title: Interactive Extraction of Neural Structures with User-Guided Morphological Diffusion.
abstract: Extracting neural structures with their fine details from confocal volumes is essential to quantitative analysis in neurobiology research. Despite the abundance of various segmentation methods and tools, for complex neural structures, both manual and semi-automatic methods are ine ective either in full 3D or when user interactions are restricted to 2D slices. Novel interaction techniques and fast algorithms are demanded by neurobiologists to interactively and intuitively extract neural structures from confocal data. In this paper, we present such an algorithm-technique combination, which lets users interactively select desired structures from visualization results instead of 2D slices. By integrating the segmentation functions with a confocal visualization tool neurobiologists can easily extract complex neural structures within their typical visualization workflow.
authors.affiliation: SCI Institute and the School of Computing, University of Utah.
authors.forename: Yong
authors.initials: Y
authors.lastname: Wan
authors.affiliation: Department of Neurobiology and Anatomy, University of Utah.
authors.forename: Hideo
authors.initials: H
authors.lastname: Otsuna
authors.affiliation: Department of Neurobiology and Anatomy, University of Utah.
authors.forename: Chi-Bin
authors.initials: CB
authors.lastname: Chien
authors.affiliation: SCI Institute and the School of Computing, University of Utah.
authors.forename: Charles
authors.initials: C
authors.lastname: Hansen
keywords: Computer Graphics [I.3.8]: Methodology and Techniques; Image Processing and Computer Vision [I.4.6]: Segmentation; Interaction techniques; Life and Medical Sciences [J.3]: Biology and genetics; Region growing, partitioning