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Imaging informatics

Imaging informatics is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Imaging informatics rather than just read about it. In short: Imaging informatics, also known as radiology informatics or medical imaging informatics, is a subspecialty of biomedical informatics that aims to improve the efficiency, accuracy, usability and reliability of medical imaging services within the healthcare enterprise. It is devoted to the study of how information about and contained within medical images is retrieved, analyzed, enhanced, and exchanged throughout the…

Imaging informatics — main illustration
Imaging informatics — illustration

Key takeaways

  • Imaging informatics belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Imaging informatics to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Imaging informatics from memory before moving on to harder problems.

Reference excerpt

Imaging informatics, also known as radiology informatics or medical imaging informatics, is a subspecialty of biomedical informatics that aims to improve the efficiency, accuracy, usability and reliability of medical imaging services within the healthcare enterprise. It is devoted to the study of how information about and contained within medical images is retrieved, analyzed, enhanced, and exchanged throughout the medical enterprise. As radiology is an inherently data-intensive and technology-driven specialty, those in this branch of medicine have become leaders in Imaging Informatics. However, with the proliferation of digitized images across the practice of medicine to include fields such as cardiology, ophthalmology, dermatology, surgery, gastroenterology, obstetrics, gynecology and pathology, the advances in Imaging Informatics are also being tested and applied in other areas of medicine. Various industry players and vendors involved with medical imaging, along with IT experts and other biomedical informatics professionals, are contributing and getting involved in this expanding field. Imaging informatics exists at the intersection of several broad fields:

biological science – includes bench sciences such as biochemistry, microbiology, physiology and genetics clinical services – includes the practice of medicine, bedside research, including outcomes and cost-effectiveness studies, and public health policy information science – deals with the acquisition, retrieval, cataloging, and archiving of information medical physics / biomedical engineering – entails the use of equipment and technology for a medical purpose cognitive science – studying human computer interactions, usability, and information visualization computer science – studying the use of computer algorithms for applications such as computer assisted diagnosis and computer vision Due to the diversity of the industry players and broad professional fields involved with Imaging Informatics, there grew a demand for new standards and protocols. These include DICOM (Digital Imaging and Communications in Medicine), Health Level 7 (HL7), International Organization for Standardization (ISO), and Artificial Intelligence protocols. Current research surrounding Imaging Informatics has a focus on Artificial Intelligence (AI) and Machine Learning (ML). These new technologies are being used to develop automation methods, disease classification, advanced visualization techniques, and improvements in diagnostic accuracy. However, AI and ML integration faces several challenges with data management and security.

History

Medical imaging to imaging informatics

While the field of imaging informatics is based around the power of modern computing, its roots trace back to the dawn of the 20th century. On November 8, 1895, German physicist Wilhelm Conrad Röntgen observed a new imaging technique he coined "X-rays" during his experiments. This discovery led to the creation of the medical imaging field, and in turn launched a new wave of human innovation. X-rays stood as the only medical imaging technology for several decades following its discovery. However, the arrival of the mid 20th century meant the expansion of the medical imaging field. The new modalities included: computed tomography (CT) to visualize soft tissue with a high degree of resolution; Magnetic Resonance Imaging (MRI) which is a modern standard for soft tissue imaging; Ultrasound that uses sound waves to create less expensive visualizations; Nuclear Imaging and Hybrid Scanners for functional imaging and imaging with higher spatial resolution created by combining multiple modalities. As these imaging techniques became more sophisticated, the amount of information that medical imaging professionals were expected to process also increased. Additionally, the digital revolution of the mid to late 20th century further increased the data these techniques could gather. As a result, the main limiting factor for the medical imaging field became the human inability to accurately interpret large amounts of data. Thus, the need arose for computerized assistance with complex digital imaging analysis, storage and manipulation. Modern Imaging Informatics was developed to fulfill these needs.

Imaging informatics development Imaging Informatics is a broad field with numerous areas of interest, making its development a culmination of the development of various individual technologies. Several of the key innovations for the field are as follows:

Picture archiving and communication system (PACS)

The development of PACS popularized the use of image storage and retrieval systems in medical practices. Moreover, this new technology demanded the development of others. The world quickly realized that digital imaging standards would need to be put in place given the impact PACS had on the medical community. The American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) created the Digital Imaging and Communications Standards Committee (later becoming DICOM) in response to this concern.

Information technology integration The digital age's impact on radiology resulted in a large influx of data that needed to be managed. To combat this, the field of information technology was incorporated with technology such as Radiology Information System (RIS) and Hospital Information System (HIS). These systems would work in tandem with PACS and other imaging technology to streamline the patient data management, as shown in the figure to the right.

… excerpt ends here. Continue reading the full article.

Illustrations

Imaging informatics: Overview of a PACS system and a visualization of its interactions with the RIS and DICOM.
Overview of a PACS system and a visualization of its interactions with the RIS and DICOM.
Imaging informatics: DICOM InfoModel
DICOM InfoModel
Imaging informatics: HL7 Reference Information Model
HL7 Reference Information Model
Imaging informatics: FHIR resource graph
FHIR resource graph
Imaging informatics: Clinical decision support system for quantitative analysis of whole-slide images.
Clinical decision support system for quantitative analysis of whole-slide images.

Worked examples

Example 1 — a first encounter with Imaging informatics

Start with the simplest possible case. Write down what Imaging informatics claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Imaging informatics before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Imaging informatics ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Imaging informatics

In research
Imaging informatics appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Imaging informatics in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Imaging informatics is common in secondary-school and first-year university syllabi. It links to neighbouring topics Bioinformatics, Computing in medical imaging, so understanding it makes those chapters shorter.
In everyday life
Look for Imaging informatics outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Imaging informatics in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Imaging informatics means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Imaging informatics out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Imaging informatics in simple terms?

Imaging informatics, also known as radiology informatics or medical imaging informatics, is a subspecialty of biomedical informatics that aims to improve the efficiency, accuracy, usability and reliability of medical imaging services within the healthcare enterprise. It is devoted to the study of h…

Why does Imaging informatics matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Imaging informatics?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Imaging informatics.

Tags

  • Bioinformatics
  • Computing in medical imaging

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