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
会议日期	2016-8
会议地点	中国哈尔滨
关键词	Neuronal Networks Reconstruction Deep Convolutional Neural Network Watershed Neuronal Boundary Detection Drosophila Mushroom Body.
英文摘要	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.
会议录	ICMA2016 proceedings
学科主题	模式识别与智能系统
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/14642]
专题	自动化研究所_类脑智能研究中心
作者单位	1.中国科学院自动化研究所 2.湖北大学
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]. 见:. 中国哈尔滨. 2016-8.