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Deep learning

A collection of 3 posts

Fluorescent image of biological cells

AI-assisted image analysis

Triple Threat: AI-assisted Multiview Confocal Imaging

One group of researchers is bringing deep learning to that workhorse of bioimaging: confocal microscopy. In a recent paper, Wu et al. present a new microscopy platform that builds on confocal using AI approaches and technical innovations.

How to train your model: LIVECell for AI-assisted cell segmentation

cell segmentation

How to train your model: LIVECell for AI-assisted cell segmentation

Edlund et al. created a dataset of phase-contrast images encompassing including 8 morphologically different cell types and trained a CNN-based model to evaluate the model’s cell segmentation accuracy.

More data, more problems: Perspectives on challenges in large-scale, high-complexity bioimage analysis

AI and deconvolution

More data, more problems: Perspectives on challenges in large-scale, high-complexity bioimage analysis

Advances in high-parameter imaging technologies over the past several decades created an exponential increase in the complexity of imaging datasets. In this article, we’ll cover: in situ imaging technologies, deep learning for image analysis, and unmet challenges bioimaging dataset analysis.