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Radiological interpretation 2020: Toward quantitative image assessment
Author(s) -
Boone John M.
Publication year - 2007
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2789501
Subject(s) - sophistication , medical imaging , medical physics , quantitative assessment , health care , radiological weapon , computer science , medicine , artificial intelligence , risk analysis (engineering) , radiology , social science , sociology , economics , economic growth
The interpretation of medical images by radiologists is primarily and fundamentally a subjective activity, but there are a number of clinical applications such as tumor imaging where quantitative imaging (QI) metrics (such as tumor growth rate) would be valuable to the patient's care. It is predicted that the subjective interpretive environment of the past will, over the next decade, evolve toward the increased use of quantitative metrics for evaluating patient health from images. The increasing sophistication and resolution of modern tomographic scanners promote the development of meaningful quantitative end points, determined from images which are in turn produced using well‐controlled imaging protocols. For the QI environment to expand, medical physicists, physicians, other researchers and equipment vendors need to work collaboratively to develop the quantitative protocols for imaging, scanner calibrations, and robust analytical software that will lead to the routine inclusion of quantitative parameters in the diagnosis and therapeutic assessment of human health. Most importantly, quantitative metrics need to be developed which have genuine impact on patient diagnosis and welfare, and only then will QI techniques become integrated into the clinical environment.