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A Fully Automated Analytic System for Measuring Endolymphatic Hydrops Ratios in Patients With Ménière Disease via Magnetic Resonance Imaging: Deep Learning Model Development Study.

Chae Jung ParkYoung Sang ChoMyung Jin ChungYi Kyung KimHyung-Jin KimKyunga KimJae-Wook KoWon-Ho ChungBaek-Hwan Cho
Published in: Journal of medical Internet research (2021)
In this study, a fully automated full-stack magnetic resonance analysis system for measuring EH ratios was developed (named INHEARIT-v2), and the results showed that there was a high correlation between the expert-calculated EH ratio values and those calculated by the INHEARIT-v2 system. The system is an upgraded version of the INHEARIT system; it has higher segmentation performance and automatically selects representative images from an MRI stack. The new model can help clinicians by providing objective analysis results and reducing the workload for interpreting magnetic resonance images.
Keyphrases
  • deep learning
  • magnetic resonance
  • magnetic resonance imaging
  • convolutional neural network
  • contrast enhanced
  • artificial intelligence
  • machine learning
  • computed tomography
  • palliative care
  • clinical practice