Graph Cut Segmentation of Neuronal Structures from Transmission Electron Micrographs

Nhat Vu and B. S. Manjunath
Center for Bio-image Informatics
Department of Electrical and Computer Engineering
University of California, Santa Barbara, CA 93106-9560


In many neurophysiological studies, understanding the neuronal circuitry of the brain requires detailed 3D models of the nerve cells and their synapses. Typically, researchers build the 3D models by manually tracing the 2D cross-sectional profiles of the 3D structures from serial electron micrograph (EM) stacks and then construct the models from these 2D contours. While current computer-aided techniques can reduce the tracing time, they often require extensive user interaction. We propose a segmentation framework to extract the 2D profiles that is both fast and requires a minimal amount of user interaction. The framework uses graph cuts to minimize an energy defined over the image intensity and the flux of the intensity gradient field. Furthermore, to correct segmentation errors, our framework allows for efficient and intuitive editing of the initial results.
[PDF] [BibTex]
Nhat Vu and B.S. Manjunath,
Proc. IEEE International Conference on Image Processing, pp. 725-728, San Diego, CA, Oct. 2008.
Node ID: 502 , DB ID: 309 , Lab: VRL , Target: Conference
Subject: [Detection on Images and Videos] « Look up more