Publications by authors named "D Sage"
This manuscript showcases the latest advancements in deepImageJ, a pivotal Fiji/ImageJ plugin for bioimage analysis in life sciences. The plugin, known for its user-friendly interface, facilitates the application of diverse pre-trained convolutional neural networks to custom data. The manuscript demonstrates several deepImageJ capabilities, particularly in deploying complex pipelines, three-dimensional (3D) image analysis, and processing large images.
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- * The group organizes MiFoBio conferences that feature lectures and hands-on workshops, allowing specialists to share insights and reflect on the evolution of microscopy over the years.
- * The 2023 conference included retrospective talks on key topics like multicellular imaging and advancements in imaging technologies, with summaries available on the ImaBio YouTube channel for further learning.
Article Synopsis
- Machine learning is changing image processing and analysis, especially in microscopy, by automating tasks and uncovering visual patterns.
- The review examines the importance of data characteristics like quantity and content in choosing the right ML models for microscopy applications.
- It also discusses the uses of ML in cell biology, including data curation and prediction, while addressing challenges and risks, suggesting ways to mitigate them.
Super-resolution structured-illumination microscopy (SIM) is a powerful technique that allows one to surpass the diffraction limit by up to a factor two. Yet, its practical use is hampered by its sensitivity to imaging conditions which makes it prone to reconstruction artefacts. In this work, we present FlexSIM, a flexible SIM reconstruction method capable to handle highly challenging data.
View Article and Find Full Text PDFQuantification of Mycobacterium tuberculosis (Mtb) growth dynamics in cell-based in vitro infection models is traditionally carried out by measurement of colony forming units (CFU). However, Mtb being an extremely slow growing organism (16-24 h doubling time), this approach requires at least 3 weeks of incubation to obtain measurable readouts. In this chapter, we describe an alternative approach based on time-lapse microscopy and quantitative image analysis that allows faster quantification of Mtb growth dynamics in host cells.
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