Tosun, Akif BurakSokmensuer, C.Gündüz-Demir, Çiğdem2016-02-082016-02-0820101051-4651http://hdl.handle.net/11693/28520Date of Conference: 23-26 Aug. 2010This paper presents a new algorithm for the unsupervised segmentation of tissue images. It relies on using the spatial information of cytological tissue components. As opposed to the previous study, it does not only use this information in defining its homogeneity measures, but it also uses it in its region growing process. This algorithm has been implemented and tested. Its visual and quantitative results are compared with the previous study. The results show that the proposed segmentation algorithm is more robust in giving better accuracies with less number of segmented regions. © 2010 IEEE.EnglishImage segmentationQuantitative medical image analysisTexture analysisMedical image analysisObject orientedQuantitative resultRegion growingSegmentation algorithmsSegmented regionsSpatial informationsTexture analysisTissue componentsTissue image segmentationTissue imagesUnsupervised segmentationAlgorithmsImage analysisInformation useMedical imagingPattern recognitionTexturesTissueImage segmentationConference Paper10.1109/ICPR.2010.616