Automated segmentation of cells with IHC membrane staining.
This study presents a fully automated membrane segmentation technique for immunohistochemical tissue images with membrane staining, which is a critical task in computerized immunohistochemistry (IHC). Membrane segmentation is particularly tricky in immunohistochemical tissue images because the cellular membranes are visible only in the stained tracts of the cell, while the unstained tracts are not visible. Our automated method provides accurate segmentation of the cellular membranes in the stained tracts and reconstructs the approximate location of the unstained tracts using nuclear membranes as a spatial reference. Accurate cell-by-cell membrane segmentation allows per cell morphological analysis and quantification of the target membrane proteins that is fundamental in several medical applications such as cancer characterization and classification, personalized therapy design, and for any other applications requiring cell morphology characterization. Experimental results on real datasets from different anatomical locations demonstrate the wide applicability and high accuracy of our approach in the context of IHC analysis.
Department of Control and Computer Engineering, Politecnico di Torino, Torino 10129, Italy. elisa.ficarra@polito.it
Elisa
E
Ficarra
Santa
S
Di Cataldo
Andrea
A
Acquaviva
Enrico
E
Macii
D000465:Algorithms; D002462:Cell Membrane / Q000648:ultrastructure*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry / Q000379:methods*; D008099:Liver / Q000166:cytology; D008168:Lung / Q000166:cytology; D008175:Lung Neoplasms / Q000473:pathology; D008297:Male; D011467:Prostate / Q000166:cytology; D015203:Reproducibility of Results