Introduction to our open-sourced PLDC system

This open-sourced deep-learning-based model acts as an end-to-end system, input from prostate mpMRI sequences (i.e. T2, ADC, and hDWI), output to prediction results (i.e. prostate segmentation, coarse lesion detection, and malignancy estimation). The system supports multi-format inputs, including DICOM, jpeg, png, and jpg files. It is emphasized that no manual prostate segmentation or annotation is required.
 1. To realize automatic PLDC with multi-cohort mpMRIs (i.e., T2, ADC, and hDWI), please download the executable software first from the Github repository. In addition, you should also download the PLDC_software.zip  from the Github repository. Unzip the zip file, and put the downloaded executable software in the folder "./PLDC_software/ ".
2. Install required packages for mpMRI-based PLDC testing. 
3. In order to perform PLDC using your local cohort samples, you should train a  domain adaptation (DA)  model first (see details in the next Section " Prostate lesion assessment using your local cohort mpMRI "). Put all of your well-trained model weights in the folder "./PLDC_software/doc/weights/ ".
4. Begin to test the target mpMRIs from your local cohort using the open-sourced system. Open the executable software. Start your testing via the "Main menu" button, and then click "Start testing". The predicted results will be saved in the folder "./media/output/ ", including prostate segmentation, prostate lesion detection, and lesion malignancy results.  You can download the following prostate_exe.mp4 to learn the details if necessary.