English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Organoids are self-organized 3D cell clusters that closely mimic thearchitecture and function of in vivo tissues and organs. Quantification oforganoid morphology helps in studying organ development, drug discovery, andtoxicity assessment. Recent microscopy techniques provide a potent tool toacquire organoid morphology features, but manual image analysis remains a laborand time-intensive process. Thus, this paper proposes a comprehensive pipelinefor microscopy analysis that leverages the SegmentAnything to preciselydemarcate individual organoids. Additionally, we introduce a set ofmorphological properties, including perimeter, area, radius, non-smoothness,and non-circularity, allowing researchers to analyze the organoid structuresquantitatively and automatically. To validate the effectiveness of ourapproach, we conducted tests on bright-field images of human inducedpluripotent stem cells (iPSCs) derived neural-epithelial (NE) organoids. Theresults obtained from our automatic pipeline closely align with manual organoiddetection and measurement, showcasing the capability of our proposed method inaccelerating organoids morphology analysis.

SegmentAnything helps microscopy images based automatic and quantitative organoid detection and analysis