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pydicom

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pydicom

Use pydicom for DICOM dataset I/O and pixel processing. Version 3.0.2 is the current stable release reviewed here. It fixes CVE-2026-32711, a crafted DICOMDIR path-traversal issue. pydicom 3.0.2 declares Python >=3.10; its bundled DICOM dictionary is 2024c, while the live DICOM Standard may be newer.

Mandatory safety boundary

  • Work only with local data that the user is authorized to access.
  • DICOM metadata, file names, private elements, overlays, structured content, and pixels may contain protected health information (PHI).
  • Never print Dataset, export full metadata/JSON, or log element values by default. Use a documented allowlist and aggregate output.
  • pydicom is a general DICOM framework, not a diagnostic viewer. Pixel output, validation, conversion, and plugin availability are not diagnostic claims.
  • De-identification is profile-, purpose-, recipient-, jurisdiction-, and threat-context-specific. It requires privacy/DICOM expert verification.
  • Never claim that a tag-removal script is DICOM PS3.15, HIPAA, GDPR, or other compliance. Preserve originals and audit derived outputs.
  • Treat deterministic pseudonymization keys and UID maps as re-identification secrets: use least privilege and encrypted/managed secret storage, never commit, sync, log, or share them with derivatives, and define backup, rotation, revocation, and destruction procedures. A leaked key invalidates the intended separation; rotation also changes deterministic mappings.
  • Set explicit input-file, file-count, frame-count, decoded-byte, and output limits before parsing untrusted or unusually large datasets.

Installation

Create or activate an isolated environment, then install the exact reviewed release:

bash
uv pip install "pydicom==3.0.2"

Uncompressed pixel arrays and image rendering:

bash
uv pip install "pydicom==3.0.2" "numpy==2.5.1" "Pillow==12.3.0"

Install only the transfer-syntax plugins required by the deployment:

bash
# JPEG/JPEG-LS, JPEG 2000/HTJ2K, and faster RLE through pylibjpeg
uv pip install "numpy==2.5.1" "pylibjpeg==2.1.0" \
  "pylibjpeg-libjpeg==2.4.0" "pylibjpeg-openjpeg==2.5.0" \
  "pylibjpeg-rle==2.2.0"

# JPEG-LS encoder/decoder
uv pip install "numpy==2.5.1" "pyjpegls==1.5.1"

# Alternative decoder with platform-specific wheels
uv pip install "python-gdcm==3.2.6"

Plugin licenses and wheels differ by package/platform; review them before deployment. Pillow has documented decoding limitations and pydicom cautions that plugin output must be independently checked.

Native codec wheels widen the supply-chain and memory-safety boundary. For a controlled deployment, resolve these exact pins on a trusted build host, lock and verify wheel hashes/provenance, mirror approved artifacts internally, scan them, and install with hash enforcement rather than resolving from the public index at runtime.

Choose the workflow

  1. Need an aggregate overview: run scripts/extract_metadata.py.
  2. Need bounded technical checks: run scripts/dicom_inventory.py.
  3. Need codec deployment preflight: run scripts/transfer_syntax_inspector.py.
  4. Need frame/memory planning: run scripts/pixel_frame_planner.py.
  5. Need one non-diagnostic rendered frame: run scripts/dicom_to_image.py.
  6. Need a pseudonymized derivative: read the de-identification section, create a site-reviewed action profile, then run scripts/anonymize_dicom.py and scripts/deidentification_audit.py.
  7. Need to check a sensitive UID map: run scripts/uid_mapping_validator.py.

Read datasets safely

dcmread() returns a FileDataset, a Dataset subclass with File Format state such as file_meta, preamble, and original encoding.

python
from pathlib import Path
import pydicom

path = Path("authorized/input.dcm")
ds = pydicom.dcmread(
    path,
    stop_before_pixels=True,
    specific_tags=[
        "SOPClassUID",
        "Modality",
        "Rows",
        "Columns",
        "NumberOfFrames",
    ],
)

technical = {
    "sop_class": ds.get("SOPClassUID"),
    "modality": ds.get("Modality"),
    "rows": ds.get("Rows"),
    "columns": ds.get("Columns"),
}

Use:

  • stop_before_pixels=True for metadata-only work.
  • specific_tags=[...] for a minimum allowlist.
  • defer_size="1 MiB" when a later write must preserve large values.
  • force=False (default). force=True only bypasses the File Format header check; it does not prove the bytes are valid DICOM.

Do not call print(ds), repr(ds), or iterate values into logs on clinical data.

Dataset, DataElement, and sequences

Access standard elements by keyword and check for absence:

python
modality = ds.get("Modality", "UNSPECIFIED")
if "ReferencedImageSequence" in ds:
    for item in ds.ReferencedImageSequence:
        referenced_class = item.get("ReferencedSOPClassUID")

Tag access, such as ds[0x0010, 0x0010], returns a DataElement; its .value is separate. Sequence behaves like a list of nested Dataset items. Privacy actions must recurse through every sequence item, not only the top level.

When creating a file, use FileMetaDataset for group 0002, keep dataset and file-meta SOP UIDs consistent, set a Transfer Syntax UID, and write in enforced File Format:

python
from pydicom import dcmwrite
from pydicom.dataset import FileDataset, FileMetaDataset
from pydicom.uid import CTImageStorage, ExplicitVRLittleEndian, generate_uid

meta = FileMetaDataset()
meta.MediaStorageSOPClassUID = CTImageStorage
meta.MediaStorageSOPInstanceUID = generate_uid()
meta.TransferSyntaxUID = ExplicitVRLittleEndian

ds = FileDataset(None, {}, file_meta=meta, preamble=b"\0" * 128)
ds.SOPClassUID = meta.MediaStorageSOPClassUID
ds.SOPInstanceUID = meta.MediaStorageSOPInstanceUID
# Add all attributes required by the selected IOD before writing.
dcmwrite("new.dcm", ds, enforce_file_format=True, overwrite=False)

write_like_original is deprecated in pydicom 3.0; use enforce_file_format. A successful write is not full PS3.3 IOD conformance.

UIDs and transfer syntax

The File Meta Information Transfer Syntax UID controls dataset encoding and pixel compression:

python
ts = ds.file_meta.TransferSyntaxUID
summary = {
    "uid": str(ts),
    "name": ts.name,
    "compressed": ts.is_compressed,
    "implicit_vr": ts.is_implicit_VR,
    "little_endian": ts.is_little_endian,
}

pydicom 3.0 chooses write encoding from the Transfer Syntax UID before legacy dataset flags. Do not replace structural UIDs (Transfer Syntax, SOP Class, or coding-scheme UIDs) during pseudonymization. Instance/reference UID replacement must be one-to-one and consistent across the complete declared scope.

Read references/transfer_syntaxes.md before compression, decompression, or encapsulation.

Pixel data and frames

The stable pydicom.pixels API supports path-based, frame-specific decoding:

python
from pydicom.pixels import pixel_array

# Reads only the selected frame where the source permits it.
frame = pixel_array("authorized/image.dcm", index=0, raw=False)

Shape semantics:

  • grayscale single frame: (rows, columns)
  • grayscale multi-frame: (frames, rows, columns)
  • color single frame: (rows, columns, samples)
  • color multi-frame: (frames, rows, columns, samples)

raw=False converts YCbCr pixel data to RGB when possible; raw=True retains the decoded color space after mandatory minimal processing. Use iter_pixels(path, indices=[...]) for bounded multi-frame iteration.

For grayscale display, apply transforms in this order:

python
from pydicom.pixels import apply_modality_lut, apply_voi_lut

modality_values = apply_modality_lut(frame, ds)
display_values = apply_voi_lut(modality_values, ds, index=0)

Modality LUT/rescale and VOI/windowing change display/value semantics. MONOCHROME1 may require presentation inversion. Palette Color requires apply_color_lut(). Presentation states and ICC behavior may require a validated viewer. Never use per-frame min/max normalization for quantitative analysis.

Compression, decompression, and encapsulation

  • Accessing pixel_array decodes as needed but does not change the dataset.
  • Dataset.decompress() changes Pixel Data in place, sets Explicit VR Little Endian, updates image metadata, and generates a new SOP Instance UID by default.
  • Dataset.compress(uid) changes Pixel Data and Transfer Syntax in place and generates a new SOP Instance UID by default.
  • pydicom 3.0 built-in/found encoders cover RLE Lossless, JPEG-LS, and JPEG 2000 combinations documented in the stable plugin matrix.
  • Each compressed frame is separately encoded and then encapsulated. Use encapsulate() or encapsulate_extended() for externally encoded frames.
  • Read frames with current pydicom.encaps.generate_frames() or get_frame(); legacy encapsulation generator names are deprecated for pydicom 4.

Always inspect capabilities first, limit decoded bytes/frames, and verify pixel correctness independently. Lossy compression acceptability is outside pydicom and the DICOM encoding specification.

DICOM JSON and private elements

Dataset.to_json(), to_json_dict(), and Dataset.from_json() implement the DICOM JSON Model, but pydicom documents JSON support as beta. Full JSON may inline binary data and expose every identifier and pixel payload. Do not emit it as a metadata report. A BulkDataURI handler introduces separate storage, authorization, and retrieval obligations.

Private elements are not standardized and may contain PHI:

python
# Recursive removal, but not sufficient de-identification by itself.
ds.remove_private_tags()

Retain private elements only under an explicit reviewed safe-private policy. Read references/common_tags.md for tag access, privacy classes, and standard pointers.

De-identification workflow

DICOM PS3.15 Annex E explicitly states that confidentiality profiles do not guarantee removal of all identifying information and do not replace a complete de-identification process.

  1. Define purpose, recipients, linkage needs, regulations, threat model, and acceptable re-identification risk.
  2. Select the Basic Application Level Confidentiality Profile and needed options (pixel, recognizable visual features, graphics, structured content, descriptors, temporal information, patient characteristics, devices, institutions, UIDs, and safe private data).
  3. Preserve source objects unchanged in controlled storage.
  4. Apply every action recursively, including nested sequences.
  5. Replace instance/reference UIDs consistently across the complete scope; preserve structural UIDs.
  6. Decide date/time handling explicitly. A fixed shift can preserve intervals but partial dates, time zones, standalone times, leap days, longitudinal linkage, and external events require reviewed policy.
  7. Inspect pixels, overlays, graphics, structured content, and recognizable visual features. Do not infer clean pixels from missing metadata or set BurnedInAnnotation=NO without verification.
  8. Rebuild File Meta Information and preamble to prevent leakage.
  9. Run technical validation and a de-identification audit, then perform expert verification and documented risk review.

The bundled script intentionally sets PatientIdentityRemoved to NO because it cannot establish successful de-identification.

Helper CLIs

All --help paths are dependency-free. The tools perform no network access and emit no DICOM values beyond narrow technical allowlists.

Bundled content consists of the two linked references, the documented helper scripts, and synthetic tests. The pydicom runtime dependency is installed from the pinned PyPI release.

bash
# Redacted aggregate metadata
python scripts/extract_metadata.py authorized/ --recursive

# Metadata-only technical inventory
python scripts/dicom_inventory.py authorized/ --recursive

# Installed codec/plugin capabilities
python scripts/transfer_syntax_inspector.py --input authorized/image.dcm

# Frame shape, byte, and transform plan
python scripts/pixel_frame_planner.py authorized/image.dcm --frames 0,2-4

# One non-diagnostic frame
python scripts/dicom_to_image.py authorized/image.dcm frame.png \
  --acknowledge-pixel-phi

# Create a secret key, then a scoped pseudonymized derivative plus audit
python scripts/anonymize_dicom.py --generate-uid-key project.key
python scripts/anonymize_dicom.py authorized/in.dcm derived/out.dcm \
  --uid-key-file project.key --uid-scope export-v1 \
  --audit-report derived/out.audit.json

# Audit candidate metadata; no pixel decompression
python scripts/deidentification_audit.py derived/out.dcm

# Validate an explicitly requested sensitive UID mapping
python scripts/uid_mapping_validator.py derived/uid-map.json \
  --uid-key-file project.key --uid-scope export-v1

The generated raw key file is a controlled-local convenience and is created with owner-only permissions. For production, materialize key bytes from an approved secret manager into a locked ephemeral file, restrict access to the de-identification service, and securely remove it afterward. Store any optional UID map separately from derivatives; it directly links original and replacement identifiers.

pydicom 3.0 migration notes

  • read_file() and write_file() were removed; use dcmread() and dcmwrite().
  • write_like_original is deprecated; use enforce_file_format.
  • pydicom.pixel_data_handlers is deprecated for removal in v4; use pydicom.pixels.
  • Dataset.pixel_array uses the new pixels backend by default and converts YCbCr to RGB when possible.
  • JPEGLossless now means UID 1.2.840.10008.1.2.4.57; JPEGLosslessSV1 is .70.
  • Dataset.is_little_endian and is_implicit_VR are deprecated for v4.

Sources (verified 2026-07-23)