US Hetero–Homo conversion test

# 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