基于深度学习的肺部CT多病种智能诊断内含数据集和运行环境说明.zip

Directory Structure: +-- 01.preprocessing.ipynb +-- data | +-- mhd | +-- *.mhd | +-- npy | +-- *.npy +-- utils.py +-- label_mapping.py +-- chestCT_round1_annotation.csv # the npy can be obtained by the load_itk function in the former notebook called visualization Others: 2d/3d patch --> 2d/3d Neural Network --> loss The above is a complete training process, and this notebook clarifies the first step.