This project implements a complete deep learning pipeline for counting cells in microscopy images using semantic segmentation. Given fluorescence microscopy images, the model predicts a binary ...

What should I do to properly use my cell segmentation mask? Another thing I noticed is that although each cell was manually drawn and labeled in Napari, and the .tif file was converted to a binary ...

This study aims to investigate the application of visual information processing mechanisms in the segmentation of stem cell (SC) images. The cognitive principles underlying visual information ...

ABSTRACT: Spatial transcriptomics is undergoing rapid advancements and iterations. It is a beneficial tool to significantly enhance our understanding of tissue organization and relationships between ...

Cytotoxicity is a broad term that refers to the negative effects of chemical or environmental changes on cell health. Cells exposed to a cytotoxic stimulus may lose metabolic activity, experience ...

Exploring biology in its native environment is perhaps the ideal scenario for generating better hypotheses about the cellular interactions that influence—and drive—healthy and diseased states, ...

Formalin-fixed, paraffin-embedded (FFPE) tissues represent the predominant sample conservation method in clinical practice, yet degraded and crosslinked RNA has long limited whole-transcriptome ...

Cell segmentation is a crucial step in numerous biomedical imaging endeavors—so much so that the community is flooded with publicly available, state-of-the-art segmentation techniques ready for out-of ...