [Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models](https://mlsanity.com/paper/2507.08254/) (2025)
- [Toward Availability Attacks in 3D Point Clouds](https://mlsanity.com/paper/2407.11011/) (2024)
- [Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis](https://mlsanity.com/paper/2206.15328/) (2022)
- [Building Universal Foundation Models for Medical Image Analysis with Spatially Adaptive Networks](https://mlsanity.com/paper/2312.07630/) (2023)
- [TrIND: Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields](https://mlsanity.com/paper/2403.08974/) (2024)
- [Manifold Topological Deep Learning for Biomedical Data](https://mlsanity.com/paper/2503.00175/) (2025)
- [SeaLion: Semantic Part-Aware Latent Point Diffusion Models for 3D Generation](https://mlsanity.com/paper/2505.17721/) (2025)
- [Vector Representations of Vessel Trees](https://mlsanity.com/paper/2506.11163/) (2025)
- [AI-Enhanced Virtual Reality in Medicine: A Comprehensive Survey](https://mlsanity.com/paper/2402.03093/) (2024)
- [AneumoBench: A Source-Linked Benchmark for Synthetic-Geometry Transfer in Aneurysm CFD](https://mlsanity.com/paper/2505.14717/) (2025)
- [A Survey of Medical Point Cloud Shape Learning: Registration, Reconstruction and Variation](https://mlsanity.com/paper/2508.03057/) (2025)
- [TACO-Net: Topological Signatures Triumph in 3D Object Classification](https://mlsanity.com/paper/2509.24802/) (2025)
- [Graph Deep Learning for Intracranial Aneurysm Blood Flow Simulation and Risk Assessment](https://mlsanity.com/paper/2512.09013/) (2025)
- [3D Intracranial Aneurysm Classification and Segmentation via Unsupervised Dual-branch Learning](https://mlsanity.com/paper/2201.02198/) (2022)
- [From CAD models to soft point cloud labels: An automatic annotation pipeline for cheaply supervised 3D semantic segmentation](https://mlsanity.com/paper/2302.03114/) (2023)
- [Local region-learning modules for point cloud classification](https://mlsanity.com/paper/2303.17338/) (2023)
- [Structured Low-Rank Tensors for Generalized Linear Models](https://mlsanity.com/paper/2308.02922/) (2023)
- [3D Understanding of Deformable Linear Objects: Datasets and Transferability Benchmark](https://mlsanity.com/paper/2310.08904/) (2023)
- [Generative Data Augmentation for Object Point Cloud Segmentation](https://mlsanity.com/paper/2505.17783/) (2025)
- [Multi-view Normal and Distance Guidance Gaussian Splatting for Surface Reconstruction](https://mlsanity.com/paper/2508.07701/) (2025)
- [TRELLIS-Enhanced Surface Features for Comprehensive Intracranial Aneurysm Analysis](https://mlsanity.com/paper/2509.03095/) (2025)
- [Point-SRA: Self-Representation Alignment for 3D Representation Learning](https://mlsanity.com/paper/2601.01746/) (2026)
- [A Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation](https://mlsanity.com/paper/2605.17131/) (2026)
- [A Task-driven Network for Mesh Classification and Semantic Part Segmentation](https://mlsanity.com/paper/2306.05246/) (2023)
- [Benefits of mirror weight symmetry for 3D mesh segmentation in biomedical applications](https://mlsanity.com/paper/2309.17076/) (2023)

## Abstract (arXiv)

Medicine is an important application area for deep learning models. Research in this field is a combination of medical expertise and data science knowledge. In this paper, instead of 2D medical images, we introduce an open-access 3D intracranial aneurysm dataset, IntrA, that makes the application of points-based and mesh-based classification and segmentation models available. Our 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. We provide a large-scale benchmark of classification and part segmentation by testing state-of-the-art networks. We also discuss the performance of each method and demonstrate the challenges of our dataset. The published dataset can be accessed here: https://github.com/intra3d2019/IntrA.