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Review

Explainable Deep Learning Models in Medical Image Analysis

1
Theoretical and Experimental Epistemology Laboratory, School of Optometry and Vision Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada
2
Department of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
*
Author to whom correspondence should be addressed.
J. Imaging 2020, 6(6), 52; https://doi.org/10.3390/jimaging6060052
Received: 28 May 2020 / Revised: 16 June 2020 / Accepted: 17 June 2020 / Published: 20 June 2020
(This article belongs to the Special Issue Deep Learning in Medical Image Analysis)
Deep learning methods have been very effective for a variety of medical diagnostic tasks and have even outperformed human experts on some of those. However, the black-box nature of the algorithms has restricted their clinical use. Recent explainability studies aim to show the features that influence the decision of a model the most. The majority of literature reviews of this area have focused on taxonomy, ethics, and the need for explanations. A review of the current applications of explainable deep learning for different medical imaging tasks is presented here. The various approaches, challenges for clinical deployment, and the areas requiring further research are discussed here from a practical standpoint of a deep learning researcher designing a system for the clinical end-users. View Full-Text
Keywords: explainability; explainable AI; XAI; deep learning; medical imaging; diagnosis explainability; explainable AI; XAI; deep learning; medical imaging; diagnosis
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MDPI and ACS Style

Singh, A.; Sengupta, S.; Lakshminarayanan, V. Explainable Deep Learning Models in Medical Image Analysis. J. Imaging 2020, 6, 52. https://doi.org/10.3390/jimaging6060052

AMA Style

Singh A, Sengupta S, Lakshminarayanan V. Explainable Deep Learning Models in Medical Image Analysis. Journal of Imaging. 2020; 6(6):52. https://doi.org/10.3390/jimaging6060052

Chicago/Turabian Style

Singh, Amitojdeep; Sengupta, Sourya; Lakshminarayanan, Vasudevan. 2020. "Explainable Deep Learning Models in Medical Image Analysis" J. Imaging 6, no. 6: 52. https://doi.org/10.3390/jimaging6060052

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