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24 October 2017 Spatial-spectral blood cell classification with microscopic hyperspectral imagery
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Proceedings Volume 10461, AOPC 2017: Optical Spectroscopy and Imaging; 1046102 (2017)
Event: Applied Optics and Photonics China (AOPC2017), 2017, Beijing, China
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.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qiong Ran, Lan Chang, Wei Li, and Xiaofeng Xu "Spatial-spectral blood cell classification with microscopic hyperspectral imagery", Proc. SPIE 10461, AOPC 2017: Optical Spectroscopy and Imaging, 1046102 (24 October 2017);

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