Powered by OpenAIRE graph
Found an issue? Give us feedback
ZENODOarrow_drop_down
ZENODO
Dataset . 2024
License: CC BY NC SA
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY NC SA
Data sources: Datacite
versions View all 2 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Trackerless 3D Freehand Ultrasound Reconstruction Challenge 2024 - Train Dataset (Part 3)

Authors: Li, Qi; Saeed, Shaheer U.; Huang, Yuliang; Barratt, Dean C.; Clarkson, Matthew J.; Vercauteren, Tom; Hu, Yipeng;

Trackerless 3D Freehand Ultrasound Reconstruction Challenge 2024 - Train Dataset (Part 3)

Abstract

This Challenge will be an open-ended challenge, and we welcome your submission. Please register your team via this ⁠form. You can submit the algorithm via this form for TUS-REC2024 Challenge, and we will test your submitted docker on the test set. We are organising TUS-REC2025 at MICCAI2025. More information is available on the TUS-REC2025 challenge website and Baseline code repo. This is the third part of the Challenge dataset. Link to first part; Link to second part. Link to validation dataset. For detailed information please refer to the Challenge website. Baseline code is also provided, which can be found at this repo. Dataset structure: The dataset contains 50 .h5 files. Each corresponds to one subject, storing coordinates of landmarks for 24 scans of this subject. For each scan, the coordinates are stored in numpy array with shape of [20,3]. The first column is the index of frames; the second and third columns denote the coordinates of landmarks in the image coordinate system. Data Usage Policy: The training and validation data provided may be utilized within the research scope of this challenge and in subsequent research-related publications. However, commercial use of the training and validation data is prohibited. In cases where the intended use is ambiguous, participants accessing the data are requested to abstain from further distribution or use outside the scope of this challenge. Please cite our challenge paper if you use our dataset in your publication: Challenge paper: Qi Li et al. "TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker." arXiv preprint arXiv:2506.21765 (2025). Additional relevant publications may also be cited as appropriate (optional): Optional articles: Qi Li, Ziyi Shen, Qianye Yang, Dean C. Barratt, Matthew J. Clarkson, Tom Vercauteren, and Yipeng Hu. "Nonrigid Reconstruction of Freehand Ultrasound without a Tracker." In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 689-699. Cham: Springer Nature Switzerland, 2024. doi: 10.1007/978-3-031-72083-3_64. Qi Li, Ziyi Shen, Qian Li, Dean C. Barratt, Thomas Dowrick, Matthew J. Clarkson, Tom Vercauteren, and Yipeng Hu. "Long-term Dependency for 3D Reconstruction of Freehand Ultrasound Without External Tracker." IEEE Transactions on Biomedical Engineering, vol. 71, no. 3, pp. 1033-1042, 2024. doi: 10.1109/TBME.2023.3325551. Qi Li, Ziyi Shen, Qian Li, Dean C. Barratt, Thomas Dowrick, Matthew J. Clarkson, Tom Vercauteren, and Yipeng Hu. "Trackerless freehand ultrasound with sequence modelling and auxiliary transformation over past and future frames." In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), pp. 1-5. IEEE, 2023. doi: 10.1109/ISBI53787.2023.10230773. Qi Li, Ziyi Shen, Qian Li, Dean C. Barratt, Thomas Dowrick, Matthew J. Clarkson, Tom Vercauteren, and Yipeng Hu. "Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction." In International Workshop on Advances in Simplifying Medical Ultrasound, pp. 142-151. Cham: Springer Nature Switzerland, 2023. doi: https://doi.org/10.1007/978-3-031-44521-7_14.

Related Organizations
Keywords

MICCAI 2024 challenges, ultrasound, Freehand, 3D Reconstruction, Trackerless, Spatial transformation estimation

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average