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EscopeFile/merge_aorta.py

+import os
+
+from monai.transforms import LoadImage, SaveImage, AddChannel
+from skimage import measure
+
+
+def connected_component(image):
+    # 标记输入的3D图像
+    label, num = measure.label(image, connectivity=1, return_num=True)
+    if num < 1:
+        return image
+
+    # 获取对应的region对象
+    region = measure.regionprops(label)
+    # 获取每一块区域面积并排序
+    num_list = [i for i in range(1, num + 1)]
+    area_list = [region[i - 1].area for i in num_list]
+    num_list_sorted = sorted(num_list, key=lambda x: area_list[x - 1])[::-1]
+    # 去除面积较小的连通域
+    if len(num_list_sorted) > 3:
+        # for i in range(3, len(num_list_sorted)):
+        for i in num_list_sorted[3:]:
+            # label[label==i] = 0
+            label[region[i - 1].slice][region[i - 1].image] = 0
+        num_list_sorted = num_list_sorted[:3]
+    return label
+
+
+coronary_path = r"F:\data\cta-data\coronary-144\train\labels"  # 冠脉label路径
+aorta_path = r"F:\data\cta-data\Aorta_mask_15cases"  # 带aorta的冠脉label路径
+merge1_path = r"F:\data\cta-data\merge_coronary_CAC"  # 合并冠脉和钙化的label路径
+load = LoadImage()
+files = [file for file in os.listdir(aorta_path)]
+for aorta_file in files:
+    print(aorta_file)
+    aorta_name, nii_ext = aorta_file.split(".", 1)
+    aorta = aorta_name.split("_")
+    coronary_name = aorta[0] + "_" + aorta[1] + "_mask"
+    merge1_name = coronary_name + "_merge"
+    coronary_file = coronary_name + "." + nii_ext
+    merge1_file = merge1_name + "." + nii_ext
+    aorta_label, meta_aorta = load(os.path.join(aorta_path, aorta_file))
+    coronary_label, meta_coronary = load(os.path.join(coronary_path, coronary_file))
+    merge1_label, meta_merge1 = load(os.path.join(merge1_path, merge1_file))
+    label = aorta_label - coronary_label
+    label[label < 0] = 0
+    label = connected_component(label)
+    label[label > 1] = 0
+    merge_aorta_label = label * 3 + merge1_label
+    merge_aorta_label[merge_aorta_label > 3] = 0
+    # print(aorta)
+    save = SaveImage(output_dir=r"F:\data\cta-data\merge_labels", output_postfix='merge_aorta', output_ext='.nii.gz',
+                     resample=True, mode='nearest', separate_folder=False)
+    save(img=AddChannel()(merge_aorta_label), meta_data=meta_coronary)
+