The caBIG annotation and image Markup project

J Digit Imaging. 2010 Apr;23(2):217-25. doi: 10.1007/s10278-009-9193-9. Epub 2009 Mar 18.


Image annotation and markup are at the core of medical interpretation in both the clinical and the research setting. Digital medical images are managed with the DICOM standard format. While DICOM contains a large amount of meta-data about whom, where, and how the image was acquired, DICOM says little about the content or meaning of the pixel data. An image annotation is the explanatory or descriptive information about the pixel data of an image that is generated by a human or machine observer. An image markup is the graphical symbols placed over the image to depict an annotation. While DICOM is the standard for medical image acquisition, manipulation, transmission, storage, and display, there are no standards for image annotation and markup. Many systems expect annotation to be reported verbally, while markups are stored in graphical overlays or proprietary formats. This makes it difficult to extract and compute with both of them. The goal of the Annotation and Image Markup (AIM) project is to develop a mechanism, for modeling, capturing, and serializing image annotation and markup data that can be adopted as a standard by the medical imaging community. The AIM project produces both human- and machine-readable artifacts. This paper describes the AIM information model, schemas, software libraries, and tools so as to prepare researchers and developers for their use of AIM.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / organization & administration*
  • Computer Communication Networks / organization & administration*
  • Databases, Factual
  • Diagnostic Imaging / standards*
  • Diagnostic Imaging / trends
  • Humans
  • Interdisciplinary Communication
  • Medical Records Systems, Computerized
  • National Cancer Institute (U.S.)
  • National Institutes of Health (U.S.)
  • Neoplasms / diagnostic imaging
  • Program Evaluation
  • Quality of Health Care
  • Radiographic Image Enhancement / standards
  • Radiographic Image Enhancement / trends*
  • Radiology Information Systems / organization & administration*
  • Software
  • Systems Integration
  • United States
  • User-Computer Interface