Abstract: We propose a new robust, effective, and surprisingly simple approach for the segmentation of cells in phase contrast microscopy images. The key feature of our algorithm is that it strongly ...
Chang leads assay and applications development at Takara Bio, driving the commercialization of novel spatial genomics products. She has extensive experience in single-cell multiomics technologies and ...
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 ...
Abstract: State-of-the-art (SOTA) methods for cell instance segmentation are based on deep learning (DL) semantic segmentation approaches, focusing on distinguishing foreground pixels from background ...
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, ...
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