pydicom

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Pydicom - Medical Imaging Standards

Pydicom - 医学影像标准

DICOM is more than an image; it's a rich data structure containing patient info, spatial orientation, and pixel data. Pydicom provides access to all these tags.

DICOM不仅仅是一种图像格式，它是一种包含患者信息、空间定位和像素数据的丰富数据结构。Pydicom可让你访问所有这些标签。

When to Use

适用场景

Processing medical imaging data (CT, MRI, X-ray, ultrasound).
Extracting patient metadata and clinical information from DICOM files.
Building AI models for radiology that require both image and metadata.
Converting DICOM to other formats for analysis.
Quality assurance and compliance checking in medical imaging workflows.

处理医学影像数据（CT、MRI、X光、超声）。
从DICOM文件中提取患者元数据和临床信息。
构建需要同时使用图像和元数据的放射科AI模型。
将DICOM转换为其他格式用于分析。
医学影像工作流中的质量保证与合规性检查。

Core Principles

核心原则

Datasets as Dicts

数据集作为字典

Access tags by name (e.g.,

ds.PatientName

) or ID (

ds[0x0010, 0x0010]

通过名称（例如

ds.PatientName

）或ID（

ds[0x0010, 0x0010]

）访问标签。

Pixel Data

像素数据

Raw pixel data is stored in

PixelData

, but should be accessed via

pixel_array

for NumPy integration.

原始像素数据存储在

PixelData

中，但应通过

pixel_array

访问以实现与NumPy的集成。

VR (Value Representation)

VR（值表示）

Strict typing for dates, ages, and decimals ensures data integrity.

对日期、年龄和小数的严格类型定义确保数据完整性。

Quick Reference

快速参考

Standard Imports

标准导入

python

import pydicom
from pydicom.data import get_testdata_files
import matplotlib.pyplot as plt
import numpy as np

python

import pydicom
from pydicom.data import get_testdata_files
import matplotlib.pyplot as plt
import numpy as np

Basic Patterns

基础用法

python

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python

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1. Read file

1. 读取文件

ds = pydicom.dcmread("scan.dcm")

2. Access Metadata

2. 访问元数据

print(f"Patient: {ds.PatientName}, ID: {ds.PatientID}") print(f"Modality: {ds.Modality}") # CT, MR, DX print(f"Study Date: {ds.StudyDate}") print(f"Slice Thickness: {ds.SliceThickness}")

3. Access Image

3. 访问图像

plt.imshow(ds.pixel_array, cmap="gray") plt.title(f"{ds.Modality} - {ds.PatientName}")

undefined

plt.imshow(ds.pixel_array, cmap="gray") plt.title(f"{ds.Modality} - {ds.PatientName}")

undefined

Critical Rules

重要规则

✅ DO

✅ 建议做法

Use pixel_array property - Always access pixel data via
```
ds.pixel_array
```
rather than
```
ds.PixelData
```
for proper NumPy integration.
Check for missing tags - Use
```
hasattr(ds, 'TagName')
```
before accessing optional tags.
Respect patient privacy - DICOM files contain PHI (Protected Health Information). Always anonymize before sharing.
Handle different photometric interpretations - Some images may be inverted or use different color spaces.

使用pixel_array属性 - 始终通过
```
ds.pixel_array
```
访问像素数据，而非
```
ds.PixelData
```
，以实现与NumPy的正确集成。
检查缺失标签 - 在访问可选标签前使用
```
hasattr(ds, 'TagName')
```
进行检查。
尊重患者隐私 - DICOM文件包含PHI（受保护健康信息）。分享前务必匿名化。
处理不同的光度解释 - 部分图像可能存在反转或使用不同的色彩空间。

❌ DON'T

❌ 禁止做法

Don't modify DICOM files in place - Always create a copy when modifying to preserve original data.
Don't ignore VR types - DICOM has strict data types. Converting incorrectly can corrupt data.
Don't assume all DICOM files have images - Some contain only metadata (structured reports).

不要原地修改DICOM文件 - 修改时务必创建副本以保留原始数据。
不要忽略VR类型 - DICOM有严格的数据类型。错误转换可能导致数据损坏。
不要假设所有DICOM文件都包含图像 - 部分文件仅包含元数据（结构化报告）。

Advanced Patterns

高级用法

Working with DICOM Series

处理DICOM序列

python

import pydicom
from pathlib import Path

python

import pydicom
from pathlib import Path

Load a series of DICOM files

加载一系列DICOM文件

dicom_dir = Path("dicom_series") files = sorted(dicom_dir.glob("*.dcm"))

Load and stack slices

加载并堆叠切片

slices = [pydicom.dcmread(f) for f in files] volume = np.stack([s.pixel_array for s in slices])

undefined

slices = [pydicom.dcmread(f) for f in files] volume = np.stack([s.pixel_array for s in slices])

undefined

Anonymization

匿名化

python

undefined

python

undefined

Remove patient identifiers

移除患者标识符

ds.PatientName = "ANONYMOUS" ds.PatientID = "000000" ds.PatientBirthDate = "" ds.PatientSex = ""


Pydicom is the foundation of medical imaging in Python, enabling researchers and clinicians to work with the rich, standardized DICOM format that powers modern radiology.

ds.PatientName = "ANONYMOUS" ds.PatientID = "000000" ds.PatientBirthDate = "" ds.PatientSex = ""


Pydicom是Python医学影像领域的基础工具，助力研究人员和临床医生处理支撑现代放射学的标准化DICOM格式的丰富数据。