[2603.19386] TuLaBM: Tumor-Biased Latent Bridge Matching for Contrast-Enhanced MRI Synthesis

Electrical Engineering and Systems Science > Image and Video Processing arXiv:2603.19386 (eess) [Submitted on 19 Mar 2026] Title:TuLaBM: Tumor-Biased Latent Bridge Matching for Contrast-Enhanced MRI Synthesis Authors:Atharva Rege, Adinath Madhavrao Dukre, Numan Balci, Dwarikanath Mahapatra, Imran Razzak View a PDF of the paper titled TuLaBM: Tumor-Biased Latent Bridge Matching for Contrast-Enhanced MRI Synthesis, by Atharva Rege and 4 other authors View PDF HTML (experimental) Abstract:Contrast-enhanced magnetic resonance imaging (CE-MRI) plays a crucial role in brain tumor assessment; however, its acquisition requires gadolinium-based contrast agents (GBCAs), which increase costs and raise safety concerns. Consequently, synthesizing CE-MRI from non-contrast MRI (NC-MRI) has emerged as a promising alternative. Early Generative Adversarial Network (GAN)-based approaches suffered from instability and mode collapse, while diffusion models, despite impressive synthesis quality, remain computationally expensive and often fail to faithfully reproduce critical tumor contrast patterns. To address these limitations, we propose Tumor-Biased Latent Bridge Matching (TuLaBM), which formulates NC-to-CE MRI translation as Brownian bridge transport between source and target distributions in a learned latent space, enabling efficient training and inference. To enhance tumor-region fidelity, we introduce a Tumor-Biased Attention Mechanism (TuBAM) that amplifies tumor-relevant latent feature...