mlsanityData to 14 Oct 2026

Aorta Segmentation from 3D CT in MICCAI SEG.A. 2023 Challenge

arXiv 2310.04114 ↗First posted 6 Oct 2023eess.IV cs.CVcited by 5

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Abstract (arXiv)

Aorta provides the main blood supply of the body. Screening of aorta with imaging helps for early aortic disease detection and monitoring. In this work, we describe our solution to the Segmentation of the Aorta (SEG.A.231) from 3D CT challenge. We use automated segmentation method Auto3DSeg available in MONAI. Our solution achieves an average Dice score of 0.920 and 95th percentile of the Hausdorff Distance (HD95) of 6.013, which ranks first and wins the SEG.A. 2023 challenge.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 5 of its 8 references that are in the map. First posted on arXiv 6 Oct 2023.

Builds on

5 of 8 references.

References · 5

  1. 2022Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Imagescited by 830
  2. 2021Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysiscited by 422
  3. 20183D MRI brain tumor segmentation using autoencoder regularizationcited by 328
  4. 2021DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentationcited by 48
  5. 2021AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quocited by 12

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 1.

5 papers.

  1. 2024VISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imagingcited by 64
  2. 2025ENSAM: an efficient foundation model for interactive segmentation of 3D medical imagescited by 2
  3. 2025Towards the Automatic Segmentation, Modeling and Meshing of the Aortic Vessel Tree from Multicenter Acquisitions: An Overview of the SEG.A. 2023 Segmentation of the Aorta Challengecited by 2
  4. 2025AortaDiff: Volume-Guided Conditional Diffusion Models for Multi-Branch Aortic Surface Generationcited by 1
  5. 2026Sketch2CT: Multimodal Diffusion for Structure-Aware 3D Medical Volume Generationcited by 0