Journal
JOURNAL OF OPTICS
Volume 19, Issue 12, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/2040-8986/aa95d7
Keywords
hyperspectral imaging; red blood cell counting; endmember abundance image; spectral unmixing
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Funding
- National Natural Science Foundation of China [61377107]
- Science and Technology Commission of Shanghai Municipality [14DZ2260800]
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Red blood cell counting, as a routine examination, plays an important role in medical diagnoses. Although automated hematology analyzers are widely used, manual microscopic examination by a hematologist or pathologist is still unavoidable, which is time-consuming and error-prone. This paper proposes a full-automatic red blood cell counting method which is based on microscopic hyperspectral imaging of blood smears and combines spatial and spectral information to achieve high precision. The acquired hyperspectral image data of the blood smear in the visible and near-infrared spectral range are firstly preprocessed, and then a quadratic blind linear unmixing algorithm is used to get endmember abundance images. Based on mathematical morphological operation and an adaptive Otsu's method, a binaryzation process is performed on the abundance images. Finally, the connected component labeling algorithm with magnification-based parameter setting is applied to automatically select the binary images of red blood cell cytoplasm. Experimental results show that the proposed method can perform well and has potential for clinical applications.
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