DOI: 10.5281/zenodo.11180794
title: Trackerless 3D Freehand Ultrasound Reconstruction Challenge 2024 - Train Dataset (Part 2)

description: 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 second part of the Challenge dataset. Link to first part; Link to third part. Link to validation dataset.

Acquisition devices and config: The 2D US images were acquired using an Ultrasonix machine (BK, Europe) with a curvilinear probe (4DC7-3/40). The associated position information of each frame was recorded by an optical tracker (NDI Polaris Vicra, Northern Digital Inc., Canada). The acquired US frames were recorded at 20 fps, with an image size of 480×640, without speckle reduction. The frequency was set at 6MHz with a dynamic range of 83 dB, an overall gain of 48% and a depth of 9 cm. 



Scanning protocol: Both left and right forearms of volunteers were scanned. For each forearm, the US probe moves in three different trajectories (straight line shape, "C" shape, and "S" shape), in a distal-to-proximal direction followed by a proximal-to-distal direction, with the US plane perpendicular of and parallel to the scanning direction. The train dataset contains 1200 scans in total, 24 scans associated with each subject.





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 folders (one subject per folder), each with 24 scans. Each .h5 file corresponds to one scan, storing image and transformation of each frame within this scan. Key-value pairs in each .h5 file are explained below.





“frames”  - All frames in the scan; with a shape of [N,H,W], where N refers to the number of frames in the scan, H and W denote the height and width of a frame. 




“tforms” - All transformations in the scan; with a shape of [N,4,4], where N is the number of frames in the scan, and the transformation matrix denotes the transformation from tracker tool space to camera space. 




Notations in the name of each .h5 file: “RH”: right arm; “LH”: left arm; “Per”: perpendicular; “Par”: parallel; “L”: straight line shape; “C”: C shape; “S”: S shape; “DtP”: distal-to-proximal direction; “PtD”: proximal-to-distal direction; For example, “RH_Per_L_DtP.h5” denotes a scan on the right forearm, with ultrasound probe perpendicular of the forearm sweeping along straight line, in distal-to-proximal direction.






Calibration matrix: The calibration matrix was obtained using a pinhead-based method. The "scaling_from_pixel_to_mm" and "spatial_calibration_from_image_coordinate_system_to_tracking_tool_coordinate_system" are provided in the “calib_matrix.csv”. 





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.