@inproceedings{2dad78c1df8d4f64977c1a45414226e8,
title = "Automatic polyp detection: A comparative study",
abstract = "In this work we present a performance comparison between a set of different state-of-the-art image descriptors for the automatic detection of polyps in colonoscopy videos. This set includes: Local binary patterns, 2-dimensional Gabor filters, wavelet-based texture, and histogram of oriented gradients. We use these descriptors in conjunction with support vector machine or nearest neighbor classifiers to classify candidate regions, which in turn are selected using the maximally stable extremal regions algorithm. We present performance scores on the ASU-Mayo Clinic polyp database.",
author = "\{El Khatib\}, Alaa and Naoufel Werghi and Hussain Al-Ahmad",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 ; Conference date: 25-08-2015 Through 29-08-2015",
year = "2015",
month = nov,
day = "4",
doi = "10.1109/EMBC.2015.7318941",
language = "British English",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2669--2672",
booktitle = "2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015",
address = "United States",
}