Salah Elias
@theeliaslab.bsky.social
🇩🇿 🇫🇷 cell & developmental biologist
associate professor at @unisouthampton.bsky.social
stem cells, cell division, cell polarity, mammary organogenesis, breast cancer and microscopy
associate professor at @unisouthampton.bsky.social
stem cells, cell division, cell polarity, mammary organogenesis, breast cancer and microscopy
CenSegNet is fast, generalisable, and open-source—built for biologists and pathologists.
A fantastic collaboration across
@unisouthampton.bsky.social & @cam.ac.uk
#theeliaslab @sotonbiosciences.bsky.social
3/3
A fantastic collaboration across
@unisouthampton.bsky.social & @cam.ac.uk
#theeliaslab @sotonbiosciences.bsky.social
3/3
September 15, 2025 at 8:33 PM
CenSegNet is fast, generalisable, and open-source—built for biologists and pathologists.
A fantastic collaboration across
@unisouthampton.bsky.social & @cam.ac.uk
#theeliaslab @sotonbiosciences.bsky.social
3/3
A fantastic collaboration across
@unisouthampton.bsky.social & @cam.ac.uk
#theeliaslab @sotonbiosciences.bsky.social
3/3
Using human breast cancer TMAs, CenSegNet uncovers how structural and numerical centrosome abnormalities are patterned across tumour regions, revealing their mechanistic uncoupling and links to tumour progression and heterogeneity, hormone status, and age.
2/3
2/3
September 15, 2025 at 8:33 PM
Using human breast cancer TMAs, CenSegNet uncovers how structural and numerical centrosome abnormalities are patterned across tumour regions, revealing their mechanistic uncoupling and links to tumour progression and heterogeneity, hormone status, and age.
2/3
2/3
CenSegNet is fast, generalisable, and open-source—built for biologists and pathologists.
A fantastic collaboration across @unisouthampton.bsky.social & @cam.ac.uk
Check it out: github.com/SKELAB/CenSe...
#theeliaslab @sotonbiosciences.bsky.social
3/3
A fantastic collaboration across @unisouthampton.bsky.social & @cam.ac.uk
Check it out: github.com/SKELAB/CenSe...
#theeliaslab @sotonbiosciences.bsky.social
3/3
GitHub - SKELAB/CenSegNet: A generalist high-throughput deep learning framework for centrosome phenotyping at spatial and single-cell resolution in heterogeneous tissues
A generalist high-throughput deep learning framework for centrosome phenotyping at spatial and single-cell resolution in heterogeneous tissues - SKELAB/CenSegNet
github.com
September 15, 2025 at 4:09 PM
CenSegNet is fast, generalisable, and open-source—built for biologists and pathologists.
A fantastic collaboration across @unisouthampton.bsky.social & @cam.ac.uk
Check it out: github.com/SKELAB/CenSe...
#theeliaslab @sotonbiosciences.bsky.social
3/3
A fantastic collaboration across @unisouthampton.bsky.social & @cam.ac.uk
Check it out: github.com/SKELAB/CenSe...
#theeliaslab @sotonbiosciences.bsky.social
3/3