title: Red Blood Cell Count Automation Using Microscopic Hyperspectral Imaging Technology.
abstract: Red blood cell counts have been proven to be one of the most frequently performed blood tests and are valuable for early diagnosis of some diseases. This paper describes an automated red blood cell counting method based on microscopic hyperspectral imaging technology. Unlike the light microscopy-based red blood count methods, a combined spatial and spectral algorithm is proposed to identify red blood cells by integrating active contour models and automated two-dimensional k-means with spectral angle mapper algorithm. Experimental results show that the proposed algorithm has better performance than spatial based algorithm because the new algorithm can jointly use the spatial and spectral information of blood cells.
authors.affiliation: East China Normal University, Shanghai Key Laboratory of Multidimensional Information Processing, Shanghai 200241, China.
authors.forename: Qingli
authors.initials: Q
authors.lastname: Li
authors.forename: Mei
authors.initials: M
authors.lastname: Zhou
authors.forename: Hongying
authors.initials: H
authors.lastname: Liu
authors.forename: Yiting
authors.initials: Y
authors.lastname: Wang
authors.forename: Fangmin
authors.initials: F
authors.lastname: Guo
mesh_terms: D000465:Algorithms; D001331:Automation; D004867:Equipment Design; D004906:Erythrocyte Count / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008853:Microscopy / Q000295:instrumentation / Q000379:methods*