Automated clustering of histology slide texture using co-occurrence based grayscale image features and manifold learning

Onder, Devrim; Karaçali, B.

doi:10.1109/biyomut.2009.5130342

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2018

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“…A clustering algorithm is designed for the development of manifold learning [8,9,10]. The learning framework can be combined with the non linear dimensionality reduction process.…”

Section: Related Workmentioning

confidence: 99%

An Edge based Clustering Technique with Self-Organizing Maps

Chamundeswari¹,

Varma²,

Satyanarayana³

2018

IJITCS

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Recently, artificial neural networks are fund to be efficiently used in clustering algorithms. So, the present paper focuses on the development of a novel clustering method based on artificial neural networks. The present paper uses an enhancement filter to enhance the segments in the input image. After this, the various sub images are generated and features are computed for each sub and edge image. Finally, the Self Organizing Map (SOM) is used for clustering process. The proposed novel method is evaluated with a database of 795 leaf images. Further various Probability Distributed Functions (PDFs) are used to evaluate the efficacy of the proposed method. The performance measures of the proposed method indicate the efficiency of the extended clustering method with SOM.

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“…A clustering algorithm is designed for the development of manifold learning [8,9,10]. The learning framework can be combined with the non linear dimensionality reduction process.…”

Section: Related Workmentioning

confidence: 99%