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medicalimageprocess's Introduction

数据很杂,就懒得逐一整理了,很多都是实验性的,可能存在问题,不过好久没弄也忘得差不多,有问题的话还请大家自行阅读代码解决吧,下面只把每个文件是做什么用的大体说一下:

  • phi
    • my_show_grid.py:先产生规则的网格图片,然后使用STN根据读入的形变场对其变形
    • show_grid.py:读入形变场的.nii文件,然后生成可视化的形变场图片
  • show_nii
    • show_nii.py:展示三维的.nii图像
    • show_nii3.py:同时展示三维的.nii格式的器官、器官分割mask、病灶分割mask图像
  • ants.py:使用ANTs包内的SyN对图像进行配准
  • antspy.py:使用基于python版的ANTs——antspy对图像和其对应的标签同时进行配准
  • CBAM:CBAM注意力模块的实现
  • crop_resize.py:先找到包含脑部区域的最小矩形框,然后手动计算矩形框的大小(每一维应该是16的倍数),然后用已经注释掉的部分进行resize
  • data_augmentation.py:数据增强的代码,包括B样条采样、反转、平移、缩放、旋转、灰度值均衡化等,但B样条采样貌似有问题
  • dcm2nii.py:将dcm格式的三维图像转换为.nii格式的
  • FreeSurfer+FSL.py:先用FreeSurfer对脑部图像进行颅骨剥离,然后用FSL对图像和标签同时进行仿射对齐
  • FreeSurfer.py:用FreeSurfer对脑部图像进行颅骨剥离
  • image_combine_example.py:别人给的,没用过
  • img2nii.py:将.img格式的三维图像转化为.nii格式的
  • jacobian.py:计算形变场的雅克比行列式
  • resize_img.py:对图像进行resize
  • tor_datagenerators.py:基于pytorch的数据生成器

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