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Automated clustering of histology slide texture using co-occurrence based grayscale image features and manifold learning [Gri seviye birliktelik matrisi öznitelikleri ve manifold ö?renme yardimiyla histoloji görüntülerinde otomatik doku siniflandirilmasi]

Access

info:eu-repo/semantics/closedAccess

Date

2009

Author

Önder, D.
Karaçali, B.

Metadata

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Abstract

The aim of this work is to perform automated texture classification of histology slides using grayscale images and manifold learning method. Texture feature vectors were obtained using local gray scale co-occurrence matrices and the dimension of the feature vector space was lowered using Isomap dimension reduction. In a lower dimension feature space, k-means clustering operation was performed in order to provide separate texture clusters. In this work, experimental results were obtained using human kidney histology slides. Corresponding feature vectors and determined texture types were given as results. ©2009 IEEE.

Source

Proceedings of 2009 14th National Biomedical Engineering Meeting, BIYOMUT 2009

URI

https://doi.org/10.1109/BIYOMUT.2009.5130342
https://hdl.handle.net/11147/9759

Collections

  • Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection [4673]



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