Automatically Segmenting and Reconstructing Neurons in SEM images

	Automatically Segmenting and Reconstructing Neurons in SEM images
	Rao Q(饶强)1 ; Han H(韩华)1 ; Li WF(李伟夫)2; Shen LJ(沈丽君)1 ; Chen X(陈曦)1 ; Xie QW(谢启伟)1
	2016-10
会议名称	IEEE International Conference on Mechatronics and Automation
会议录名称	ICMA2016 proceedings
会议日期	2016-8
会议地点	中国哈尔滨
摘要	Neuronal networks reconstruction is rather a challenge in the neuroscience. Recent developments in volume electron microscopy (EM) imaging have enabled us to obtain large amounts of brain tissues imaging data. Analysis of the tremendously huge electron microscopy (EM) neuronal images based on automated method would be of vital importance. In this paper we propose a method that training deep convolutional neural network (DCNN) on labeled data for neuronal boundary detection; and then with the membrane detection probability map (MDPM) generated by DCNN, a marker-controlled watershed method is used to segment neurons in the EM images. After getting the sequence of 2D EM neuronal images segmented, semi-automated and automated 3D reconstruction methods are employed to connect the sections of the corresponding segmentations belonging to each neuron. Finally, we have reconstructed dense neurons in 500 of 1793 scanning electron microscopy (SEM) images of drosophila mushroom body with automated method and several neurons with semi-automated method.
关键词	Neuronal Networks Reconstruction Deep Convolutional Neural Network Watershed Neuronal Boundary Detection Drosophila Mushroom Body.
学科领域	模式识别与智能系统
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/14642
专题	脑图谱与类脑智能实验室_微观重建与智能分析
作者单位	1.中国科学院自动化研究所 2.湖北大学
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Rao Q,Han H,Li WF,et al. Automatically Segmenting and Reconstructing Neurons in SEM images[C],2016.

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