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Proceedings Paper

Spatial-spectral blood cell classification with microscopic hyperspectral imagery
Author(s): Qiong Ran; Lan Chang; Wei Li; Xiaofeng Xu
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Paper Abstract

Microscopic hyperspectral images provide a new way for blood cell examination. The hyperspectral imagery can greatly facilitate the classification of different blood cells. In this paper, the microscopic hyperspectral images are acquired by connecting the microscope and the hyperspectral imager, and then tested for blood cell classification. For combined use of the spectral and spatial information provided by hyperspectral images, a spatial-spectral classification method is improved from the classical extreme learning machine (ELM) by integrating spatial context into the image classification task with Markov random field (MRF) model. Comparisons are done among ELM, ELM-MRF, support vector machines(SVM) and SVMMRF methods. Results show the spatial-spectral classification methods(ELM-MRF, SVM-MRF) perform better than pixel-based methods(ELM, SVM), and the proposed ELM-MRF has higher precision and show more accurate location of cells.

Paper Details

Date Published: 24 October 2017
PDF: 11 pages
Proc. SPIE 10461, AOPC 2017: Optical Spectroscopy and Imaging, 1046102 (24 October 2017); doi: 10.1117/12.2281268
Show Author Affiliations
Qiong Ran, Beijing Univ. of Chemical Technology (China)
Lan Chang, Beijing Univ. of Chemical Technology (China)
Wei Li, Beijing Univ. of Chemical Technology (China)
Xiaofeng Xu, Capital Medical Univ. (China)


Published in SPIE Proceedings Vol. 10461:
AOPC 2017: Optical Spectroscopy and Imaging
Jin Yu; Zhe Wang; Wei Hang; Bing Zhao; Xiandeng Hou; Mengxia Xie; Tsutomu Shimura, Editor(s)

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