A novel proximity graph: Circular neighborhood cell graph for histopathological tissue image analyzing
Küçük Resim Yok
Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Wiley
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The cell is the smallest unit of living beings, which has structural and functional properties. Almost all cell behaviors are regulated by various intracellular reactions initiated by the signaling. The signaling and the distance between cells influence each other. Thus, cell-location-based modeling and analyzing of histopathological tissues provide important information to the expert. In literature, methods such as distance-based threshold, K-Nearest Neighbor, Voronoi graphs, Delaunay triangulation, and colored graph have been used. However, circular neighborhood relationships of cells have not been considered by any CAD system so far despite of its crucial impact. Thus, we developed the circular neighborhood cell-graph. Histopathological images of liver were classified by using features extracted from T-Distance, K-Nearest Neighbor, Voronoi, Delaunay, and the proposed cell-graph. Then, the classification performances of the methods were compared. Experimental results show that liver tissue images can be classified with accuracy of 95.7% by using the features provided by the proposed cell-graph model.
Açıklama
Anahtar Kelimeler
cell graph, histopathological image analyzing, nuclei, proximity graph
Kaynak
International Journal of Imaging Systems and Technology
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
30
Sayı
2
