convert.py

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):

    row = data[data['Subject ID'] == pid]
    out_fn = f'NSCLC-Radiomics-NIFTI/{pid}'
    os.makedirs(out_fn)

    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)