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