Back to search

Article

Deep learning enables feature extraction of 3D collagen architecture in cleared fibrotic tissues

2026-02-26

Abstract excerpt

<h4>ABSTRACT</h4> Light-sheet fluorescence microscopy enables deep optical sectioning of large, cleared biological tissues. However, effective clearing of collagen-rich tissues remains a persistent technical challenge. Moreover, standardized workflows integrating three-dimensional imaging with computational analysis of collagen architecture are currently unavailable. Here, we present an integrated pipeline combin...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
b9fb0680-7367-5846-804b-fc6b2a926545
DOI
10.64898/2026.02.25.707675
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Deep learning enables feature extraction of 3D collagen architecture in cleared fibrotic tissuesDOI 10.64898/2026.02.25.707675
Select a neighboring publication to make it the new centre.