A Comprehensive Guide to DICOM and How It Has Shaped Modern Medical Imaging
The DICOM standard has been the de facto representation of nearly all medical images created since the 1990s, enhancing the storage and communication of medical data between hospitals, manufacturers, researchers, software vendors, and patients.
In this guide, we will explore the characteristics that put DICOM at the center of the medical imaging industry, and how it is growing even more importantly in the age of artificial intelligence.
What is DICOM?
DICOM stands for Digital Imaging and Communications in Medicine, a set of standards for international file formats used in transmitting medical images. Designed by the American College of Radiology (ACR) and the National Electrical Manufacturer’s Association (NEMA), DICOM establishes rules governing the interoperability of information of medical imaging devices from different vendors. Currently, all modern medical imaging equipment produces images in this format. Thus, doctors must use DICOM viewers and computer software programs compatible with DICOM pictures to diagnose findings from the images.
Breaking down a DICOM File
The special thing about DICOM files is that their content is more than just images. In fact, a DICOM image also contains patient attributes such as demographics and hospital information. This collection is possible thanks to the internal structure of a DICOM image, which consists of a 128-byte preamble, the prefix “DICM”, a header, and medical image metadata. The header is organized as a standardized set of tags, so extracting data from these tags will allow access to patient information and study parameters.
How DICOM Has Transformed Medical Imaging
Before DICOM, different proprietary image formats and communications protocols existed concurrently, hence integrating medical hardware and software required constant switching from one manufacturer’s protocols to another’s. Even with data translation services, this process was still chaotic and fraught with errors. The introduction of DICOM has revolutionized communication protocols and reduced the cost and complexity involved in medical hardware and software integration in 3 primary ways.
Universal Compatibility
DICOM is a universal standard that ensures compatibility across different types of medical imaging equipment and software. The chaotic data translation processes are no longer issues as medical device manufacturers must conform to a common standard. Consequently, DICOM enables the interoperability of systems in managing clinical workflows as well as producing, storing, sharing, displaying, and processing medical images. Medical experts can exchange medical imaging files in DICOM format across the world and between any devices without losing any important information or compromising image quality. This is highly efficient and cost-effective since healthcare providers no longer have to purchase specialized software or equipment for each type of medical image.
Metadata Integration
DICOM includes metadata that describes important information about the imaging study, such as patient information, imaging modality, and acquisition parameters. This metadata is critical for accurate diagnosis and treatment planning. For example, a radiologist needs to know the patient’s age and gender to help determine the likelihood of certain diseases, and the imaging modality and acquisition parameters can affect the quality and interpretation of the image. The metadata also ensures that the image can be properly indexed and retrieved in a medical image archive.
Medical Information Confidentiality
Metadata integration can be both an advantage and a concern for the adoption of DICOM in clinical settings. Medical images may be used for many legal secondary purposes, such as research projects, teaching, or the development of medical smart systems.
DICOM includes security features that protect patient data and ensure that only authorized individuals can access the images. In the case that personal data is required for reasonable research purposes, DICOM provides irreversible anonymization so that the data subject becomes unidentifiable by the data controller or any other party. Other security features include access control, data encryption, and secure transmission protocols, which serve to strictly enforce the de-identification of patient information. This helps to ensure patient privacy and confidentiality, and to comply with regulations such as HIPAA (Health Insurance Portability and Accountability Act).
The Future of DICOM Images
Unlock the Potential of DICOM with Artificial Intelligence
DICOM has revolutionized medical imaging, and will continue to do so. DICOM images use a 16-bit color profile, which displays up to 65,000 values per color — a mounting improvement compared to just 250 values in traditional greyscale images. Therefore, the recently growing demand for recognizing complex anatomical structures in medical images will only elevate the importance of DICOM in the healthcare sector. One of the most revolutionary improvements in modern-day medicine has been the application of artificial intelligence (AI) to analyze medical images for diagnostic purposes. As exciting as it sounds, this new field relies on labeling and annotating medical images to create high-quality data that these medical machine learning models train on.
Medical Labeling on DICOM Images
If you are unclear about what image labeling is, we have an entire blog dedicated to explaining its definition and subdivisions. In short, medical data labeling is the process of annotating medical data in such forms as CT scans, X-rays, MRIs, or ultrasounds. This annotated data is then used to train machine learning models, which can automatically detect the (once trained) labels in unseen images. One recommended practice to achieve high model accuracy is to use the DICOM format. The pixel-precise display of DICOM means that the machine learning models will get the most information out of medical data without losing bits along the workflow. Moreover, as all medical devices in hospitals and research centers must conform to DICOM standards, this approach will make sure the newly developed AI can fit into existing clinical information systems.
Overall, the landscape for DICOM and medical image labeling is still bristling with potential as researchers around the globe work tirelessly to develop new AI solutions and help professionals diagnose patients faster, more easily, and accurately.
See the newest advancements in the joint world of medicine and AI in this blog post.
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