2 citations · 2 across the 2 of their papers we have counts for
3 papers
Segmentation-free integration of nuclei morphology and spatial transcriptomics for retinal images
Eduard Chelebian, Pratiti Dasgupta, Zainalabedin Samadi +2
This study introduces SEFI (SEgmentation-Free Integration), a novel method for integrating morphological features of cell nuclei with spatial transcriptomics data. Cell segmentatio…
What makes for good morphology representations for spatial omics?
Eduard Chelebian, Christophe Avenel, Carolina Wählby
Spatial omics has transformed our understanding of tissue architecture by preserving spatial context of gene expression patterns. Simultaneously, advances in imaging AI have enable…
Cell segmentation of in situ transcriptomics data using signed graph partitioning
Axel Andersson, Andrea Behanova, Carolina Wählby +1
The locations of different mRNA molecules can be revealed by multiplexed in situ RNA detection. By assigning detected mRNA molecules to individual cells, it is possible to identify…