DocumentCode :
714759
Title :
K-nearest unrepeatable cell graph model of histopathological tissue image
Author :
Serin, Faruk ; Erturkler, Metin ; Gul, Mehmet
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Inonu Univ., Malatya, Turkey
fYear :
2015
fDate :
16-19 May 2015
Firstpage :
2585
Lastpage :
2588
Abstract :
One of the most important components in the histopathological tissue images is the cell nuclei. Features such as the number, morphological properties and location of the cell nuclei offer useful information for histopathological analysis. Cell-graph models are constructed using location information of cell nuclei and important distinctive information can be obtained from the features of the models. The models are generally formed according to the distance between the cell nuclei. However, the distance between the cell nuclei is affected by various factors during obtaining tissue image and shows variety. In this study, using one-way neighborhood relationship of the nuclei with each other is proposed for the construction of the cell-graph models of histopathological images. The proposed approach has been tested on 20 healthy and 20 necrotic liver tissue images. The results show that graph models constructed by the neighborhood relationship, have more distinctive characteristics than distance-based graph models.
Keywords :
biological tissues; cellular biophysics; liver; medical image processing; K-nearest unrepeatable cell graph model; cell nuclei; healthy liver tissue image; histopathological analysis; histopathological tissue image; morphological property; necrotic liver tissue image; Cancer; Computational modeling; Image segmentation; Imaging; Liver; Object oriented modeling; Object segmentation; Cell graph modeling; Computer-aided diagnosis; Histopathological image analysis; Tissue modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
Type :
conf
DOI :
10.1109/SIU.2015.7130414
Filename :
7130414
Link To Document :
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