Convolutional Neural Networks to Detect Vestibular Schwannomas on Single MRI Slices: A Feasibility Study

Convolutional Neural Networks to Detect Vestibular Schwannomas on Single MRI Slices: A Feasibility Study

In this study. we aimed to detect vestibular schwannomas (VSs) in individual magnetic resonance imaging (MRI) slices by using a 2D-CNN. A pretrained CNN (ResNet-34) was retrained and internally validated using contrast-enhanced T1-weighted (T1c) MRI slices from one institution. In a second step, the...

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Bibliographic Details
Main Authors: Carole Koechli, Erwin Vu, Philipp Sager, Lukas Näf, Tim Fischer, Paul M. Putora, Felix Ehret, Christoph Fürweger, Christina Schröder, Robert Förster, Daniel R. Zwahlen, Alexander Muacevic, Paul Windisch
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Cancers
Subjects:
artificial intelligence
deep learning
machine learning
vestibular
schwannoma
neuro-oncology
Online Access:https://www.mdpi.com/2072-6694/14/9/2069

Internet

https://www.mdpi.com/2072-6694/14/9/2069

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