Healthcare IT Glossary

What is DICOM?
Digital Imaging Communications

Every medical image — every X-ray, CT scan, MRI, ultrasound, and mammogram — needs to move between the machine that captured it, the system that stores it, and the workstation where a radiologist reads it. DICOM is the standard that makes all of this work, defining how medical images are formatted, stored, transmitted, and displayed regardless of who manufactured the equipment.

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Definition of DICOM

DICOM, which stands for Digital Imaging and Communications in Medicine, is the international standard for handling, storing, printing, and transmitting medical imaging information. It defines both a file format for medical images and a network communication protocol for exchanging those images between systems.

DICOM is developed and maintained by the DICOM Standards Committee, a joint effort of the National Electrical Manufacturers Association (NEMA) and medical imaging industry stakeholders. The standard has been in continuous development since 1985 and is now in its current form as DICOM 3.0 (often just called “DICOM”).

A DICOM file is more than just an image. Each file contains the pixel data (the actual image) plus a rich set of metadata — patient name, medical record number, study date, modality type (CT, MR, US, etc.), body part examined, institution name, referring physician, and acquisition parameters. This metadata travels with the image, ensuring the clinical context is never separated from the pixels.

DICOM supports virtually all medical imaging modalities: computed tomography (CT), magnetic resonance imaging (MRI), X-ray/radiography, ultrasound, nuclear medicine, PET, mammography, endoscopy, ophthalmology, and digital pathology. It also handles structured reports, waveforms (ECG), radiation therapy objects, and 3D surface meshes.

In simple terms: DICOM is the universal language for medical images — the standard that ensures an MRI taken on a GE scanner can be stored in any PACS, viewed on any workstation, and shared with any hospital.

How DICOM Works in Healthcare

DICOM operates across the entire medical imaging workflow — from image acquisition through storage, distribution, display, and exchange.

Image acquisition
When a patient undergoes a CT scan, MRI, or X-ray, the imaging modality (the machine) generates DICOM objects. Each image or series of images is packaged as a DICOM file with embedded patient demographics, study information, and technical acquisition parameters. The modality sends these DICOM objects to the designated storage destination using the DICOM C-STORE network service.
Image storage in PACS
The images arrive at the Picture Archiving and Communication System (PACS), which is the central archive for all medical images in a healthcare organization. PACS receives, indexes, and stores DICOM objects, making them retrievable by study, patient, date, modality, or body part. PACS is to medical imaging what the EHR is to clinical documentation — the system of record.
Worklist management
Before a study is performed, the Radiology Information System (RIS) sends a DICOM Modality Worklist to the imaging modality. This pre-populates the machine with the patient’s demographics and order details, reducing manual entry errors and ensuring the acquired images are correctly linked to the right patient and order.
Image display and interpretation
Radiologists and clinicians view DICOM images on diagnostic workstations using DICOM-compliant viewers. These viewers must support DICOM presentation states — window/level settings, annotations, measurements, and display protocols — to render images correctly for clinical interpretation.
Image exchange and teleradiology
DICOM enables image sharing between facilities for second opinions, subspecialty reads, and teleradiology services. Images can be transmitted using DICOM network services (C-MOVE, C-GET), exported to DICOM media (CD/DVD), or increasingly exchanged via DICOMweb — the HTTP-based API that enables web and mobile imaging access.
Integration with EHR
DICOM images are linked to the patient’s electronic health record through order-based workflows. The EHR places an imaging order, the RIS schedules it, the modality performs the study, PACS stores the images, and the radiology report is delivered back to the EHR — typically as an HL7 ORU message or, increasingly, a FHIR DiagnosticReport resource.

Key DICOM Standards and Specifications

These services operate over TCP/IP connections using DICOM’s Association protocol, which negotiates transfer syntaxes and service capabilities between two systems (called SCU and SCP — Service Class User and Service Class Provider).

Legacy
DICOM Information Object Definitions (IODs)
DICOM defines Information Object Definitions for each type of medical data — CT Image IOD, MR Image IOD, Ultrasound Image IOD, Structured Report IOD, and dozens more. Each IOD specifies the required and optional metadata attributes and the pixel data encoding for that modality. Conformance to the correct IOD is what ensures interoperability between vendors.
Legacy
DICOM Network Services (DIMSE)
DICOM defines a set of network services called DIMSE (DICOM Message Service Element) for exchanging data between systems:
Modern
DICOMweb
DICOMweb is the modern HTTP/RESTful interface for DICOM services. It defines three primary web services: WADO-RS (retrieve images via HTTP), STOW-RS (store images via HTTP POST), and QIDO-RS (search for studies/series/instances via HTTP GET). DICOMweb enables browser-based viewers, mobile health applications, and cloud-based imaging platforms to access DICOM data without traditional DIMSE networking.
Legacy
IHE Imaging Profiles
The Integrating the Healthcare Enterprise (IHE) organization publishes imaging integration profiles that specify how DICOM services should be used in real-world workflows. Key profiles include Scheduled Workflow (SWF) for order-based imaging, Cross-Enterprise Document Sharing for Imaging (XDS-I) for image exchange between organizations, and Web-based Image Access (WIA) for browser-based viewing.
Legacy
DICOM and AI
DICOM is increasingly important for AI in clinical imaging. AI algorithms consume DICOM images as input, and their results — detected findings, measurements, segmentation masks — can be stored back as DICOM Structured Reports or DICOM Secondary Capture objects. The DICOM standard includes specific IODs for AI-generated annotations and findings.
C-STORESend images from one system to another (modality to PACS, PACS to workstation)
C-FINDQuery a DICOM archive for studies matching search criteria
C-MOVERequest a DICOM archive to send images to a specified destination
C-GETRetrieve images directly from an archive
N-CREATE/N-SETManage worklists and status information
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Implementation Considerations

DICOM implementation spans imaging infrastructure, network architecture, vendor integration, and regulatory compliance.

HIPAA compliance for imaging. DICOM images contain PHI — patient names, dates of birth, medical record numbers — embedded in the file metadata. All DICOM storage, transmission, and access must comply with HIPAA Security Rule requirements. De-identification of DICOM metadata is required when images are used for research, AI training, or shared with non-covered entities.

Vendor conformance statements are essential
Every DICOM device (modality, PACS, viewer, router) publishes a DICOM Conformance Statement that documents which IODs, transfer syntaxes, and network services it supports. Before integrating any imaging system, review its conformance statement to identify compatibility gaps. Two systems that both “support DICOM” may not interoperate if they support different transfer syntaxes or IOD versions.
Transfer syntax negotiation
DICOM supports multiple ways to encode image data — uncompressed, JPEG, JPEG 2000, JPEG-LS, and RLE (Run Length Encoding). During connection setup, the two systems negotiate which transfer syntax to use. Mismatched transfer syntax support is one of the most common DICOM interoperability failures. Your integration architecture should include a DICOM router or gateway that can transcode between formats when needed.
PACS migration and data conversion
Migrating between PACS vendors requires exporting and re-importing millions of DICOM objects. Data integrity must be verified — every image must survive the migration with metadata intact. Patient identity reconciliation across systems — handled through the Master Patient Index — is critical to prevent images from being orphaned or misattributed.
Image data volumes
Medical imaging generates massive data volumes. A single CT study can be 500MB+. An MRI study can exceed 1GB. Organizations need storage infrastructure and network bandwidth designed for imaging workloads. Cloud-based PACS solutions are increasingly common, but require careful bandwidth planning for upload/download of large studies.
Radiation dose tracking
DICOM includes structured reports for radiation dose (DICOM Radiation Dose SR). Regulatory requirements in many jurisdictions mandate dose tracking and reporting for CT and fluoroscopy. Your imaging infrastructure should capture and archive dose reports automatically.

How Taction Helps with DICOM

At Taction, our imaging integration team builds DICOM connectivity, PACS integration, and medical imaging solutions for healthcare organizations and health IT vendors.

What we do:

Whether you’re connecting imaging equipment, building a cloud-based viewer, or integrating AI into radiology workflows, our healthcare software team delivers imaging integration with DICOM precision.

DICOM interface development
We build custom DICOM interfaces connecting imaging modalities, PACS, viewers, and clinical applications — handling C-STORE, C-FIND, C-MOVE, and worklist management across multi-vendor environments.
DICOMweb API development
We build RESTful DICOMweb services (WADO-RS, STOW-RS, QIDO-RS) for browser-based imaging access, telemedicine platforms, and mobile imaging applications.
PACS integration and migration
We integrate PACS with EHR, RIS, and clinical systems, and manage PACS-to-PACS migrations ensuring data integrity, metadata preservation, and patient identity reconciliation.
AI imaging pipeline integration
We build pipelines that route DICOM images to AI models for analysis and store AI-generated findings back as DICOM Structured Reports — connecting imaging AI to clinical workflows.
DICOM de-identification
We build automated HIPAA-compliant de-identification pipelines for DICOM images used in research, AI training, and data sharing — stripping PHI from metadata while preserving clinical utility.

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