Real-Time Image Analysis Software Suitable for Resource-Constrained Computing

Alexandre Matov

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arXiv · 2407.15735

Real-Time Image Analysis Software Suitable for Resource-Constrained Computing

Alexandre Matov

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Abstract

Methods: We have developed a software suite (DataSet Tracker) for real-time analysis designed to run on computers, smartphones, and smart glasses hardware and suitable for resource-constrained, on-the-fly computing in microscopes without internet connectivity; a demo is available for viewing at datasetanalysis.com. Our objective is to present the community with an integrated, easy to use by all, tool for resolving the complex dynamics of the cytoskeletal meshworks, intracytoplasmic membranous networks, and vesicle trafficking. Our software is optimized for resource-constrained computing and can be installed even on microscopes without internet connectivity. Results: Our computational platform can provide high-content analyses and functional secondary screening of novel compounds that are in the process of approval, or at a pre-clinical stage of development, and putative combination therapies based on FDA-approved drugs. Importantly, dissecting the mechanisms of drug action with quantitative detail will allow the design of drugs that impede relapse and optimal dose regimens with minimal harmful side effects by carefully exploiting disease-specific aberrations. Conclusions: DataSet Tracker, the real-time optical flow feature tracking software presented in this contribution, can serve as the base module of an integrated platform of existing and future algorithms for real-time cellular analysis. The computational assay we propose could successfully be applied to evaluate treatment strategies for any human organ. It is our goal to have this integrated tool approved for use in the clinical practice.

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Alexandre Matov. 2024-07-22. Real-Time Image Analysis Software Suitable for Resource-Constrained Computing. https://arxiv.org/abs/2407.15735

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