Leukocyte cells identification and quantitative morphometry based on molecular hyperspectral imaging technology

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.