Conditional generative adversarial network driven radiomic prediction of mutation status based on magnetic resonance imaging of breast cancer

Conditional generative adversarial network driven radiomic prediction of mutation status based on magnetic resonance imaging of breast cancer

Abstract Background Breast Cancer (BC) is a highly heterogeneous and complex disease. Personalized treatment options require the integration of multi-omic data and consideration of phenotypic variability. Radiogenomics aims to merge medical images with genomic measurements but encounter challenges d...

Full description

Bibliographic Details
Main Authors: Zi Huai Huang, Lianghong Chen, Yan Sun, Qian Liu, Pingzhao Hu
Format: Article
Language:English
Published: BMC 2024-03-01
Series:Journal of Translational Medicine
Subjects:
Breast cancer
cGANs
Radiogenomics
Machine learning
Magnetic resonance images
Online Access:https://doi.org/10.1186/s12967-024-05018-9

Internet

https://doi.org/10.1186/s12967-024-05018-9

Similar Items