Update convert.py

convert.py

@@ -3,12 +3,15 @@ import os
 import pydicom
 import pydicom_seg
 
+import dicom2nifti
+
 import pandas as pd
 import SimpleITK as sitk
 
 from tqdm import tqdm
 
 
+data = pd.read_csv('NSCLC-Radiomics/metadata.csv')
 patient_ids = data['Subject ID'].unique()
 
 for pid in tqdm(patient_ids):
@@ -17,23 +20,16 @@ for pid in tqdm(patient_ids):
     out_fn = f'NSCLC-Radiomics-NIFTI/{pid}'
     os.makedirs(out_fn)
 
-    try:
-        inp_fn_img = row[row['Number of Images'] > 1]['File Location'].values[0]
-        dicom2nifti.convert_directory(inp_fn_img, out_fn)
-    except:
-        print(f'Image {inp_fn_img} failed to convert')
-        pass
-
-    try:
-        inp_fn_seg = row[row['File Location'].str.contains('Segmentation')]['File Location'].values[0] + '/1-1.dcm'
-        dcm = pydicom.dcmread(inp_fn_seg)
-        reader = pydicom_seg.SegmentReader()
-        result = reader.read(dcm)
-
-        for segment_number in result.available_segments:
-            image = result.segment_image(segment_number)  # lazy construction
-            sitk.WriteImage(image, os.path.join(out_fn, f'seg-{result.segment_infos[segment_number].SegmentDescription}.nii.gz'), True)
-    except:
-        print(f'Segmentation {inp_fn_seg} failed to convert')
-        pass
+    inp_fn_img = row[row['SOP Class Name'] == 'CT Image Storage']['File Location'].values[0]
+    dicom2nifti.convert_directory(inp_fn_img, out_fn)
+
+    if pid == 'LUNG1-128': continue  # LUNG1-128 missing segmentation
+
+    inp_fn_seg = row[row['SOP Class Name'] == 'Segmentation Storage']['File Location'].values[0] + '/1-1.dcm'
+    dcm = pydicom.dcmread(inp_fn_seg)
+    reader = pydicom_seg.SegmentReader()
+    result = reader.read(dcm)
 
+    for segment_number in result.available_segments:
+        image = result.segment_image(segment_number)  # lazy construction
+        sitk.WriteImage(image, os.path.join(out_fn, f'seg-{result.segment_infos[segment_number].SegmentDescription}.nii.gz'), True)