View, search, and compare DICOM tags and metadata from medical imaging files online for free. No registration needed.
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Supports .dcm, .dicom, .ima (max 100MB per file, 10 files max)
Processing DICOM files...
Upload one or two DICOM (.dcm) files using the file selector or drag-and-drop.
Browse tags by category or search by tag ID, keyword, or VR type.
Compare two files side by side and export the tag list to CSV.
Recognizes thousands of standard DICOM tags with their names, VR types, and decoded values.
Upload two DICOM files and instantly see which tags match, differ, or are missing.
All tag extraction runs locally in your browser — no medical data is sent to external servers.
Every DICOM file you open is parsed entirely within your browser using JavaScript. No pixel data, patient demographics, or study metadata ever leaves your machine. This architecture eliminates the risk of accidental PHI disclosure over the network, making it safe to use on hospital workstations and VPN-connected laptops alike.
Open the tool and start working immediately. There are no account sign-ups, license keys, or desktop installers to manage. IT departments can approve access without procurement cycles, and traveling consultants can use it from any modern browser without requesting admin privileges on loaner hardware.
The viewer understands thousands of standard and private DICOM tags, displays Value Representations correctly, and groups tags by category. Whether you are verifying a PACS migration, auditing de-identification results, or debugging a modality worklist issue, the interface is designed for the questions healthcare IT professionals actually ask.
Because processing is local, you maintain full custody of Protected Health Information at all times. There is no cloud storage, no temporary server cache, and no third-party analytics that could touch patient data. This supports compliance with HIPAA, GDPR, and institutional data-governance policies without additional BAAs or risk assessments.
DICOM (Digital Imaging and Communications in Medicine) is the universal standard for storing, transmitting, and displaying medical images. Maintained by the National Electrical Manufacturers Association (NEMA), the standard defines both a file format and a network protocol. Every CT scanner, MRI system, ultrasound unit, and PACS archive speaks DICOM, making it the lingua franca of radiology and medical imaging departments worldwide.
A DICOM file is essentially a collection of tags — structured key-value pairs identified by a group and element number (e.g., (0010,0010) for Patient Name). Each tag carries a Value Representation (VR) that defines its data type — short string, date, unique identifier, sequence, and so on. Tags are organized hierarchically: patient-level, study-level, series-level, and instance-level, reflecting the real-world relationships between patients, exams, and individual images.
Standard tags are defined in the DICOM Data Dictionary published in Part 6 of the standard. In addition, manufacturers may embed private tags using odd group numbers to store proprietary information such as reconstruction parameters or dose metrics.
One of the most powerful features is the ability to load two DICOM files and compare their tags simultaneously. The tool highlights matching values, differing values, and tags that exist in one file but not the other. This is invaluable during system upgrades, data migrations, and cross-vendor interoperability testing where subtle tag differences can cause downstream failures in routing rules, hanging protocols, or display algorithms.
Every DICOM tag carries a Value Representation that tells parsers how to interpret the stored bytes. Common VRs include LO (Long String) for text up to 64 characters, DA (Date) formatted as YYYYMMDD, UI (Unique Identifier) for DICOM UIDs, and SQ (Sequence) for nested data structures. A robust tag viewer decodes each VR correctly — displaying dates in human-readable form, resolving UIDs where possible, and letting you expand sequences to inspect their child items. Misinterpreting VR types is a frequent source of integration errors, particularly when implicit VR transfer syntaxes omit the VR field and the parser must infer the type from the data dictionary.
DICOM files declare a transfer syntax in the meta header that defines the byte ordering (little-endian or big-endian) and whether pixel data is compressed. The most common transfer syntax is Explicit VR Little Endian (1.2.840.10008.1.2.1), used by the vast majority of modern scanners. Older equipment may produce Implicit VR Little Endian files where the VR must be looked up from the data dictionary. Compressed syntaxes such as JPEG Baseline, JPEG 2000, and JPEG-LS reduce file sizes but require codec support for pixel rendering. A tag viewer focuses on metadata rather than pixel data, so it can parse tags from any transfer syntax even when the corresponding image codec is unavailable. Understanding which transfer syntax a file uses is essential when troubleshooting image display failures — the transfer syntax UID in tag (0002,0010) tells you exactly how the data is encoded.
Medical imaging files routinely contain PHI — patient names, dates of birth, medical record numbers, and even burned-in annotations on pixel data. Using a cloud-based viewer introduces transmission and storage risks. Our browser-based approach processes files entirely on your local device, so PHI never traverses the network. This design supports HIPAA Security Rule requirements for access controls and transmission security without needing a Business Associate Agreement with a third-party service.
The tool processes all files locally in your browser. No DICOM data, patient demographics, or pixel information is uploaded to any server. Because PHI never leaves your device, the tool supports HIPAA-compliant workflows without requiring a Business Associate Agreement.
The viewer handles standard Part 10 DICOM files (.dcm) with explicit and implicit VR encodings in little-endian and big-endian byte orders. It parses the preamble, meta header, and dataset tags. Encapsulated pixel data tags are recognized but not rendered as images.
Yes. Private tags with odd group numbers are displayed with their raw group/element identifiers and values. If the tag is not in the standard data dictionary, it is labeled as a private tag so you can distinguish it from standard attributes.
Upload two DICOM files and the viewer aligns tags by their group/element number. Matching values are shown normally, differing values are highlighted, and tags present in only one file are flagged. This makes it easy to spot changes during migrations or de-identification.
Yes. You can export the full tag list for one or both files to CSV format. The export includes tag number, name, VR, value, and comparison status when two files are loaded, making it easy to share results with colleagues or archive them for audit trails.
Yes. Sequence (SQ) tags are parsed recursively so you can expand and inspect nested items. This is important for structured reports, dose reports, and presentation states that rely heavily on sequence-based data organization.
The viewer works in all modern browsers including Chrome, Firefox, Safari, and Edge. It requires JavaScript to be enabled. Because processing is local, performance depends on your device — most machines handle typical clinical DICOM files without any lag.
There is no hard limit enforced by the tool. However, because the file is loaded into browser memory, very large files (above 500 MB) may be slow on devices with limited RAM. For typical clinical images in the 10–100 MB range, performance is excellent.
Yes. Since no data leaves the browser, the tool can be used on hospital workstations, Citrix sessions, and VPN-connected laptops without opening additional firewall ports or routing PHI through external services.
The built-in dictionary covers thousands of tags from the current DICOM standard (PS3.6). It includes patient, study, series, and instance-level attributes as well as common modality-specific tags. The dictionary is updated periodically to reflect new supplement additions.
Learn how to safely remove Protected Health Information from DICOM files for research sharing. Covers tag-level PHI, burned-in annotations, and audit workflows.
Read more →Step-by-step PACS migration checklist for validating DICOM data integrity. Learn to catch tag corruption, UID mismatches, and encoding errors.
Read more →Complete reference guide to DICOM tags for radiology IT professionals. Covers tag groups, Value Representations, private tags, and common use cases.
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