@inproceedings{6175b6ae7d0d46f8827dec82d00a6fe1,
title = "A comparative study for chest radiograph image retrieval using binary texture and deep learning classification",
abstract = "In this work various approaches are investigated for X-ray image retrieval and specifically chest pathology retrieval. Given a query image taken from a data set of 443 images, the objective is to rank images according to similarity. Different features, including binary features, texture features, and deep learning (CNN) features are examined. In addition, two approaches are investigated for the retrieval task. One approach is based on the distance of image descriptors using the above features (hereon termed the 'descriptor'-based approach); the second approach ('classification'-based approach) is based on a probability descriptor, generated by a pair-wise classification of each two classes (pathologies) and their decision values using an SVM classifier. Best results are achieved using deep learning features in a classification scheme.",
author = "Yaron Anavi and Ilya Kogan and Elad Gelbart and Ofer Geva and Hayit Greenspan",
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 = "https://doi.org/10.1109/EMBC.2015.7319008",
language = "الإنجليزيّة",
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 = "2940--2943",
booktitle = "2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015",
address = "الولايات المتّحدة",
}