High-quality label-free prediction of fluorescence images through stimulated Raman scattering imaging and recurrent deep neural network

Tianrun Chen; Ying Zang; Jia Zhang; Delong Zhang

doi:10.1117/12.2654298

3 April 2023 High-quality label-free prediction of fluorescence images through stimulated Raman scattering imaging and recurrent deep neural network

Tianrun Chen, Ying Zang, Jia Zhang, Delong Zhang

Author Affiliations +

Proceedings Volume 12467, Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment; 124671D (2023) https://doi.org/10.1117/12.2654298
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

Multiple imaging modalities are commonly jointly used for investigating biological phenomena or diagnosis purposes. In this study, we propose a deep-learning-based cross-modality imaging technique that utilizes one imaging modality to computationally predict another. A novel neural network architecture, featuring recurrent multi-stage refinement controlled by gated activation, was developed for this purpose. To demonstrate the effectiveness of the proposed method, we conducted experiments on predicting organelle fluorescence images from stimulated Raman scattering (SRS) imaging. The results of the experiments indicate that our method outperforms the current state-of-the-art techniques across multiple datasets, in terms of both accuracy and efficiency. The neural network architecture was able to produce high-quality predictions with clear boundaries and high prediction accuracy through the multi-stage refinement process. The proposed method presents a versatile framework that addresses the limitations of current deep-learning-enabled cross-modality image prediction techniques and has potential applications in the field of medical and biological imaging.

Citation Download Citation

Tianrun Chen, Ying Zang, Jia Zhang, and Delong Zhang "High-quality label-free prediction of fluorescence images through stimulated Raman scattering imaging and recurrent deep neural network", Proc. SPIE 12467, Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment, 124671D (3 April 2023); https://doi.org/10.1117/12.2654298

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