Article

Prediction of Prognosis in Glioblastoma with Radiomics Features extracted by Synthetic MR Image using Cycle-consistent GAN

2023-07-25

Abstract excerpt

<title>Abstract</title> <p>Purpose To propose a style transfer model for multi-contrast magnetic resonance imaging (MRI) images with a cycle-consistent generative adversarial network (CycleGAN) and evaluate the image quality and prognosis prediction performance for glioblastoma (GBM) patients from the extracted radiomics features. Methods Style transfer models of T1 weighted MRI image (T1w) to T2 weighted MRI ima...

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Literature Corpus work: f19ed86b-172b-5af0-a506-374ae0a0bbe5
DOI: 10.21203/rs.3.rs-2974678/v1

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