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Pre- to post-contrast breast MRI synthesis for enhanced tumour segmentation.
In: (Conference on Medical Imaging - Image Processing, 19-22 Februar 2024, San Diego, California). 1000 20th St, Po Box 10, Bellingham, Wa 98227-0010 Usa: SPIE, 2024.:129260Y (Proc. SPIE ; 12926)
Despite its benefits for tumour detection and treatment, the administration of contrast agents in dynamic contrast-enhanced MRI (DCE-MRI) is associated with a range of issues, including their invasiveness, bioaccumulation, and a risk of nephrogenic systemic fibrosis. This study explores the feasibility of producing synthetic contrast enhancements by translating pre-contrast T1-weighted fat-saturated breast MRI to their corresponding first DCE-MRI sequence leveraging the capabilities of a generative adversarial network (GAN). Additionally, we introduce a Scaled Aggregate Measure (SAMe) designed for quantitatively evaluating the quality of synthetic data in a principled manner and serving as a basis for selecting the optimal generative model. We assess the generated DCE-MRI data using quantitative image quality metrics and apply them to the downstream task of 3D breast tumour segmentation. Our results highlight the potential of post-contrast DCE-MRI synthesis in enhancing the robustness of breast tumour segmentation models via data augmentation. Our code is available at https://github.com/RichardObi/pre_post_synthesis.
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Publication type
Article: Conference contribution
Keywords
Breast Cancer ; Contrast Agent ; Deep Learning ; Gans ; Generative Models ; Synthetic Data; Image; Cancer
ISSN (print) / ISBN
0277-786X
e-ISSN
1996-756X
Conference Title
Conference on Medical Imaging - Image Processing
Conference Date
19-22 Februar 2024
Conference Location
San Diego, California
Journal
Proceedings of SPIE
Quellenangaben
Volume: 12926,
Article Number: 129260Y
Publisher
SPIE
Publishing Place
1000 20th St, Po Box 10, Bellingham, Wa 98227-0010 Usa
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute for Machine Learning in Biomed Imaging (IML)
Grants
Ministry of Science and Innovation of Spain
European Union
European Union