LIDC-IDRI数据集制作
0.下载
0.0 链接汇总
- LIDC-IDRI官方网址：https://www.cancerimagingarchive.net/nbia-search/?CollectionCriteria=LIDC-IDRI
- NBIA Data Retriever 下载链接：https://wiki.cancerimagingarchive.net/display/NBIA/Downloading+TCIA+Images
0.1 步骤
- 检索
分成两种，Simple Search一个是多种关键字筛选，鉴定为没用。
直接用Text Search ，将annotation的ID输上，点击search
- 加入Cart
检索出来会有好几种模态/任务的数据，选择自己需要点击购物车加入Cart。
例如：我是做CT分割，故只选择模态为CT的那个数据。
重复Text检索步骤，得到最终自己需要的所有Cart：
- 下载
-
安装好NBIA Data Retriever
前面链接下载，或者Download->Get NBIA Data Retriever 下载，有官方指引。
-
生成manifest文件
-
下载
设置好路径，点击start
1.合成CT图
这边是直接偷了NaviAirwayi的代码进行dicom文件merge成nii文件。
文件结构需要为：
如果按照之前步骤进行下载的话，获得的文件就是上述结构。只是子文件名称会因为太长而被修改，不过不影响结果，最终生成文件名是按照一级目录命名。
预处理代码完整如下：
c
import numpy as np
import os
import SimpleITK as sitk
from PIL import Image
import pydicom
import cv2
import nibabel as nib
import pydicom
## funtion
#####-----------------------------------------------------------------------
def loadFile(filename):
ds = sitk.ReadImage(filename)
#pydicom.dcmread(filename)
img_array = sitk.GetArrayFromImage(ds)
frame_num, width, height = img_array.shape
#print("frame_num, width, height: "+str((frame_num, width, height)))
return img_array, frame_num, width, height
'''
def loadFileInformation(filename):
information = {}
ds = pydicom.read_file(filename)
information['PatientID'] = ds.PatientID
information['PatientName'] = ds.PatientName
information['PatientSex'] = ds.PatientSex
information['StudyID'] = ds.StudyID
information['StudyDate'] = ds.StudyDate
information['StudyTime'] = ds.StudyTime
information['Manufacturer'] = ds.Manufacturer
return information
'''
def get_3d_img_for_one_case(img_path_list, img_format="dcm"):
img_3d=[]
for idx, img_path in enumerate(img_path_list):
print("progress: "+str(idx/len(img_path_list))+"; "+str(img_path), end="\r")
img_slice, frame_num, _, _ = loadFile(img_path)
assert frame_num==1
img_3d.append(img_slice)
img_3d=np.array(img_3d)
return img_3d.reshape(img_3d.shape[0], img_3d.shape[2], img_3d.shape[3])
#####-----------------------------------------------------------------------
# the path to LIDC-IDRI raw images
LIDC_IDRI_raw_path = "G:\BAS_test_raw\manifest-1708937949454\LIDC-IDRI"
LIDC_IDRI_raw_img_dict = {}
img_names = os.listdir(LIDC_IDRI_raw_path)
img_names.sort()
img_names
path_to_a_case = ""
def find_imgs(input_path):
global path_to_a_case
items = os.listdir(input_path)
items.sort()
# print("There are "+str(items)+" in "+str(input_path))
All_file_flag = True
for item in items:
if os.path.isdir(input_path + "/" + item):
All_file_flag = False
break
if All_file_flag and len(items) > 10:
# print("we get "+str(input_path))
path_to_a_case = input_path
else:
for item in items:
if os.path.isdir(input_path + "/" + item):
# print("open filefloder: "+str(input_path+"/"+item))
find_imgs(input_path + "/" + item)
for idx, img_name in enumerate(img_names):
print(idx / len(img_names), end="\r")
find_imgs(LIDC_IDRI_raw_path + "/" + img_name)
slice_names = os.listdir(path_to_a_case)
slice_names.sort()
LIDC_IDRI_raw_img_dict[img_name] = []
for slice_name in slice_names:
if slice_name.split(".")[1] == "dcm":
LIDC_IDRI_raw_img_dict[img_name].append(path_to_a_case + "/" + slice_name)
print("Show the case names: "+str(LIDC_IDRI_raw_img_dict.keys()))
# set output path
output_image_path = r"G:\myBAS\test\images"
if not os.path.exists(output_image_path):
os.mkdir(output_image_path)
for case in LIDC_IDRI_raw_img_dict.keys():
img_3d = get_3d_img_for_one_case(LIDC_IDRI_raw_img_dict[case])
sitk.WriteImage(sitk.GetImageFromArray(img_3d),
output_image_path + "/" + case + ".nii.gz")今天折腾了半死，希望对大家有帮助。