Dataset underlying the study: Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging

This dataset contains the data used for the study ‘Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging’ (link will be added after publication). <strong>Contents:</strong> It consists of radiofrequency (RF) signals acquired during simulations and experiments, weights and biases of networks trained, and images reconstructed using delay-and-sum (DAS) beamforming. In addition to that, it also contains environments and packages used to process the data. <strong>Objective:</strong> To investigate the effect of transmit waveforms on the performance of deep learning-based approaches for localizing microbubbles in radiofrequency signals. <strong>Type of research:</strong> Fundamental, Physics, Biomedical. <strong>Method of data collection:</strong> In-silico and in-vitro. <strong>Type of data:</strong> RF signals (<code style="color:rgb(199, 37, 78);background-color:rgb(249, 242, 244);">.mat</code> and <code style="color:rgb(199, 37, 78);background-color:rgb(249, 242, 244);">.txt</code>), super-resolved RF signals (<code style="color:rgb(199, 37, 78);background-color:rgb(249, 242, 244);">.txt</code> and <code style="color:rgb(199, 37, 78);background-color:rgb(249, 242, 244);">.npy</code>), weights and biases (<code style="color:rgb(199, 37, 78);background-color:rgb(249, 242, 244);">.txt</code>), images generated with the (super-resolved) RF signals (<code style="color:rgb(199, 37, 78);background-color:rgb(249, 242, 244);">.mat</code>), videos generated with the (super-resolved) RF signals (<code style="color:rgb(199, 37, 78);background-color:rgb(249, 242, 244);">.mp4</code>), python environments (<code style="color:rgb(199, 37, 78);background-color:rgb(249, 242, 244);">.yaml</code>), microbubble size distributions (<code style="color:rgb(199, 37, 78);background-color:rgb(249, 242, 244);">.fig</code> and <code style="color:rgb(199, 37, 78);background-color:rgb(249, 242, 244);">.png</code>). The code used for this work is available at https://github.com/MIAGroupUT/super-resolution-waveforms.