Journal of Innovative Optical Health Sciences, Volume. 13, Issue 2, 2050005(2020)

Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology

Xueqi Hu... Jiahua Ou, Mei Zhou, Menghan Hu, Li Sun, Song Qiu, Qingli Li* and Junhao Chu |Show fewer author(s)
Author Affiliations
  • Shanghai Key Laboratory of Multidimensional, Information Processing, East China Normal University, Shanghai 200241, P. R. China
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    Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection of light, the spectral feature is proved to be important for leukocytes classification and identification. This paper proposes an accurate identification method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging (HSI) technology which combines the spectral information. The segmentation of nucleus and cytoplasm is obtained by the morphological watershed algorithm. Then, the spectral features are extracted and combined with the spatial features. Based on this, the support vector machine (SVM) is applied for classification of five types of leukocytes and abnormal leukocytes. Compared with different classification methods, the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes, improving the accuracy in the classification and identification of leukocytes. This paper only selects one subtype of ALL for test, and the proposed method can be applied for detection of other leukemia in the future.

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    Xueqi Hu, Jiahua Ou, Mei Zhou, Menghan Hu, Li Sun, Song Qiu, Qingli Li, Junhao Chu. Spatial-spectral identification of abnormal leukocytes based on microscopic hyperspectral imaging technology[J]. Journal of Innovative Optical Health Sciences, 2020, 13(2): 2050005

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    Paper Information

    Received: Aug. 24, 2019

    Accepted: Nov. 21, 2019

    Published Online: Aug. 6, 2020

    The Author Email: Li Qingli (qlli@cs.ecnu.edu.cn)

    DOI:10.1142/s1793545820500054

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