Pre- to Post-Contrast Breast MRI Synthesis for Enhanced Tumour Segmentation

Richard Osuala, Smriti Joshi, Apostolia Tsirikoglou, Lidia Garrucho, Walter H. L. Pinaya +2 more
11/17/2023
eess.IVcs.CVcs.LG

Official code: RichardObi/pre_post_synthesis (13 stars, last commit 2024-01-31).

Abstract

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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Code Implementations(1)

RichardObi/pre_post_synthesisOfficial100%

Official repository for "Pre- to Post-Contrast Breast MRI Synthesis for Enhanced Tumour Segmentation"

131C, C++Nov 17, 20232 years ago
breast-cancerdce-mrigenerative-adversarial-networkgenerative-aiimage-synthesis+7 more

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Cite this paper

@article{osuala2023pre,
  title  = {Pre- to Post-Contrast Breast MRI Synthesis for Enhanced Tumour Segmentation},
  author = {Richard Osuala and Smriti Joshi and Apostolia Tsirikoglou and Lidia Garrucho and Walter H. L. Pinaya and Oliver Diaz and Karim Lekadir},
  year   = {2023},
  eprint = {2311.10879},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2311.10879v3}
}

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