基于卷积神经网络进行断层扫描结肠炎检测.zip

Developed by Jiamin Liu (liujiamin@cc.nih.gov) https://github.com/rsummers11/CADLab Please cite our papers if you end up using this code: Liu, J., Wang, D., Wei, Z., Lu, L., Kim, L., Turkbey, E., & Summers, R. M. (2016, April). Colitis detection on computed tomography using regional convolutional neural networks. In�Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on�(pp. 863-866). IEEE. Liu, J., Wang, D., Lu, L., Wei, Z., Kim, L., Turkbey, E., Sahiner, B., Petrick, N. & Summers, R. M. (2017, May), Detection and diagnosis of colitis on computed tomography using deep convolutional neural networks, Medical Physics, Accepted. Code includes modifications of open-source packages: 1. https://github.com/ShaoqingRen/faster_rcnn 2. Various submission of the Matlab file exchange (https://www.mathworks.com/matlabcentral/fileexchange/29344-read-medical-data-3d?focused=5186757&tab=function) Requirements: 1. Matlab 2. CUDA-compatible graphics card 3. CUDA toolkit Execution: 1. Download and install Faster RCNN following the instructions: https://github.com/ShaoqingRen/faster_rcnn 2. Run dicom_to_jpgs.m to convert dicoms to jpgs or download example jpgs. 3. Down load trained colitis detection models. 4. Run script_faster_rcnn_run_colitis_detection.m.