# dicompare
[](https://astewartau.github.io/dicompare/)
dicompare is a DICOM validation tool designed to ensure compliance with study-specific imaging protocols and domain-specific guidelines while preserving data privacy. It provides multiple interfaces, including support for validation directly in the browser, leveraging WebAssembly (WASM), Pyodide, and the underlying pip package [`dicompare`](#dicompare). dicompare is suitable for multi-site studies and clinical environments without requiring software installation or external data uploads.
dicompare supports DICOM session validation against:
- **Session schemas**: JSON schema files that can be generated based on a reference session;
- **[TESTING] domain guidelines**: Flexible guidelines for specific domains (currently [QSM](https://doi.org/10.1002/mrm.30006));
- **[FUTURE] landmark studies**: Schema files based on landmark studies such as the [HCP](https://doi.org/10.1038/s41586-018-0579-z), [ABCD](https://doi.org/10.1016/j.dcn.2018.03.001), and [UK BioBank](https://doi.org/10.1038/s41586-018-0579-z) projects.
# Command-line interface (CLI) and application programming interface (API)
While you can run [dicompare](https://astewartau.github.io/dicompare/) in your browser now without any installation, you may also use the underlying `dicompare` pip package if you wish to use the command-line interface (CLI) or application programming interface (API).
```bash
pip install dicompare
```
## Command-line interface (CLI)
The package provides the following CLI entry points:
- `dcm-gen-session`: Generate JSON schemas for DICOM validation.
- `dcm-check-session`: Validate DICOM sessions against predefined schemas.
1. Generate a JSON Reference Schema
```bash
dcm-gen-session \
--in_session_dir /path/to/dicom/session \
--out_json_ref schema.json \
--acquisition_fields ProtocolName SeriesDescription \
--reference_fields EchoTime RepetitionTime
```
This will create a JSON schema describing the session based on the specified fields.
2. Validate a DICOM Session
```bash
dicompare-session \
--in_session /path/to/dicom/session \
--json_ref schema.json \
--out_json compliance_report.json
```
The tool will output a compliance summary, indicating deviations from the reference schema.
## Python API
The `dicompare` package provides a Python API for programmatic schema generation and validation.
**Generate a schema:**
```python
from dicompare.io import read_dicom_session
reference_fields = ["EchoTime", "RepetitionTime"]
acquisition_fields = ["ProtocolName", "SeriesDescription"]
session_data = read_dicom_session(
session_dir="/path/to/dicom/session",
acquisition_fields=acquisition_fields,
reference_fields=reference_fields
)
# Save the schema as JSON
import json
with open("schema.json", "w") as f:
json.dump(session_data, f, indent=4)
```
**Validate a session:**
```python
from dicompare.io import read_json_session, read_dicom_session
from dicompare.compliance import check_session_compliance
# Load the schema
acquisition_fields, reference_fields, ref_session = read_json_session(json_ref="schema.json")
# Read the input session
in_session = read_dicom_session(
session_dir="/path/to/dicom/session",
acquisition_fields=acquisition_fields,
reference_fields=reference_fields
)
# Perform compliance check
compliance_summary = check_session_compliance(
in_session=in_session,
ref_session=ref_session,
series_map=None # Optional: map series if needed
)
# Print compliance summary
for entry in compliance_summary:
print(entry)
```
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"description": "# dicompare\n\n[](https://astewartau.github.io/dicompare/)\n\ndicompare is a DICOM validation tool designed to ensure compliance with study-specific imaging protocols and domain-specific guidelines while preserving data privacy. It provides multiple interfaces, including support for validation directly in the browser, leveraging WebAssembly (WASM), Pyodide, and the underlying pip package [`dicompare`](#dicompare). dicompare is suitable for multi-site studies and clinical environments without requiring software installation or external data uploads.\n\ndicompare supports DICOM session validation against:\n\n- **Session schemas**: JSON schema files that can be generated based on a reference session;\n- **[TESTING] domain guidelines**: Flexible guidelines for specific domains (currently [QSM](https://doi.org/10.1002/mrm.30006));\n- **[FUTURE] landmark studies**: Schema files based on landmark studies such as the [HCP](https://doi.org/10.1038/s41586-018-0579-z), [ABCD](https://doi.org/10.1016/j.dcn.2018.03.001), and [UK BioBank](https://doi.org/10.1038/s41586-018-0579-z) projects.\n\n# Command-line interface (CLI) and application programming interface (API)\n\nWhile you can run [dicompare](https://astewartau.github.io/dicompare/) in your browser now without any installation, you may also use the underlying `dicompare` pip package if you wish to use the command-line interface (CLI) or application programming interface (API).\n\n```bash\npip install dicompare\n```\n\n## Command-line interface (CLI)\n\nThe package provides the following CLI entry points:\n\n- `dcm-gen-session`: Generate JSON schemas for DICOM validation.\n- `dcm-check-session`: Validate DICOM sessions against predefined schemas.\n\n1. Generate a JSON Reference Schema\n\n```bash\ndcm-gen-session \\\n --in_session_dir /path/to/dicom/session \\\n --out_json_ref schema.json \\\n --acquisition_fields ProtocolName SeriesDescription \\\n --reference_fields EchoTime RepetitionTime\n```\n\nThis will create a JSON schema describing the session based on the specified fields.\n\n2. Validate a DICOM Session\n\n```bash\ndicompare-session \\\n --in_session /path/to/dicom/session \\\n --json_ref schema.json \\\n --out_json compliance_report.json\n```\n\nThe tool will output a compliance summary, indicating deviations from the reference schema.\n\n## Python API\n\nThe `dicompare` package provides a Python API for programmatic schema generation and validation.\n\n**Generate a schema:**\n\n```python\nfrom dicompare.io import read_dicom_session\n\nreference_fields = [\"EchoTime\", \"RepetitionTime\"]\nacquisition_fields = [\"ProtocolName\", \"SeriesDescription\"]\n\nsession_data = read_dicom_session(\n session_dir=\"/path/to/dicom/session\",\n acquisition_fields=acquisition_fields,\n reference_fields=reference_fields\n)\n\n# Save the schema as JSON\nimport json\nwith open(\"schema.json\", \"w\") as f:\n json.dump(session_data, f, indent=4)\n```\n\n**Validate a session:**\n\n```python\nfrom dicompare.io import read_json_session, read_dicom_session\nfrom dicompare.compliance import check_session_compliance\n\n# Load the schema\nacquisition_fields, reference_fields, ref_session = read_json_session(json_ref=\"schema.json\")\n\n# Read the input session\nin_session = read_dicom_session(\n session_dir=\"/path/to/dicom/session\",\n acquisition_fields=acquisition_fields,\n reference_fields=reference_fields\n)\n\n# Perform compliance check\ncompliance_summary = check_session_compliance(\n in_session=in_session,\n ref_session=ref_session,\n series_map=None # Optional: map series if needed\n)\n\n# Print compliance summary\nfor entry in compliance_summary:\n print(entry)\n```\n\n",
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