@inproceedings{123c0267579d4e40a7c2616e51d6ae5e,
title = "A novel intuitionistic fuzzy set approach for segmentation of kidney MR images",
abstract = "This paper presents a novel algorithm, which uses intuitionistic fuzzy sets and rough set theory to segment the renal components in kidney MR images. A new membership function is proposed and then is used to obtain an intuitionistic fuzzy model of the image to compensate the inherent heterogeneity present among the different renal tissue classes. In addition, a new method, which uses Hamming distance is proposed to calculate the histon. The histon is then used to compute intuitionistic fuzzy roughness measure which yields optimum valley points for image segmentation. The proposed algorithm segments the kidney MR images into medulla, cortex, and blood vessels. The quantitative performance evaluation indicates better performance of the proposed algorithm over a competing technique.",
author = "Shreyas Mushrif and Aldo Morales and Christopher Sica and Yang, {Qing X.} and Susan Eskin and Lawrence Sinowa",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 ; Conference date: 03-12-2016",
year = "2017",
month = feb,
day = "7",
doi = "10.1109/SPMB.2016.7846874",
language = "English (US)",
series = "2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings",
address = "United States",
}