A combined spatial-spectral method for automated white blood cells segmentation

详细信息    查看全文

• 作者：Qingli Li ; Yiting Wang ; Hongying Liu ; Jianbiao Wang ; Fangmin Guo
• 关键词：Microscopy hyperspectral imaging ; Blood cells ; Image segmentation
• 刊名：Optics and Laser Technology
• 出版年：2013
• 出版时间：30 December, 2013
• 年：2013
• 卷：54
• 期：Complete
• 页码：225-231
• 全文大小：2715 K

文摘

To overcome the shortcomings in the traditional white blood cells (WBCs) identification methods based on the color or gray images captured by light microscopy, a microscopy hyperspectral imaging system was used to analyze the blood smears. The system was developed by coupling an acousto-optic tunable filter (AOTF) adapter to a microscopy and driven by a SPF Model AOTF controller, which can capture hyperspectral images from 550 nm to 1000 nm with the spectral resolution 2-5 nm. Moreover, a combined spatial-spectral algorithm is proposed to segment the nuclei and cytoplasm of WBCs from the microscopy hyperspectral images. The proposed algorithm is based on the pixel-wise improved spectral angle mapper (ISAM) segmentation, followed by the majority voting within the active contour model regions. Experimental results show that the accuracy of the proposed algorithm is 91.06 % (nuclei) and 85.59 % (cytoplasm), respectively, which is higher than that of the spectral information divergence (SID) algorithm because the new method can jointly use both the spectral and spatial information of blood cells.