Deep learning with ultrasonography: automated classification of liver fibrosis using a deep convolutional neural network
Abstract
The aim of this study was to develop a deep convolutional neural network (DCNN) for the prediction of the METAVIR score using B-mode ultrasonography images. Datasets from two tertiary academic referral centers were used. A total of 13,608 ultrasonography images from 3446 patients who underwent surgical resection, biopsy, or transient elastography were used for training a DCNN for the prediction of the METAVIR score. Pathological specimens or...
Paper Details
Title
Deep learning with ultrasonography: automated classification of liver fibrosis using a deep convolutional neural network
Published Date
Sep 2, 2019
Journal
Volume
30
Issue
2
Pages
1264 - 1273
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