Application of local binary pattern and human visual Fibonacci texture features for classification different medical images

Foram Sanghavi; Sos Agaian

doi:10.1117/12.2262930

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10 May 2017 Application of local binary pattern and human visual Fibonacci texture features for classification different medical images

Foram Sanghavi, Sos Agaian

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Proceedings Volume 10221, Mobile Multimedia/Image Processing, Security, and Applications 2017; 102210S (2017) https://doi.org/10.1117/12.2262930
Event: SPIE Commercial + Scientific Sensing and Imaging, 2017, Anaheim, California, United States

Abstract

The goal of this paper is to (a) test the nuclei based Computer Aided Cancer Detection system using Human Visual based system on the histopathology images and (b) Compare the results of the proposed system with the Local Binary Pattern and modified Fibonacci -p pattern systems. The system performance is evaluated using different parameters such as accuracy, specificity, sensitivity, positive predictive value, and negative predictive value on 251 prostate histopathology images. The accuracy of 96.69% was observed for cancer detection using the proposed human visual based system compared to 87.42% and 94.70% observed for Local Binary patterns and the modified Fibonacci p patterns.

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Foram Sanghavi and Sos Agaian "Application of local binary pattern and human visual Fibonacci texture features for classification different medical images", Proc. SPIE 10221, Mobile Multimedia/Image Processing, Security, and Applications 2017, 102210S (10 May 2017); https://doi.org/10.1117/12.2262930

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