Precision Imaging: more descriptive, predictive and integrative imaging

Frangi, A.F., Taylor, Z.A. and Gooya, A. (2016) Precision Imaging: more descriptive, predictive and integrative imaging. Medical Image Analysis, 33, pp. 27-32. (doi: 10.1016/j.media.2016.06.024) (PMID:27373145)

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Abstract

Medical image analysis has grown into a matured field challenged by progress made across all medical imaging technologies and more recent breakthroughs in biological imaging. The cross-fertilisation between medical image analysis, biomedical imaging physics and technology, and domain knowledge from medicine and biology has spurred a truly interdisciplinary effort that stretched outside the original boundaries of the disciplines that gave birth to this field and created stimulating and enriching synergies. Consideration on how the field has evolved and the experience of the work carried out over the last 15 years in our centre, has led us to envision a future emphasis of medical imaging in Precision Imaging. Precision Imaging is not a new discipline but rather a distinct emphasis in medical imaging borne at the cross-roads between, and unifying the efforts behind mechanistic and phenomenological model-based imaging. It captures three main directions in the effort to deal with the information deluge in imaging sciences, and thus achieve wisdom from data, information, and knowledge. Precision Imaging is finally characterised by being descriptive, predictive and integrative about the imaged object. This paper provides a brief and personal perspective on how the field has evolved, summarises and formalises our vision of Precision Imaging for Precision Medicine, and highlights some connections with past research and current trends in the field.

Item Type:Articles
Additional Information:We acknowledge continued funding from the European Commission (FP7-ICT-2011-9-601055, FP7-ICT-2011-9-600932), EPSRC (EP/M006328/1, EP/N026993/1, EP/N027078/1, EP/M013014/1), and BBSRC (BB/M01021X/1).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Gooya, Dr Ali
Authors: Frangi, A.F., Taylor, Z.A., and Gooya, A.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Medical Image Analysis
Publisher:Elsevier
ISSN:1361-8415
Published Online:16 August 2016

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