Comparative analysis of codeword representation by clustering methods for the classification of histological tissue types

Ahmet Saygili; Gunalp Uysal; Gokhan Bilgin

doi:10.1117/12.2228526

8 December 2015 Comparative analysis of codeword representation by clustering methods for the classification of histological tissue types

Ahmet Saygili, Gunalp Uysal, Gokhan Bilgin

Author Affiliations +

Proceedings Volume 9875, Eighth International Conference on Machine Vision (ICMV 2015); 98750U (2015) https://doi.org/10.1117/12.2228526
Event: Eighth International Conference on Machine Vision, 2015, Barcelona, Spain

Abstract

In this study, the classification of several histological tissue types, i.e., muscles, nerves, connective and epithelial tissue cells, is studied in high resolutional histological images. In the feature extraction step, bag of features method is utilized to reveal distinguishing features of each tissue cell types. Local small blocks of sub-images/patches are extracted to find discriminative patterns for followed strategy. For detecting points of interest in local patches, Harris corner detection method is applied. Afterwards, discriminative features are extracted using the scale invariant feature transform method using these points of interests. Several code word representations are obtained by clustering approach (using k-means fuzzy c-means, expectation maximization method, Gaussian mixture models) and evaluated in comparative manner. In the last step, the classification of the tissue cells data are performed using k-nearest neighbor and support vector machines methods.

Citation Download Citation

Ahmet Saygili, Gunalp Uysal, and Gokhan Bilgin "Comparative analysis of codeword representation by clustering methods for the classification of histological tissue types", Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 98750U (8 December 2015); https://doi.org/10.1117/12.2228526

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available