Using a generative adversarial network to generate synthetic MRI images for multi-class automatic segmentation of brain tumors

Using a generative adversarial network to generate synthetic MRI images for multi-class automatic segmentation of brain tumors

Challenging tasks such as lesion segmentation, classification, and analysis for the assessment of disease progression can be automatically achieved using deep learning (DL)-based algorithms. DL techniques such as 3D convolutional neural networks are trained using heterogeneous volumetric imaging dat...

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Bibliographic Details
Main Authors: P. Raut, G. Baldini, M. Schöneck, L. Caldeira
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Radiology
Subjects:
deep learning
3D convolutional neural network
generative adversarial network
synthetic images
multi-parametric MRI
brain tumors
Online Access:https://www.frontiersin.org/articles/10.3389/fradi.2023.1336902/full

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https://www.frontiersin.org/articles/10.3389/fradi.2023.1336902/full

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