What Is DICOM Data Structure?
The DICOM (Digital Imaging and Communications in Medicine) data structure is a standard format used in the medical field for storing and transmitting medical images and related information. It is widely adopted and supported by healthcare organizations, software developers, and medical device manufacturers.
DICOM is a comprehensive standard that defines how medical images, such as X-rays, CT scans, MRI scans, and ultrasound images, should be organized and exchanged between different systems. It ensures interoperability and allows healthcare professionals to access patient data across different imaging devices and software platforms.
The DICOM data structure consists of a set of rules that specify how information should be represented, stored, transmitted, and displayed. It includes various elements such as patient demographics, study information, image acquisition parameters, image pixel data, annotations, and more.
Key Features of DICOM
- DICOM enables seamless exchange of medical images between different systems regardless of the vendor or manufacturer.
- It ensures that imaging devices produce standardized output that can be easily interpreted by any DICOM-compliant software.
- DICOM ensures the integrity of medical data through mechanisms like digital signatures for authentication and encryption for secure transmission.
- It provides methods to verify the consistency of the acquired image data to minimize errors or discrepancies.
Storage and Querying:
- DICOM supports various storage media such as hard drives, CDs/DVDs, PACS (Picture Archiving and Communication Systems), etc., allowing for efficient and long-term storage of medical images.
- It provides a standardized query and retrieval mechanism, allowing healthcare professionals to access specific patient records or image datasets quickly.
DICOM Data Structure
The DICOM data structure is based on a hierarchical model with multiple levels of information. It starts with a patient level, which contains demographics, such as the patient’s name, age, gender, and medical record number.
Next is the study level, which represents a specific imaging study conducted on the patient. It includes details like the study description, study date and time, referring physician’s name, etc.
The series level represents a collection of related images acquired during a single imaging session. Each series has unique attributes such as modality (e.g., CT, MRI), body part examined (e., head, abdomen), and image orientation.
Finally, at the image level, individual images are stored along with their associated metadata. This includes information like image dimensions, pixel spacing, image position, windowing settings for display purposes, and more.
DICOM File Format
DICOM files typically have a “.dcm” extension and consist of two main parts: the header and the pixel data. The header contains metadata in a structured format following DICOM specifications. It includes tags that uniquely identify each data element along with its value representation (VR) and value length (VL).
The pixel data section stores the actual image pixel values using various compression techniques like lossless JPEG or JPEG 2000 to minimize storage requirements while preserving image quality.
To ensure compliance with the DICOM standard, software applications and imaging devices undergo conformance testing. This involves testing the implementation against a set of predefined criteria to verify that it correctly handles DICOM data and adheres to the standard protocols.
Conformance testing helps guarantee interoperability, data integrity, and consistency across different systems, ensuring that medical images can be accurately exchanged and interpreted by healthcare professionals.
The DICOM data structure is a vital component of modern healthcare systems, enabling seamless exchange and storage of medical images. Its standardized format ensures interoperability, data integrity, and efficient querying capabilities. Understanding the DICOM data structure is crucial for software developers, healthcare professionals, and anyone involved in medical image management.