DreamOn: a data augmentation strategy to narrow the robustness gap between expert radiologists and deep learning classifiers

DreamOn: a data augmentation strategy to narrow the robustness gap between expert radiologists and deep learning classifiers

PurposeSuccessful performance of deep learning models for medical image analysis is highly dependent on the quality of the images being analysed. Factors like differences in imaging equipment and calibration, as well as patient-specific factors such as movements or biological variability (e.g., tiss...

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Bibliographic Details
Main Authors: Luc Lerch, Lukas S. Huber, Amith Kamath, Alexander Pöllinger, Aurélie Pahud de Mortanges, Verena C. Obmann, Florian Dammann, Walter Senn, Mauricio Reyes
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Radiology
Subjects:
deep learning
robustness
ultrasound
breast cancer
generative adversarial network
convolutional neural network
Online Access:https://www.frontiersin.org/articles/10.3389/fradi.2024.1420545/full
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https://www.frontiersin.org/articles/10.3389/fradi.2024.1420545/full

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