DOI: 10.5281/zenodo.12752246
title: Trackerless 3D Freehand Ultrasound Reconstruction Challenge - Validation Dataset

description: This is the validation dataset. The training dataset is available at Part1, Part2, and Part3.

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 validation dataset contains 72 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: 



Folder frames: contains three folders (one subject per folder), each with 24 scans. Each .h5 file corresponds to one scan, storing image of each frame within this scan. Key-value pair and name of 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. 

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.









Folder transfs: contains three folders (one subject per folder), each with 24 scans. Each .h5 file corresponds to one scan, storing transformation of each frame within this scan. Key-value pair and name of each .h5 file are explained below. 



“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 is the same as in folder frames.



Folder landmark: contains three .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 a shape of [20,3]. The first column is the index of frame; the second and third columns denote the coordinates of landmarks in the image coordinate system.

calib_matrix.csv: 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”.

dataset_keys.h5: stores the paths to all the scans of the data set. Keys in “dataset_keys.h5” denotes all the available scans in validation set, in a format of “sub%03d__%s” where %03d denotes folder name, and %s denotes the scan name. For example, “sub050__LH_Par_C_DtP” means the scan in folder “050”, with file name of “LH_Par_C_DtP.h5”




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.

After we publish the summary paper of the challenge, if you use our dataset in your publication, please cite the summary paper (reference will be provided once published) and the following article:  



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.