Automatic Brain Extraction in Nissl-Stained Histological Sections

被引：0
|
作者：
Smolcic, T. [1 ]
Petkovic, T. [2 ]
Skokic, S. [1 ]
机构：
[1] Univ Zagreb, Sch Med, Zagreb, Croatia
[2] Univ Zagreb, Fac Elect Engn & Comp, Zagreb, Croatia
来源：
2020 43RD INTERNATIONAL CONVENTION ON INFORMATION, COMMUNICATION AND ELECTRONIC TECHNOLOGY (MIPRO 2020) | 2020年
关键词：
brain segmentation; anisotropic diffusion; shape smoothing; histology; FOCAL CEREBRAL-ISCHEMIA; MOUSE-BRAIN; SEGMENTATION;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A simple and robust algorithm for automatic segmentation of Nissl-stained histological brain images is presented. The algorithm preprocesses the input image with anisotropic diffusion filter prior to applying standard binary image manipulations to isolate the brain from the background. Shape smoothing filter is applied to mimic the common practice of human evaluators. The developed code is tested on histological sections of mouse brains and shows good agreement with manual segmentation results.
引用
收藏
页码：283 / 287
页数：5
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