Neuroimaging feature terminology: A controlled terminology for the annotation of brain imaging features

Anandhi Iyappan, Erfan Younesi, Alberto Redolfi, Henri Vrooman, Shashank Khanna, Giovanni B. Frisoni, Martin Hofmann-Apitius

Research output: Contribution to journalArticlepeer-review


Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

Original languageEnglish
Pages (from-to)1153-1169
Number of pages17
JournalJournal of Alzheimer's Disease
Issue number4
Publication statusPublished - Jan 1 2017


  • Alzheimer's disease
  • annotation
  • brain
  • neuroimaging
  • terminology

ASJC Scopus subject areas

  • Clinical Psychology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health


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