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Biomedical image analysis challenges should be considered as an academic exercise, not an instrument that will move the field forward in a real, practical way
Author(s) -
Armato Samuel G.,
Farahani Keyvan,
Zaidi Habib
Publication year - 2020
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 - 10.1002/mp.14081
Subject(s) - field (mathematics) , medical imaging , medical physics , computer science , data science , medicine , artificial intelligence , mathematics , pure mathematics
The biomedical imaging community has witnessed innovative algorithmic developments in quantitative imaging biomarkers taking advantage of modern multimodality imaging technologies. These developments encompass a wide methodological portfolio including but not limited to image registration, segmentation, classification, and prediction. Despite the enormous progress in technical developments, including rigorous peer-review preceding publication in the scientific literature, extensive testing, and feedback from users of the associated open-source software tools, validation of these advanced image analysis tools prior to their deployment in the clinic is still one of the main challenges faced by developers and end-users.