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Biology subjects

Russell, C. T.

Publications and source records attributed to Russell, C. T..

2 recordsLinked to original sources

DL4MicEverywhere: Deep learning for microscopy made flexible, shareable, and reproducible

Deep learning has revolutionised the analysis of extensive microscopy datasets, yet challenges persist in the widespread adoption of these techniques. Many lack access to training data, computing resources, and expertise to develop complex models. We introduce DL4MicEverywhere, advancing our previous ZeroCostDL4Mic platform, to make deep learning more accessible. DL4MicEverywhere uniquely allows flexible training and deployment across diverse computational environments by encapsulating methods in interactive Jupyter notebooks within Docker containers -a standalone virtualisation of required packages and code to reproduce a computational environment-. This enhances reproducibility and convenience. The platform includes twice as many techniques as originally provided by ZeroCostDL4Mic and enables community contributions via automated build pipelines. DL4MicEverywhere empowers participatory innovation and aims to democratise deep learning for bioimage analysis.

bioinformatics↗

mmSIM: An open toolbox for accessible structured illumination microscopy

Since the first practical super-resolution structured illumination fluorescence microscopes (SIM) were demonstrated more than two decades ago the method has become increasingly popular for a wide range of bioimaging applications. The high cost and relative inflexibility of commercial systems, coupled with the conceptual simplicity of the approach and the desire to exploit and customise existing hardware, have led to the development of a large number of home-built systems. Several detailed hardware designs are available in the scientific literature, complemented by open-source software tools for SIM image validation and reconstruction. However, there remains a lack of simple open-source software to control these systems and manage the synchronization between hardware components, which is critical for effective SIM imaging. This article describes a new suite of software tools based on the popular Micro-Manager package, which enable the keen microscopist to develop and run a SIM system. We use the software to control two custom-built, high-speed, spatial light modulator-based SIM systems, evaluating their performance by imaging a range of fluorescent samples. By simplifying the process of SIM hardware development, we aim to support wider adoption of the technique.

biophysics↗