Abstract: In recent years, deep learning has been widely utilized in the fields of biomedical image segmentation and cellular image analysis. Supervised deep neural networks trained on annotated data ...
Background: 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 ...
Learn how to detect and manage deleted Excel cells that don’t appear in the change log. Tips for tracking all changes effectively. #ExcelTips #TrackChanges #SpreadsheetSkills Donald Trump impeachment ...
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New Excel Features for Pictures in Cells | Tutorial
Explore the latest Excel improvements for inserting and managing pictures in cells. Learn tips and tricks to enhance your spreadsheets efficiently. #ExcelTips #PictureInCell #ProductivityHacks ...
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: 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 ...
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 ...
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