luna16肺部CT数据集预处理（根据标注信息生成掩膜）

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已于 2022-03-25 20:16:02 修改 · 3.7k 阅读

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#python

于 2022-03-25 20:03:41 首次发布

本文介绍了一种用于肺结节标注的方法，并演示了如何从医学影像中提取特定区域的过程。通过使用SimpleITK和NumPy等库，实现了肺部CT扫描中结节的自动标注及图像掩膜的生成。

in:（luna16）

*.mhd

*.raw

标注文件：annotations.csv

out:

大小为512*512，只包含一张scan的图片和掩膜

from __future__ import print_function, division
import SimpleITK as sitk
import numpy as np
import csv
from glob import glob
import os
import pandas as pd
try:
    from tqdm import tqdm # long waits are not fun
except:
    print('TQDM does make much nicer wait bars...')
    tqdm = lambda x: x

#Some helper functions

def make_mask(center,diam,z,width,height,spacing,origin):
    '''
Center : centers of circles px -- list of coordinates x,y,z
diam : diameters of circles px -- diameter
widthXheight : pixel dim of image
spacing = mm/px conversion rate np array x,y,z
origin = x,y,z mm np.array
z = z position of slice in world coordinates mm
    '''
    mask = np.zeros([height,width]) # 0's everywhere except nodule swapping x,y to match img
    #convert to nodule space from world coordinates

    # Defining the voxel range in which the nodule falls
    v_center = (center-origin)/spacing
    v_diam = int(diam/spacing[0]+5)
    v_xmin = np.max([0,int(v_center[0]-v_diam)-5])