Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges

Published in IEEE International Symposium on Biomedical Imaging (ISBI), 2020

First authored paper accepted to the IEEE International Symposium on Biomedical Imaging (ISBI’20).

MRI, an extremely expensive imaging modality, often suffers from a high degree of motion artifacting, which nececitates the need for some automated detection mechanism to avoid the inefficient use of high-cost radiologist labor to filter images. In this paper, we explore several convolutional neural network-based frameworks for medical image quality assessment and investigate several challenges therein.

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Recommended citation:

J. J. Ma et al., “Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges,” 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, USA, 2020, pp. 337-340, doi: 10.1109/ISBI45749.2020.9098735.