文章基本信息

标题：Enhanced CNN Based Electron Microscopy Image Segmentation
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作者：Govindan-pp-84-97.pdf">S. M. Leena ; V. K. Govindan 等
期刊名称：Cybernetics and Information Technologies
印刷版ISSN：1311-9702
电子版ISSN：1314-4081
出版年度：2012
卷号：12
期号：2
出版社：Bulgarian Academy of Science
摘要：Detecting the neural processes like axons and dendrites needs high quality SEM images. This paper proposes an approach using perceptual grouping via a graph cut and its combinations with Convolutional Neural Network (CNN) to achieve improved segmentation of SEM images. Experimental results demonstrate improved computational efficiency with linear running time.
关键词：Convolutional Neural Network; SEM image; perceptual grouping;constraints via a graph cut; segmentation using a graph cut; graph cut optimization;affinity graph; backpropagation; Maxflow/Mincut algorithm; Neuronal;segmentation.