A task-based approach to adaptive and multimodality imaging

Eric Clarkson, Matthew A. Kupinski, Harrison H. Barrett, Lars Furenlid

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


Multimodality imaging is becoming increasingly important in medical imaging. Since the motivation for combining multiple imaging modalities is generally to improve diagnostic or prognostic accuracy, the benefits of multimodality imaging cannot be assessed through the display of example images. Instead, we must use objective, task-based measures of image quality to draw valid conclusions about system performance. In this paper, we will present a general framework for utilizing objective, task-based measures of image quality in assessing multimodality and adaptive imaging systems. We introduce a classification scheme for multimodality and adaptive imaging systems and provide a mathematical description of the imaging chain along with block diagrams to provide a visual illustration. We show that the task-based methodology developed for evaluating single-modality imaging can be applied, with minor modifications, to multimodality and adaptive imaging. We discuss strategies for practical implementing of task-based methods to assess and optimize multimodality imaging systems.

Original languageEnglish (US)
Article number4446232
Pages (from-to)500-511
Number of pages12
JournalProceedings of the IEEE
Issue number3
StatePublished - Mar 2008


  • Adaptive imaging
  • Image quality
  • Multimodality

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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