@inproceedings{2df51855842d4ef5ae43c5e2ac68a386,
title = "An improved support vector machine algorithm for blood cell segmentation from hyperspectral images",
abstract = "Blood cell analysis is becoming more and more attainable and worthy for blood diseases diagnosis. And blood cell segmentation is an important step for automated blood cells analysis based on image processing. This paper presented an improved support vector machine algorithm for blood cell segmentation for molecular hyperspectral images processing. This algorithm combined SVM with iterative self-organizing data analysis techniques algorithm to correct the miss-identified pixels by putting them into the minimum Euclidean distance cluster. Satisfactory performance can be seen from the experimental results that the proposed algorithm is superior to ISODATA and SVM algorithms in blood cell segmentation, because the new algorithm combines spatial and spectral information of blood cells.",
keywords = "Blood cell, Hyperspectral imaging, Segmentation, Support vector machine",
author = "Qian Wang and Li Chang and Zhen Sun and Mei Zhou and Qingli Li and Hongying Liu and Fangmin Guo",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016 ; Conference date: 03-10-2016 Through 05-10-2016",
year = "2017",
month = feb,
day = "28",
doi = "10.1109/IMCEC.2016.7867108",
language = "英语",
series = "Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "35--39",
editor = "Bing Xu",
booktitle = "Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016",
address = "美国",
}