7 May 2012 Pathological leucocyte segmentation algorithm based on hyperspectral imaging technique
Author Affiliations +
Optical Engineering, 51(5), 053202 (2012). doi:10.1117/1.OE.51.5.053202
White blood cells (WBC) are comparatively significant components in the human blood system, and they have a pathological relationship with some blood-related diseases. To analyze the disease information accurately, the most essential work is to segment WBCs. We propose a new method for pathological WBC segmentation based on a hyperspectral imaging system. This imaging system is used to capture WBC images, which is characterized by acquiring 1-D spectral information and 2-D spatial information for each pixel. A spectral information divergence algorithm is presented to segment pathological WBCs into four parts. In order to evaluate the performance of the new approach, K-means and spectral angle mapper-based segmental methods are tested in contrast on six groups of blood smears. Experimental results show that the presented method can segment pathological WBCs more accurately, regardless of their irregular shapes, sizes, and gray-values.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE)
Yana Guan, Qingli Li, Hongying Liu, Ziqiang Zhu, Yiting Wang, "Pathological leucocyte segmentation algorithm based on hyperspectral imaging technique," Optical Engineering 51(5), 053202 (7 May 2012). https://doi.org/10.1117/1.OE.51.5.053202

Image segmentation

Hyperspectral imaging


Imaging systems

Image classification

Image processing algorithms and systems


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