mlsanityData to 7 Oct 2026

IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning

arXiv 2003.02920 ↗First posted 2 Mar 2020eess.IV cs.CV cs.LGcited by 41

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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.

Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Mar 2020.

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Citing papers per year: 2021: 3; 2022: 3; 2023: 9; 2024: 7; 2025: 12; 2026: 7.

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  1. 2021MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classificationcited by 682
  2. 2022Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectivescited by 32
  3. 20213D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysiscited by 23
  4. 2021RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scanscited by 21
  5. 2023VesselVAE: Recursive Variational Autoencoders for 3D Blood Vessel Synthesiscited by 13
  6. 2025Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Modelscited by 13
  7. 2024Toward Availability Attacks in 3D Point Cloudscited by 7
  8. 2022Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysiscited by 5
  9. 2023Building Universal Foundation Models for Medical Image Analysis with Spatially Adaptive Networkscited by 4
  10. 2024TrIND: Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fieldscited by 4
  11. 2025Manifold Topological Deep Learning for Biomedical Datacited by 4
  12. 2025SeaLion: Semantic Part-Aware Latent Point Diffusion Models for 3D Generationcited by 4
29 more
  1. 2025Vector Representations of Vessel Treescited by 3
  2. 2024AI-Enhanced Virtual Reality in Medicine: A Comprehensive Surveycited by 2
  3. 2025AneumoBench: A Source-Linked Benchmark for Synthetic-Geometry Transfer in Aneurysm CFDcited by 2
  4. 2025A Survey of Medical Point Cloud Shape Learning: Registration, Reconstruction and Variationcited by 2
  5. 2025TACO-Net: Topological Signatures Triumph in 3D Object Classificationcited by 2
  6. 20223D Intracranial Aneurysm Classification and Segmentation via Unsupervised Dual-branch Learningcited by 1
  7. 2023From CAD models to soft point cloud labels: An automatic annotation pipeline for cheaply supervised 3D semantic segmentationcited by 1
  8. 2023Local region-learning modules for point cloud classificationcited by 1
  9. 2023Structured Low-Rank Tensors for Generalized Linear Modelscited by 1
  10. 20233D Understanding of Deformable Linear Objects: Datasets and Transferability Benchmarkcited by 1
  11. 2025Generative Data Augmentation for Object Point Cloud Segmentationcited by 1
  12. 2025Multi-view Normal and Distance Guidance Gaussian Splatting for Surface Reconstructioncited by 1
  13. 2025TRELLIS-Enhanced Surface Features for Comprehensive Intracranial Aneurysm Analysiscited by 1
  14. 2025Graph Deep Learning for Intracranial Aneurysm Blood Flow Simulation and Risk Assessmentcited by 1
  15. 2026Point-SRA: Self-Representation Alignment for 3D Representation Learningcited by 1
  16. 2026A Survey on Deep Learning Architectures for Point Cloud Classification and Segmentationcited by 1
  17. 2023A Task-driven Network for Mesh Classification and Semantic Part Segmentationcited by 0
  18. 2023Benefits of mirror weight symmetry for 3D mesh segmentation in biomedical applicationscited by 0
  19. 2023Sample selection with noise rate estimation in noise learning of medical image analysiscited by 0
  20. 2024DataCook: Crafting Anti-Adversarial Examples for Healthcare Data Copyright Protectioncited by 0
  21. 2024Frenet-Serret Frame-based Decomposition for Part Segmentation of 3D Curvilinear Structurescited by 0
  22. 2024From Tissue Plane to Organ World: A Benchmark Dataset for Multimodal Biomedical Image Registration using Deep Co-Attention Networkscited by 0
  23. 2024Cross-D Conv: Cross-Dimensional Transferable Knowledge Base via Fourier Shifting Operationcited by 0
  24. 2025Recursive Variational Autoencoders for 3D Blood Vessel Generative Modelingcited by 0
  25. 2026PlaneCycle: Training-Free 2D-to-3D Lifting of Foundation Models Without Adapterscited by 0
  26. 2026A Muon-Accelerated Algorithm for Low Separation Rank Tensor Generalized Linear Modelscited by 0
  27. 2026Augmented Equivariant Mesh Networks for Anatomical Segmentationcited by 0
  28. 2026SynVA: A Modular Toolkit for Vessel Generation and Aneurysm Editingcited by 0
  29. 2026Heat Field Signatures: From Point Clouds to Smooth Geometrycited by 0