DICOM Metadata Viewer

View metadata from DICOM (.dcm) medical imaging files: CT, MRI, X-ray, ultrasound. Extract patient, study, series, equipment, and image tags. No desktop DICOM viewer required.

1.0.0
Version
Auth
Batch

About DICOM Metadata Viewer

A radiology DVD lands on your desk, a research collaborator emails a .dcm sample, or a vendor ships an export from a CT scanner — and you just need to know what's inside the header. The desktop options (MicroDicom, OsiriX, RadiAnt, Horos) are full PACS workstations built for clinical interpretation; they take minutes to install, want to organise a study tree, and bury the actual tag list under a viewer optimised for pixels. Most online viewers are the same — focused on rendering the image, with the metadata tab as an afterthought.

This DICOM metadata viewer does the inverse — it parses the header only and never reads pixel data (stop_before_pixels=True in pydicom). The output is an organised summary in five groups — Patient, Study, Series, Equipment, Image — followed by a complete tag dump with group/element/VR/value columns (up to 500 tags). Modality (CT, MR, CR, US, PT, MG, …) and the Transfer Syntax UID are surfaced at the top so you can tell at a glance whether the file is Explicit VR Little Endian, JPEG 2000 lossless, or one of the dozen other DICOM transports. Files up to 30 MB are processed in a stateless function and discarded immediately after the response.

Use it to audit what PHI is sitting in a file before you share it with a collaborator, debug a transfer-syntax mismatch between a scanner and a PACS, dump tags into Excel for a research cohort, look up the acquisition parameters of a study someone emailed you, or sanity-check a de-identification script's output. CSV (UTF-8 BOM, Excel-ready) and JSON downloads are generated alongside the on-page table.

DICOM Metadata Viewer Use Cases

  • Researchers auditing what PHI sits in a study before sharing it externally
  • Imaging engineers debugging Transfer Syntax mismatches between a scanner and PACS
  • Radiology trainees learning what tags accompany a CT, MRI or ultrasound study
  • Building research cohorts by dumping per-study tags to CSV for Excel pivot tables
  • Verifying a de-identification script actually stripped the tags it claimed to strip
  • Looking up acquisition parameters of a sample DICOM emailed by a vendor
  • Quick sanity-check on a .dcm file before importing it into an AI training pipeline

DICOM Metadata Viewer Features

  • Reads metadata only — pixel data is never decoded (stop_before_pixels), so file processing stays fast and PHI in pixels stays untouched
  • Five-group organised summary — Patient, Study, Series, Equipment, Image — with human-readable labels and date/time formatting
  • Complete tag dump up to 500 entries with group/element hex, VR, name and value columns; binary blobs truncated for sanity
  • Detects Modality (CT, MR, CR, US, PT, MG, …) and Transfer Syntax UID up front for quick file identification
  • Pixel info summary — rows, columns, bits allocated/stored, photometric interpretation, samples per pixel, frame count — without reading pixels
  • Exports the full tag table to CSV (UTF-8 BOM for Excel) and JSON for programmatic downstream use
  • Files up to 30 MB processed in a stateless serverless function and discarded immediately after the response

How to Use DICOM Metadata Viewer

Upload a .dcm file

Drag-and-drop or click to select a single DICOM file (up to 30 MB). Multi-series studies should be uploaded one image at a time — for batches, scripted pydicom is the right tool.

Click Parse

The file is read in a stateless serverless function with pydicom in stop-before-pixels mode. Metadata is extracted to a five-group summary plus a complete tag dump; the file is deleted immediately after.

Review the five summary groups

Patient (ID, name, DOB, sex, age), Study (date, description, accession, referring physician, UID), Series (modality, description, body part), Equipment (manufacturer, model, station, institution), Image (rows, columns, bits, pixel spacing).

Inspect the full tag table

Below the summary, every non-pixel tag is listed with its group/element hex tuple, name, VR (value representation) and value. Binary or oversize values are truncated at 500 chars so the table stays usable.

Download CSV or JSON

Click 'Download CSV' for an Excel-ready spreadsheet with UTF-8 BOM, or 'Download JSON' for the full structured payload to feed into a Python or JavaScript pipeline.

DICOM Metadata Viewer FAQ

The full file bytes are uploaded so that pydicom can parse the DICOM container, but pixel data is never decoded — pydicom is called with stop_before_pixels=True, so the (7FE0,0010) Pixel Data element is skipped entirely. The file is processed in a stateless serverless function and deleted immediately after the response is returned. Nothing is logged to durable storage.

Any modality. The header parser is modality-agnostic — CT, MR, CR (computed radiography), DX (digital radiography), US (ultrasound), PT (PET), MG (mammography), NM (nuclear medicine), XA (X-ray angio), OT (other) and the rest all expose the same patient/study/series/equipment/image tag structure. The Modality field is shown at the top of the summary so you can confirm.

30 MB per file. This covers single CT slices, MRI images and most X-ray and ultrasound captures. Multi-frame ultrasound clips, CT volumes and DICOM-encapsulated PDFs can exceed 30 MB — for those, save a single representative image first, or use scripted pydicom locally to iterate across an entire series.

Desktop viewers are PACS workstations built to render and interpret images. This is a focused metadata inspector — no image render, no annotation, no MPR — that gives you the header tags in a clean organised view with CSV and JSON export. Useful when the question is 'what's in the header?' rather than 'what does the image show?' and when installing a 200 MB workstation isn't justified.

It identifies the byte-level encoding of the file — for example 1.2.840.10008.1.2.1 is Explicit VR Little Endian (uncompressed), 1.2.840.10008.1.2.4.70 is JPEG Lossless and 1.2.840.10008.1.2.4.91 is JPEG 2000. PACS and scanner negotiation mismatches almost always trace back to this field, so it's shown at the top of the summary.

Not directly — this viewer is read-only and does not produce a stripped .dcm file. Use it before anonymisation to audit which PHI tags are present (Patient Name, Patient ID, Date of Birth, Referring Physician, Accession Number, Institution Name, Station Name and Device Serial are the usual suspects), then run a dedicated anonymiser like pydicom's anonymize example or DICOM Anonymizer Pro to produce the cleaned file.

Some DICOM files (especially structured reports or spectroscopy) have thousands of tags, and rendering all of them in a single table is unmanageable. The first 500 are extracted server-side, and the first 200 are returned for the on-page view — but the CSV download contains all 500 so you can grep the full dump for the specific tag you're looking for. For files with deeper tag trees, scripted pydicom is the way.

PHI warning: DICOM files often contain Protected Health Information (PHI). Files are parsed in memory and deleted immediately after the response. Still, for production PHI workflows, consider running this tool locally.

Upload a .dcm file

CT, MRI, X-ray, ultrasound, PET — any DICOM modality • Max 30MB

Requires login • 2 credits

DICOM Metadata Viewer Tutorial

What is DICOM?

DICOM (Digital Imaging and Communications in Medicine) is the standard for medical imaging. Every CT slice, MRI, X-ray, and ultrasound you see in hospitals is stored as a .dcm file. Each file bundles the image data with hundreds of metadata tags describing the patient, study, equipment, and acquisition parameters.

What You'll See

  • Modality — CT, MR, CR (X-ray), US (ultrasound), PT (PET), etc.
  • Patient info — ID, name, DOB, sex (often anonymized in teaching/research sets)
  • Study details — date, description, referring physician, accession number
  • Equipment — manufacturer, model, station, institution, software version
  • Image parameters — resolution, bit depth, slice thickness, pixel spacing
  • All tags — full dump of every non-pixel tag with its VR (Value Representation)

Why This Tool Exists

Installing a DICOM viewer just to check a file's metadata is overkill. Researchers, medical imaging engineers, radiology IT staff, and students often just need to see what's inside a .dcm file — where it came from, which machine, what modality. This tool does exactly that, no install, no 4GB software package.

Pixel Data

We deliberately do not decode or display pixel data — that would require a full imaging pipeline and is a different product. For viewing actual images, use RadiAnt, Mango, or OsiriX.

Tags Format

Each DICOM tag is a (group, element) hex pair: (0010,0010) is PatientName. The VR column shows data type: PN person name, DA date, UI unique identifier, IS integer string, etc.

Privacy

Files are parsed in RAM only. The temp file is deleted in the finally block. Nothing is persisted. Still — for clinical or research PHI, run this locally with pydicom directly.