Reproducible Semi-Automated Quantification of Vascularization in Bone Sections Using CD31 Immunohistochemistry and Trainable Weka Segmentation
Nick Mattern, Holger Freischmidt, Matthias Schulte, Alma Aubert, Sanja Kalmus, Jan Makogon, Paul Alfred Grützner, Jonas Armbruster, Felix Lamadé-Dootz · 2026
Read Reproducible Semi-Automated Quantification of Vascularization in Bone Sections Using CD31 Immunohistochemistry and Trainable Weka Segmentation by Nick Mattern, Holger Freischmidt, Matthias Schulte, Alma Aubert, Sanja Kalmus, Jan Makogon, Paul Alfred Grützner, Jonas Armbruster, Felix Lamadé-Dootz (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13608717.txt.
Description
Nick Mattern and co-authors set out in 2026 a repeatable, semi automatic workflow for measuring blood vessel growth in stained bone sections, using open source tools. Vessel growth matters in bone repair research, but scoring stained sections by hand is slow and varies between people. Their pipeline pairs a stain that marks vessel lining cells with a trainable image classifier inside a free image platform.
Standard steps cover image capture, region choice, pixel classification, and the share of vessel area in the tissue. Hand measures by two observers matched well, and the trained classifiers were far steadier, with variation near two percent against about seven by hand. The workflow also cut scoring time per section. Labs get a shared, low cost standard.
Catalog record
| CREATOR | Nick Mattern, Holger Freischmidt, Matthias Schulte, Alma Aubert, Sanja Kalmus, Jan Makogon, Paul Alfred Grützner, Jonas Armbruster, Felix Lamadé-Dootz |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 44 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |