Beyond Imaging: Vision Transformer Digital Twin Surrogates for 3D+T Biological Tissue Dynamics

• URL: http://arxiv.org/abs/2508.15883v2
• Date: Mon, 25 Aug 2025 10:31:36 GMT
• Title: Beyond Imaging: Vision Transformer Digital Twin Surrogates for 3D+T Biological Tissue Dynamics
• Authors: Kaan Berke Ugurlar, Joaquín de Navascués, Michael Taynnan Barros,
• Abstract summary: Vision Transformer Digital Twin Surrogate Network (VT-DTSN) is a deep learning framework for predictive modeling of 3D+T imaging data from biological tissue.<n>VT-DTSN learns to reconstruct high-fidelity, time-resolved dynamics of a Drosophila midgut.
• Score: 0.433313790597694
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Understanding the dynamic organization and homeostasis of living tissues requires high-resolution, time-resolved imaging coupled with methods capable of extracting interpretable, predictive insights from complex datasets. Here, we present the Vision Transformer Digital Twin Surrogate Network (VT-DTSN), a deep learning framework for predictive modeling of 3D+T imaging data from biological tissue. By leveraging Vision Transformers pretrained with DINO (Self-Distillation with NO Labels) and employing a multi-view fusion strategy, VT-DTSN learns to reconstruct high-fidelity, time-resolved dynamics of a Drosophila midgut while preserving morphological and feature-level integrity across imaging depths. The model is trained with a composite loss prioritizing pixel-level accuracy, perceptual structure, and feature-space alignment, ensuring biologically meaningful outputs suitable for in silico experimentation and hypothesis testing. Evaluation across layers and biological replicates demonstrates VT-DTSN's robustness and consistency, achieving low error rates and high structural similarity while maintaining efficient inference through model optimization. This work establishes VT-DTSN as a feasible, high-fidelity surrogate for cross-timepoint reconstruction and for studying tissue dynamics, enabling computational exploration of cellular behaviors and homeostasis to complement time-resolved imaging studies in biological research.

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