US Hetero–Homo conversion test

<p># US Hetero&ndash;Homo conversion test</p> <p>&nbsp;</p> <p>## Paper information</p> <p>(under review)</p> <p>Deep Learning for Hetero&ndash;Homo Conversion in Channel-Domain for Phase Aberration Correction in Ultrasound Imaging</p> <p>Tatsuki Koike, Naoki Tomii, Yoshiki Watanabe, Takashi Azumaa, Shu Takagi</p> <p>&nbsp;</p> <p>## Required</p> <p>+ Matlab 2018b</p> <p>&nbsp; &nbsp; + Matlab Signal Processing Toolbox version 8.1</p> <p>&nbsp; &nbsp; + Matlab Image Processing Toolbox version &gt;= 9.3</p> <p>+ Docker version 20.10.14</p> <p>&nbsp;</p> <p>## How to test</p> <p>&nbsp;</p> <p>### RF Data Cropping</p> <p>[Shell]</p> <p>&gt; cd code/rfdata_cropping</p> <p>&gt; matlab ./RFDataCropping</p> <p>&nbsp;</p> <p>### RF Data Conversion Using Deep Neural Network</p> <p>[Shell]</p> <p>&gt; cd code/prediction</p> <p>&gt; ./build.sh</p> <p>&gt; ./run.sh</p> <p>&nbsp;</p> <p>### B-Mode Image Reconstruction</p> <p>[Shell]</p> <p>&gt; cd code/analysis</p> <p>&gt; matlab ./BModeReconstruction\(true\)</p> <p>\# boolean flag is true if image reconstruction is performed using rf data processed by DNN</p> <p>&nbsp;</p> <p>## Contents</p> <p>&nbsp;</p> <p>+ code</p> <p>&nbsp; &nbsp; + analysis : Matlab scripts for B-mode image reconstruction</p> <p>&nbsp; &nbsp; + item : Matlab matrices</p> <p>&nbsp; &nbsp; + prediction : python scripts for Hetero&ndash;Homo conversion test</p> <p>&nbsp; &nbsp; + rfdata_cropping : Matlab scripts for rf data cropping</p> <p>+ data</p> <p>&nbsp; &nbsp; + test</p> <p>&nbsp; &nbsp; &nbsp; &nbsp; + hetero : cropped rf data for Hetero&ndash;Homo conversion</p> <p>+ result</p> <p>&nbsp; &nbsp; + dnn_result : trained model</p> <p>&nbsp; &nbsp; + images : B-mode images of test data</p> <p>&nbsp; &nbsp; + sim_result : K-wave simlation results</p> <p>&nbsp;</p>