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Detection of Mitotic Cells in Histopathological Images Using Textural Features

dc.contributor.authorAlbayrak, Abdulkadir
dc.contributor.authorBilgin, Gokhan
dc.date.accessioned2026-06-27T13:20:53Z
dc.date.issued2013
dc.description.abstractIn this work, segmentation of cellular structures in the high resolutional histopathological images and possibility of the discrimination within normal and mitotic cells has been investigated. Mitosis detection is very exhaustive and time consuming process. In the first step, features of cells which have been found by the clustering algorithm have been extracted by oriented gradient histograms (HOG) method which is known as a robust texture descriptor. A mitotic cell has some textural changes that makes it recognizable among other normal cells. Hence, the classification accuracy of the unsupervised learning methods is increased after making use of proposed textural descriptor.en
dc.identifier.isbn978-1-4673-5563-6; 978-1-4673-5562-9
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/20.500.14981/52038
dc.identifier.wos000325005300038
dc.language.isotur
dc.publisherIEEE
dc.relation.conference21st Signal Processing and Communications Applications Conference (SIU)
dc.relation.ispartof2013 21ST SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
dc.subjectHistopathological images
dc.subjectmitosis detection
dc.subjecthistogram of oriented gradients
dc.subjectsegmentation
dc.subjectclassification
dc.subjectTRACKING
dc.subjectEngineering
dc.subjectTelecommunications
dc.titleDetection of Mitotic Cells in Histopathological Images Using Textural Features
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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