Ultrasound imaging dataset for elastography, deformation correction, and algorithm evaluation

Ultrasound imaging is widely used for its cost-effectiveness, non-invasiveness, and real-time capabilities in diagnostics and image-guided procedures. However, the direct skin contact involved in ultrasound image acquisition induces deformations in the tissues. In certain scenarios, such as elastography or freehand 3D ultrasound imaging, the relative deformations between successive ultrasound images must therefore be estimated or corrected. This is a non-rigid image registration operation. In addition to image data, validation requires knowledge of several parameters related to image deformation, such as probe contact force, indentation or mechanical parameters of the imaged body. Existing methods are often validated on simulated data or non-public datasets accessible within the research group, and the reported performances are challenging to reproduce by other research groups. Quality public datasets would enable research groups to compare their research results and drive performance improvements through competition. To address this gap, we introduce a publicly available dataset with controlled deformations on a phantom, including B-mode images, RF signals, probe indentations, contact force, and phantom material mechanical parameters. This dataset serves as a valuable resource for validating various registration and elastography methods, offering a standardized platform for performance evaluation and comparison among research groups. The article outlines the experimental protocol, the mechanical system for probe maintenance and indentation, force measurement, and the phantom creation process.