Pinnock, Mark A;
Hu, Yipeng;
Bainbridge, Alan;
Atkinson, David;
Mookerjee, Rajeshwar P;
Taylor, Stuart A;
Barratt, Dean C;
(2021)
Deep learning-based detection of liver disease using MRI.
In: Block, Walter F and Jones, Derek K and Boiteaux,, Sonja K, (eds.)
ISMRM Annual Meeting Proceedings 2021.
(pp. p. 2988).
ISMRM: Concord, CA, USA.
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Abstract
Traditional approaches to MRI detection of liver disease require specialist hardware, sequences and post-processing. Here we propose a deep learning (DL) based model for the detection of liver disease using standard T2-weighted anatomical sequences, as an early feasibility study for the potential of DL-based classification of liver disease severity. Our DL model achieved a diagnostic accuracy of 0.92 on unseen data and achieved a test accuracy of 0.75 when trained with relevant anatomical segmentation masks without images, demonstrating potential scanner/sequence independence. Lastly, we used DL interpretability techniques to analyse failure cases.
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