从医院云影像中提取dicom

参考资料：
医疗云影像下载器，从在线报告下载 CT、MRI 等片子的 DICOM 文件

（这个项目的思路，是从在线报告的云胶片中，下载 CT、MRI 等片子的 DICOM 文件，需要适配特别多的平台）

将医院给的在线CT查阅链接中提取为本地DICOM文件
（思路：用浏览器查看云胶片，然后将查看过程中的浏览保存为HAR, 再将HAR中的dicom数据提取出来，避免了适配不同的平台，只有胶片能用浏览器查看就行）

根据第2种思路，做了些优化改进：

import os
import json
import argparse
import base64
import binascii
from io import BytesIO
from datetime import datetime
from collections import defaultdict

import pydicom





def get_patient_name(ds):
    pn = getattr(ds, "PatientName", None)
    if not pn:
        return "UnknownPatient"

    try:
        return str(pn).replace("^", "_")
    except:
        return "UnknownPatient"






# ========= HAR → DICOM =========

def extract_dicoms_from_har(har_path):
    with open(har_path, 'r', encoding='utf-8') as f:
        har = json.load(f)

    dicoms = []
    seen_sop = set()

    for entry in har.get("log", {}).get("entries", []):
        content = entry.get("response", {}).get("content", {})
        text = content.get("text")

        if not text:
            continue

        if content.get("encoding") != "base64":
            continue

        try:
            raw = base64.b64decode(text.encode("utf-8"))
        except binascii.Error:
            continue

        if len(raw) < 256:
            continue

        try:
            ds = pydicom.dcmread(BytesIO(raw), stop_before_pixels=True)
        except Exception as e:
            print("invalid dicom:", e)
            continue

        sop_uid = getattr(ds, "SOPInstanceUID", None)
        if not sop_uid or sop_uid in seen_sop:
            continue

        seen_sop.add(sop_uid)

        dicoms.append((ds, raw))

    return dicoms




# ========= group + sort =========

def group_dicoms(dicoms):
    tree = defaultdict(lambda: defaultdict(lambda: defaultdict(list)))

    for ds, raw in dicoms:
        patient = get_patient_name(ds)
        study = getattr(ds, "StudyInstanceUID", "UnknownStudy")
        series = getattr(ds, "SeriesInstanceUID", "UnknownSeries")

        tree[patient][study][series].append((ds, raw))

    return tree


def sort_by_instance_number(slices):
    slices = sorted(
        slices,
        key=lambda x: getattr(x[0], "InstanceNumber", 0)
    )


    nums = [getattr(ds, "InstanceNumber") for ds, _ in slices]
    if len(nums) != len(set(nums)):
        print("⚠️ InstanceNumber existed.")

    return slices





# ========= save =========

def save_tree(tree, base_folder):
    timestamp = datetime.now().strftime('%Y%m%d%H%M%S')
    root = os.path.join(base_folder, "dicom_output", timestamp)

    for patient, studies in tree.items():
        for study, series_dict in studies.items():
            for series, slices in series_dict.items():

                sorted_slices = sort_by_instance_number(slices)

                folder = os.path.join(root, patient, study, series)
                os.makedirs(folder, exist_ok=True)

                for i, (ds, raw) in enumerate(sorted_slices):
                    filename = f"{i+1:04d}.dcm"
                    path = os.path.join(folder, filename)

                    with open(path, "wb") as f:
                        f.write(raw)

                print(f"[OK] {patient} | {series} -> {len(sorted_slices)} slices")

    print(f"\noutput dir: {root}")




def run(har_path, output_folder):
    dicoms = extract_dicoms_from_har(har_path)
    
    if not dicoms:
        print("not found DICOM，exit...")
        return    

    print(f"extracted DICOM count: {len(dicoms)}")
    tree = group_dicoms(dicoms)
    save_tree(tree, output_folder)




if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="extrace DICOM from HAR and save to file")
    parser.add_argument("har_file", help="HAR file path")
    parser.add_argument("output_dir", help="output dir")
    args = parser.parse_args()
    
    run(args.har_file, args.output_dir)

都是用python完成的