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13 March 2024 Deep transfer learning and ensemble learning coupled with non-linear optical microscopy for the classification of senescent cells
Salvatore Sorrentino, Francesco Manetti, Arianna Bresci, Federico Vernuccio, Chiara Ceconello, Marco Ventura, Andrea Rabolini, Silvia Ghislanzoni, Italia Bongarzone, Renzo Vanna, Giulio Cerullo, Dario Polli
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Proceedings Volume PC12855, Advanced Chemical Microscopy for Life Science and Translational Medicine 2024; PC128550R (2024) https://doi.org/10.1117/12.3001077
Event: SPIE BiOS, 2024, San Francisco, California, United States
Abstract
Recent oncology research highlights that senescence, once deemed beneficial in cancer treatments, can contribute to cancer relapse. Detecting therapy-induced senescent cells is challenging due to their complexity and lack of specific markers. Nonlinear optical (NLO) microscopy provides a fast, non-invasive, label-free detection solution. To distinguish between senescent and proliferating cells, here we present the development of a deep learning architecture based on multimodal NLO microscopy images coming from Stimulated Raman Scattering, Two Photon Excited Fluorescence and Optical Transmission. Despite limited labeled data, Transfer Learning, Data Augmentation, and Ensemble Learning techniques allowed us to achieve an accuracy over 90%. Ultimately, the predictions of the neural network are evaluated using the Grad-CAM visualization approach, which allows highlighting the most important features in the input images responsible for the labels assigned by the network. This work reveals the effectiveness of deep learning in senescence classification, potentially advancing treatment strategies.
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Salvatore Sorrentino, Francesco Manetti, Arianna Bresci, Federico Vernuccio, Chiara Ceconello, Marco Ventura, Andrea Rabolini, Silvia Ghislanzoni, Italia Bongarzone, Renzo Vanna, Giulio Cerullo, and Dario Polli "Deep transfer learning and ensemble learning coupled with non-linear optical microscopy for the classification of senescent cells", Proc. SPIE PC12855, Advanced Chemical Microscopy for Life Science and Translational Medicine 2024, PC128550R (13 March 2024); https://doi.org/10.1117/12.3001077
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KEYWORDS
Nonlinear optics
Optical microscopy
Cancer
Radiotherapy
Chemotherapy
Deep learning
Microscopes
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