75 lines
2.3 KiB
Python
75 lines
2.3 KiB
Python
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import os
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import SimpleITK as sitk
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from config.constant import LABEL_MAP
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import numpy as np
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"""
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# 沿用原本 LABEL_MAP
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seg_bone(n, name, img, lbl)
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# user 自定義
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my_map = {1: "L1", 2: "L2", 3: "L3"}
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seg_bone(n, name, img, lbl, label_map=my_map)
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"""
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def seg_bone(n, name, resampled_sitk_img, resampled_sitk_lbl, output_base=None, label_map=LABEL_MAP):
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if output_base==None:
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output_base=='Dataset'
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if n not in label_map:
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raise ValueError(f"Label {n} not found in label_map")
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label_name = label_map[n]
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lssif = sitk.LabelShapeStatisticsImageFilter()
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lssif.Execute(resampled_sitk_lbl)
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if not lssif.HasLabel(n):
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raise RuntimeError(f"Label {n} not found")
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bbox2 = lssif.GetBoundingBox(n)
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roi = sitk.RegionOfInterest(resampled_sitk_img, bbox2[3:], bbox2[:3])
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label2 = sitk.RegionOfInterest(resampled_sitk_lbl, bbox2[3:], bbox2[:3])
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roi_path = os.path.join(output_base, f"{label_name}_roi.nii.gz")
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sitk.WriteImage(roi, roi_path)
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binary = sitk.BinaryThreshold(label2, lowerThreshold=n, upperThreshold=n, outsideValue=0, insideValue=1)
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binary_path = os.path.join(output_base, f"{label_name}_binary.nii.gz")
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sitk.WriteImage(binary, binary_path)
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roi_pixel_type = roi.GetPixelID()
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binary_cast = sitk.Cast(binary, roi_pixel_type)
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roi2 = roi * binary_cast
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roi2_path = os.path.join(output_base, f"{label_name}_roi2.nii.gz")
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sitk.WriteImage(roi2, roi2_path)
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lsif = sitk.LabelStatisticsImageFilter()
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label2_int = sitk.Cast(label2, sitk.sitkUInt16)
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lsif.Execute(roi2, label2_int)
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labels_in_roi = lsif.GetLabels()
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if n in labels_in_roi:
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roi_hu = sitk.GetArrayFromImage(roi2)
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threshold = np.percentile(roi_hu, 60)
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else:
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threshold = lsif.GetMedian(labels_in_roi[0])
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cortical = sitk.BinaryThreshold(roi2, lowerThreshold=threshold, upperThreshold=10000, outsideValue=0, insideValue=1)
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cortical_path = os.path.join(output_base, f"{label_name}_cortical.nii.gz")
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sitk.WriteImage(cortical, cortical_path)
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return roi_path, binary_path, roi2_path, cortical_path
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"""
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Dataset/
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└── standardized/
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└── subject001/
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├── L1_roi.nii.gz
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├── L1_binary.nii.gz
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├── L1_roi2.nii.gz
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├── L1_cortical.nii.gz
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├── L2_roi.nii.gz
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├── L2_binary.nii.gz
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...
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"""
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