Registration of multi-view echocardiography sequences using a subspace similarity measure
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Data employed for the validation of the PCA-based similarity metric proposed in "Registration of multi-view echocardiography sequences using a subspace similarity measure." Peressutti et al. (under review).
Data consists of echocardiography sequences of the Left ventricle of four volunteers (vol_A-vol_D) from different acoustic windows (aw_1-aw_5). The image format is metadata.
For each subject, the ground-truth rigid transformations that aligns each sequence to all the others is provided. Such transformations are provided by optically tracking the position of the ultrasound imaging probe.
For more detailed information regarding the datasets, please refer to the paper.
Python code for testing the proposed method can be downloaded from (https://github.com/devisperessutti/Python.git), while MATLAB code can be downloaded from (https://github.com/gomezalberto/Matlab.git).