title: Leukocyte cells identification and quantitative morphometry based on molecular hyperspectral imaging technology.
abstract: Leukocyte cells identification is one of the most frequently performed blood tests and plays an important role in the diagnosis of diseases. The quantitative observation of leukocyte cells is often complemented by morphological analysis in both research and clinical condition. Different from the traditional leukocyte cells morphometry methods, a molecular hyperspectral imaging system based on acousto-optic tunable filter (AOTF) was developed and used to observe the blood smears. A combined spatial and spectral algorithm is proposed to identify the cytoplasm and the nucleus of leukocyte cells by integrating the fuzzy C-means (FCM) with the spatial K-means algorithm. Then the morphological parameters such as the cytoplasm area, the nuclear area, the perimeter, the nuclear ratio, the form factor, and the solidity were calculated and evaluated. Experimental results show that the proposed algorithm has better performance than the spectral based algorithm as the new algorithm can jointly use the spatial and spectral information of leukocyte cells.
authors.affiliation: Key Laboratory of Polor Materials and Devices, East China Normal University, Shanghai 200241, China; Medical Center, Columbia University, New York, NY 10032, USA. Electronic address: qlli@cs.ecnu.edu.cn.
authors.forename: Qingli
authors.initials: Q
authors.lastname: Li
authors.affiliation: Institutes for Advanced Interdisciplinary Research, East China Normal University, Shanghai 200062, China.
authors.forename: Yiting
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Key Laboratory of Polor Materials and Devices, East China Normal University, Shanghai 200241, China.
authors.forename: Hongying
authors.initials: H
authors.lastname: Liu
authors.affiliation: Medical Center, Columbia University, New York, NY 10032, USA.
authors.forename: Xiaofu
authors.initials: X
authors.lastname: He
authors.affiliation: Medical Center, Columbia University, New York, NY 10032, USA.
authors.forename: Dongrong
authors.initials: D
authors.lastname: Xu
authors.affiliation: Ruinjin Hospital, Shanghai 200021, China.
authors.forename: Jianbiao
authors.initials: J
authors.lastname: Wang
authors.affiliation: Key Laboratory of Polor Materials and Devices, East China Normal University, Shanghai 200241, China.
authors.forename: Fangmin
authors.initials: F
authors.lastname: Guo
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D048429:Cell Size; D058948:Cell Tracking / Q000379:methods*; D002478:Cells, Cultured; D017143:Fuzzy Logic; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007958:Leukocyte Count / Q000379:methods*; D007962:Leukocytes / Q000166:cytology*; D008853:Microscopy / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Blood cells; Hyperspectral imaging; Leukocyte identification; Morphological analysis