452 lines
16 KiB
Text
452 lines
16 KiB
Text
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"""
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醫學影像處理程式
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功能：執行 CT 和 MR 影像的處理、轉換和 RTSTRUCT 生成
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使用方式：
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1. 命令列執行：
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python oar.py /nn/3894670/20241111/CT/a /nn/3894670/20241111/MR/6
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2. Jupyter Notebook 執行：
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from oar import inference, SendDCM
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rtss_file = inference("/nn/3894670/20241111/CT/a", "/nn/3894670/20241111/MR/6")
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SendDCM(rtss_file)
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"""
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import os
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import shutil
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import subprocess
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import sys
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import time
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import logging
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from pathlib import Path
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from nipype.interfaces.dcm2nii import Dcm2niix
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from pydicom import dcmread
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from pynetdicom import AE, debug_logger
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from pynetdicom.sop_class import CTImageStorage, RTStructureSetStorage
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from rt_utils import RTStructBuilder
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import numpy as np
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import SimpleITK as sitk
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from registration.best_reg import reg_transform
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# 設定日誌
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.StreamHandler(),
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logging.FileHandler('medical_imaging.log')
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]
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)
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logger = logging.getLogger(__name__)
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def validate_dicom_directory(dicom_path):
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"""
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加強版 DICOM 目錄驗證
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參數:
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dicom_path: str - DICOM 目錄路徑
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回傳:
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tuple: (is_valid: bool, message: str)
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"""
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try:
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if not os.path.exists(dicom_path):
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return False, f"目錄不存在：{dicom_path}"
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if not os.listdir(dicom_path):
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return False, f"目錄是空的：{dicom_path}"
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dicom_files = []
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non_dicom = []
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corrupt_files = []
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series_info = {}
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for filename in os.listdir(dicom_path):
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filepath = os.path.join(dicom_path, filename)
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if os.path.isfile(filepath):
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try:
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ds = dcmread(filepath)
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# 檢查必要的 DICOM 標籤
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if hasattr(ds, 'SeriesInstanceUID'):
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series_uid = ds.SeriesInstanceUID
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if series_uid not in series_info:
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series_info[series_uid] = []
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series_info[series_uid].append(filepath)
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dicom_files.append(filepath)
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else:
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non_dicom.append(filename)
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except Exception as e:
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logger.warning(f"無法讀取檔案 {filename}: {str(e)}")
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if filename.endswith(('.dcm', '.DCM')):
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corrupt_files.append(filename)
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else:
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non_dicom.append(filename)
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if not dicom_files:
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message = f"在 {dicom_path} 中找不到有效的 DICOM 檔案\n"
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if non_dicom:
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message += f"發現 {len(non_dicom)} 個非 DICOM 檔案\n"
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if corrupt_files:
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message += f"發現 {len(corrupt_files)} 個損壞的 DICOM 檔案"
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return False, message
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# 檢查是否所有檔案屬於同一個系列
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if len(series_info) > 1:
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logger.warning(f"發現多個系列: {len(series_info)}")
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# 檢查檔案數量是否合理
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for series_uid, files in series_info.items():
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if len(files) < 5: # 假設至少需要5張影像
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logger.warning(f"系列 {series_uid} 的影像數量過少: {len(files)}")
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return True, f"找到 {len(dicom_files)} 個有效的 DICOM 檔案，分屬 {len(series_info)} 個系列"
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except Exception as e:
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return False, f"驗證過程發生錯誤：{str(e)}"
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def enhanced_dcm2nii(source_dir, output_dir):
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"""
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加強版的 dcm2nii 轉換函式
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參數:
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source_dir: str - 來源 DICOM 目錄
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output_dir: str - NIfTI 檔案的輸出目錄
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回傳:
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tuple: (success: bool, message: str, nifti_files: list)
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"""
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try:
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# 驗證輸入目錄
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is_valid, message = validate_dicom_directory(source_dir)
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if not is_valid:
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return False, message, []
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# 確保輸出目錄存在
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os.makedirs(output_dir, exist_ok=True)
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# 記錄轉換前的檔案
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initial_files = set(os.listdir(output_dir))
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# 設定 dcm2niix 的進階選項
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converter = Dcm2niix()
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converter.inputs.source_dir = source_dir
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converter.inputs.output_dir = output_dir
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converter.inputs.compress = 'y'
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converter.inputs.merge_imgs = True
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converter.inputs.single_file = True
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converter.inputs.verbose = True
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converter.terminal_output = 'stream'
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logger.info(f"執行 DICOM 轉換：{source_dir}")
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try:
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result = converter.run()
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# 輸出 dcm2niix 的詳細日誌
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if hasattr(result, 'runtime'):
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if hasattr(result.runtime, 'stdout'):
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logger.info(f"dcm2niix 輸出：\n{result.runtime.stdout}")
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if hasattr(result.runtime, 'stderr'):
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logger.warning(f"dcm2niix 錯誤：\n{result.runtime.stderr}")
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except Exception as run_error:
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logger.error(f"dcm2niix 執行錯誤：{str(run_error)}")
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# 檢查新產生的檔案
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final_files = set(os.listdir(output_dir))
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new_files = final_files - initial_files
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nifti_files = [f for f in new_files if f.endswith(('.nii.gz', '.nii'))]
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if not nifti_files:
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# 嘗試使用備用轉換選項
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logger.warning("使用備用轉換選項重試...")
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converter.inputs.merge_imgs = False
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converter.inputs.single_file = False
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try:
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result = converter.run()
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except Exception as retry_error:
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logger.error(f"備用轉換選項執行錯誤：{str(retry_error)}")
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final_files = set(os.listdir(output_dir))
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new_files = final_files - initial_files
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nifti_files = [f for f in new_files if f.endswith(('.nii.gz', '.nii'))]
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if not nifti_files:
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return False, "轉換完成但未產生 NIfTI 檔案", []
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# 驗證產生的 NIfTI 檔案
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valid_nifti = []
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for nii_file in nifti_files:
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try:
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img = sitk.ReadImage(os.path.join(output_dir, nii_file))
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if img.GetSize()[2] > 1: # 確保是3D影像
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valid_nifti.append(nii_file)
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else:
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logger.warning(f"檔案 {nii_file} 不是有效的3D影像")
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except Exception as e:
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logger.warning(f"無法讀取 NIfTI 檔案 {nii_file}: {str(e)}")
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if not valid_nifti:
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return False, "轉換產生的 NIfTI 檔案無效", []
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return True, f"成功轉換 {len(valid_nifti)} 個有效的 NIfTI 檔案", valid_nifti
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except Exception as e:
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logger.error(f"DICOM 轉換錯誤：{str(e)}", exc_info=True)
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return False, f"轉換過程發生錯誤：{str(e)}", []
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def inference(DCM_CT, DCM_MR):
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"""
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執行影像推論和後處理
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參數：
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DCM_CT: str - CT 影像的 DICOM 目錄路徑
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DCM_MR: str - MR 影像的 DICOM 目錄路徑
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回傳：
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str: 生成的 RTSTRUCT 檔案路徑
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"""
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logger.info(f"處理影像\nCT: {DCM_CT}\nMR: {DCM_MR}")
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try:
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# 驗證輸入目錄
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for path, desc in [(DCM_CT, "CT"), (DCM_MR, "MR")]:
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is_valid, message = validate_dicom_directory(path)
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if not is_valid:
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raise ValueError(f"{desc} 影像驗證失敗：{message}")
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# 設定工作目錄
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ROOT_DIR = os.path.dirname(os.path.dirname(DCM_CT))
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NII_DIR = os.path.join(ROOT_DIR, 'nii')
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INPUT_DIR = os.path.join(ROOT_DIR, 'input')
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OUTPUT_DIR = os.path.join(ROOT_DIR, 'output')
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# 設定 RTSTRUCT 輸出路徑
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head, tail = os.path.split(DCM_CT)
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rtss_file = os.path.join(head, tail+'-rtss.dcm')
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# 清理並建立工作目錄
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for dir_path in [NII_DIR, INPUT_DIR, OUTPUT_DIR]:
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shutil.rmtree(dir_path, ignore_errors=True)
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os.makedirs(dir_path, exist_ok=True)
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# 取得基本檔名
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nCT = os.path.basename(DCM_CT)
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nMR = os.path.basename(DCM_MR)
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# DICOM 轉 NIfTI
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logger.info("開始轉換 CT DICOM...")
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success_ct, message_ct, ct_files = enhanced_dcm2nii(DCM_CT, NII_DIR)
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if not success_ct:
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raise RuntimeError(f"CT 轉換失敗：{message_ct}")
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logger.info("開始轉換 MR DICOM...")
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success_mr, message_mr, mr_files = enhanced_dcm2nii(DCM_MR, NII_DIR)
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if not success_mr:
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raise RuntimeError(f"MR 轉換失敗：{message_mr}")
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# 尋找轉換後的檔案
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NII_CT = None
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NII_MR = None
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for f in os.listdir(NII_DIR):
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if f.endswith('.nii.gz'):
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full_path = os.path.join(NII_DIR, f)
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if f.startswith(nCT+'_'):
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NII_CT = full_path
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logger.info(f"找到 CT NIfTI 檔案：{f}")
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elif f.startswith(nMR+'_'):
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NII_MR = full_path
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logger.info(f"找到 MR NIfTI 檔案：{f}")
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if not NII_CT:
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raise FileNotFoundError(f"找不到 CT 的 NIfTI 檔案，目錄內容：{os.listdir(NII_DIR)}")
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if not NII_MR:
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raise FileNotFoundError(f"找不到 MR 的 NIfTI 檔案，目錄內容：{os.listdir(NII_DIR)}")
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# 準備輸入檔案
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basename = os.path.basename(NII_MR)
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old = '_'+basename.split('_')[-1]
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input_file = os.path.join(INPUT_DIR, basename.replace(old, '_0000.nii.gz'))
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output_file = os.path.join(OUTPUT_DIR, basename.replace(old, '.nii.gz'))
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basename_ct = os.path.basename(NII_CT)
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old_ct = '_'+basename_ct.split('_')[-1]
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label_file = os.path.join(NII_DIR, basename_ct.replace(old_ct, '.label.nii.gz'))
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logger.info(f"複製 MR NIfTI 到輸入目錄：{input_file}")
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shutil.copy(NII_MR, input_file)
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logger.info("準備執行模型推論...")
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try:
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# 執行模型推論
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subprocess.run([
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"nnUNetv2_predict",
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"-i", INPUT_DIR,
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"-o", OUTPUT_DIR,
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"-m", "2d",
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"-f", "0",
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"-tr", "nnUNetTrainer",
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"-p", "nnUNetPlans",
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"-t", "501",
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"--save_npz"
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], check=True, capture_output=True, text=True)
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except subprocess.CalledProcessError as e:
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logger.error(f"模型推論失敗：\n輸出：{e.output}\n錯誤：{e.stderr}")
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raise RuntimeError("模型推論失敗，請檢查日誌獲取詳細資訊")
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logger.info(f"模型推論完成：{output_file}")
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if not os.path.exists(output_file):
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raise FileNotFoundError(f"找不到模型輸出檔案：{output_file}")
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logger.info("開始執行影像配準...")
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# 影像配準
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try:
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reg_transform(NII_CT, NII_MR, output_file, label_file)
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except Exception as e:
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logger.error(f"影像配準失敗：{str(e)}")
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raise RuntimeError("影像配準失敗")
|
|||
|
|
|
|||
|
|
if not os.path.exists(label_file):
|
|||
|
|
raise FileNotFoundError(f"找不到配準後的標籤檔案：{label_file}")
|
|||
|
|
|
|||
|
|
logger.info("開始建立 RTSTRUCT...")
|
|||
|
|
|
|||
|
|
# 讀取 CT 影像序列
|
|||
|
|
try:
|
|||
|
|
reader = sitk.ImageSeriesReader()
|
|||
|
|
dicom_names = reader.GetGDCMSeriesFileNames(DCM_CT)
|
|||
|
|
reader.SetFileNames(dicom_names)
|
|||
|
|
reader.MetaDataDictionaryArrayUpdateOn()
|
|||
|
|
reader.LoadPrivateTagsOn()
|
|||
|
|
image = reader.Execute()
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"讀取 CT 系列失敗：{str(e)}")
|
|||
|
|
raise RuntimeError("無法讀取 CT 影像系列")
|
|||
|
|
|
|||
|
|
# 重新取樣預測結果
|
|||
|
|
try:
|
|||
|
|
nnU = sitk.ReadImage(label_file)
|
|||
|
|
nnU = sitk.Resample(nnU, image, sitk.Transform(), sitk.sitkNearestNeighbor)
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"重新取樣失敗：{str(e)}")
|
|||
|
|
raise RuntimeError("預測結果重新取樣失敗")
|
|||
|
|
|
|||
|
|
# 連通元件分析
|
|||
|
|
try:
|
|||
|
|
ccfilter = sitk.ConnectedComponentImageFilter()
|
|||
|
|
nnUCC = ccfilter.Execute(nnU)
|
|||
|
|
ObjectCount1 = ccfilter.GetObjectCount()
|
|||
|
|
|
|||
|
|
if ObjectCount1 == 0:
|
|||
|
|
logger.warning("未找到任何連通元件")
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"連通元件分析失敗：{str(e)}")
|
|||
|
|
raise RuntimeError("連通元件分析失敗")
|
|||
|
|
|
|||
|
|
# 建立 RTSTRUCT
|
|||
|
|
try:
|
|||
|
|
rtstruct = RTStructBuilder.create_new(dicom_series_path=DCM_CT)
|
|||
|
|
|
|||
|
|
# 處理每個連通元件
|
|||
|
|
for j1 in range(ObjectCount1):
|
|||
|
|
label1 = sitk.BinaryThreshold(nnUCC, j1+1, j1+1)
|
|||
|
|
mask = sitk.GetArrayFromImage(label1).astype(bool)
|
|||
|
|
mask = np.transpose(mask, (1, 2, 0))
|
|||
|
|
if mask.any():
|
|||
|
|
logger.info(f"處理 ROI {j1+1}/{ObjectCount1}")
|
|||
|
|
rtstruct.add_roi(
|
|||
|
|
mask=mask,
|
|||
|
|
color=[255, 0, 0],
|
|||
|
|
name=f"Tumor_{j1+1}"
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
logger.info(f"儲存 RTSTRUCT：{rtss_file}")
|
|||
|
|
rtstruct.save(rtss_file)
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"RTSTRUCT 生成失敗：{str(e)}")
|
|||
|
|
raise RuntimeError("無法生成或儲存 RTSTRUCT")
|
|||
|
|
|
|||
|
|
return rtss_file
|
|||
|
|
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"推論過程發生錯誤：{str(e)}", exc_info=True)
|
|||
|
|
raise
|
|||
|
|
|
|||
|
|
def SendDCM(fp):
|
|||
|
|
"""
|
|||
|
|
傳送 DICOM 檔案到 PACS
|
|||
|
|
|
|||
|
|
參數：
|
|||
|
|
fp: str - DICOM 檔案路徑
|
|||
|
|
"""
|
|||
|
|
logger.info(f"準備傳送 DICOM 檔案：{fp}")
|
|||
|
|
debug_logger()
|
|||
|
|
|
|||
|
|
if not os.path.exists(fp):
|
|||
|
|
raise FileNotFoundError(f"找不到 DICOM 檔案：{fp}")
|
|||
|
|
|
|||
|
|
try:
|
|||
|
|
ae = AE()
|
|||
|
|
ae.ae_title = 'OUR_STORE_SCP'
|
|||
|
|
ae.add_requested_context(RTStructureSetStorage)
|
|||
|
|
|
|||
|
|
try:
|
|||
|
|
ds = dcmread(fp)
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"讀取 DICOM 檔案失敗：{str(e)}")
|
|||
|
|
raise RuntimeError("無法讀取 DICOM 檔案")
|
|||
|
|
|
|||
|
|
logger.info("正在連接 PACS 伺服器...")
|
|||
|
|
try:
|
|||
|
|
assoc = ae.associate("172.16.40.36", 104, ae_title='N1000_STORAGE')
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"PACS 連接失敗：{str(e)}")
|
|||
|
|
raise RuntimeError("無法連接 PACS 伺服器")
|
|||
|
|
|
|||
|
|
if assoc.is_established:
|
|||
|
|
try:
|
|||
|
|
status = assoc.send_c_store(ds)
|
|||
|
|
if status:
|
|||
|
|
logger.info(f'DICOM 傳送成功，狀態碼: 0x{status.Status:04x}')
|
|||
|
|
else:
|
|||
|
|
raise RuntimeError('傳送失敗：連接逾時或收到無效回應')
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"DICOM 傳送失敗：{str(e)}")
|
|||
|
|
raise
|
|||
|
|
finally:
|
|||
|
|
assoc.release()
|
|||
|
|
else:
|
|||
|
|
raise RuntimeError('傳送失敗：無法建立連接')
|
|||
|
|
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"DICOM 傳送過程發生錯誤：{str(e)}", exc_info=True)
|
|||
|
|
raise
|
|||
|
|
|
|||
|
|
def main():
|
|||
|
|
"""主程式進入點"""
|
|||
|
|
if len(sys.argv) < 3:
|
|||
|
|
print('使用方式:', sys.argv[0], '<CT_DICOM_路徑> <MR_DICOM_路徑>')
|
|||
|
|
print('範例: python oar.py /nn/3894670/20241111/CT/a /nn/3894670/20241111/MR/6')
|
|||
|
|
sys.exit(1)
|
|||
|
|
|
|||
|
|
logger.info('開始執行')
|
|||
|
|
logger.info('程式名稱: %s', sys.argv[0])
|
|||
|
|
logger.info('CT路徑: %s', sys.argv[1])
|
|||
|
|
logger.info('MR路徑: %s', sys.argv[2])
|
|||
|
|
|
|||
|
|
start_time = time.time()
|
|||
|
|
try:
|
|||
|
|
rtss_file = inference(sys.argv[1], sys.argv[2])
|
|||
|
|
SendDCM(rtss_file)
|
|||
|
|
logger.info(f"處理完成，總耗時：{time.time() - start_time:.2f} 秒")
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error(f"處理過程發生錯誤：{str(e)}", exc_info=True)
|
|||
|
|
sys.exit(1)
|
|||
|
|
|
|||
|
|
if __name__ == '__main__':
|
|||
|
|
main()
|