mlsanityData to 7 Oct 2026

TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker

arXiv 2506.21765 ↗First posted 26 Jun 2025eess.IV cs.CVcited by 4

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Abstract (arXiv)

Trackerless freehand ultrasound reconstruction aims to reconstruct 3D volumes from sequences of 2D ultrasound images without relying on external tracking systems. By eliminating the need for optical or electromagnetic trackers, this approach offers a low-cost, portable, and widely deployable alternative to more expensive volumetric ultrasound imaging systems, particularly valuable in resource-constrained clinical settings. However, predicting long-distance transformations and handling complex probe trajectories remain challenging. The TUS-REC2024 Challenge establishes the first benchmark for trackerless 3D freehand ultrasound reconstruction by providing a large publicly available dataset, along with a baseline model and a rigorous evaluation framework. By the submission deadline, the Challenge had attracted 43 registered teams, of which 6 teams submitted 21 valid dockerized solutions. The submitted methods span a wide range of approaches, including the state space model, the recurrent model, the registration-driven volume refinement, the attention mechanism, and the physics-informed model. This paper provides a comprehensive background introduction and literature review in the field, presents an overview of the challenge design and dataset, and offers a comparative analysis of submitted methods across multiple evaluation metrics. These analyses highlight both the progress and the current limitations of state-of-the-art approaches in this domain and provide insights for future research directions. All data and code are publicly available to facilitate ongoing development and reproducibility. As a live and evolving benchmark, it is designed to be continuously iterated and improved. The Challenge was held at MICCAI 2024 and is organised again at MICCAI 2025, reflecting its sustained commitment to advancing this field.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 20 of its 53 references that are in the map. First posted on arXiv 26 Jun 2025.

Builds on

20 of 53 references.

References · 20

  1. 2018On the Continuity of Rotation Representations in Neural Networkscited by 1,186
  2. 2023BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairscited by 506
  3. 2019Making Convolutional Networks Shift-Invariant Againcited by 390
  4. 2023PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documentscited by 212
  5. 2018Why rankings of biomedical image analysis competitions should be interpreted with carecited by 90
  6. 2019BIAS: Transparent reporting of biomedical image analysis challengescited by 57
  7. 2021Global-Local Attention for Emotion Recognitioncited by 20
  8. 2017Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networkscited by 15
  9. 2021Self Context and Shape Prior for Sensorless Freehand 3D Ultrasound Reconstructioncited by 14
  10. 2022Deep Motion Network for Freehand 3D Ultrasound Reconstructioncited by 14
  11. 2020Sensorless Freehand 3D Ultrasound Reconstruction via Deep Contextual Learningcited by 12
  12. 2016Bayesian Optimization for Machine Learning : A Practical Guidebookcited by 10
8 more
  1. 2025UltraGauss: Ultrafast Gaussian Reconstruction of 3D Ultrasound Volumescited by 8
  2. 2022Trackerless freehand ultrasound with sequence modelling and auxiliary transformation over past and future framescited by 7
  3. 2023Long-term Dependency for 3D Reconstruction of Freehand Ultrasound Without External Trackercited by 7
  4. 2024RapidVol: Rapid Reconstruction of 3D Ultrasound Volumes from Sensorless 2D Scanscited by 7
  5. 2024Fine-grained Context and Multi-modal Alignment for Freehand 3D Ultrasound Reconstructioncited by 5
  6. 2024Nonrigid Reconstruction of Freehand Ultrasound without a Trackercited by 3
  7. 2025MoNetV2: Enhanced Motion Network for Freehand 3D Ultrasound Reconstructioncited by 3
  8. 2020Transducer Adaptive Ultrasound Volume Reconstructioncited by 1

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Cited by year (2026 to 7 Oct)

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

4 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026UBone3D: Physics-Rectified Conditional Flow Matching for Anatomical 3D Shape Completion from Ultrasound
  2. 2023Multi-IMU with Online Self-Consistency for Freehand 3D Ultrasound Reconstruction
  3. 2026UltraWorld: Learning Interactive Ultrasound World Models from Untracked Clinical Videos with Acoustic Sampling Map
  4. 2024NeRF-US: Removing Ultrasound Imaging Artifacts from Neural Radiance Fields in the Wild
  5. 2025High Volume Rate 3D Ultrasound Reconstruction with Diffusion Models
  6. 2026Scanning While Imagining: A Scene-Graph World Model for Robotic Ultrasound Navigation
  7. 2026DreamReg: Belief-Driven World Model for 2D-3D Ultrasound Registration
  8. 2025MR2US-Pro: Prostate MR to Ultrasound Image Translation and Registration Based on Diffusion Models