J
John Keyser
Researcher at Texas A&M University
Publications - 109
Citations - 3285
John Keyser is an academic researcher from Texas A&M University. The author has contributed to research in topics: Rendering (computer graphics) & Voronoi diagram. The author has an hindex of 28, co-authored 107 publications receiving 3168 citations. Previous affiliations of John Keyser include University of North Carolina at Chapel Hill & State University of New York System.
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Proceedings ArticleDOI
Knife-edge scanning microscopy for connectomics research
Yoonsuck Choe,David Mayerich,Jaerock Kwon,Daniel E. Miller,Ji Ryang Chung,Chul Sung,John Keyser,Louise C. Abbott +7 more
TL;DR: Kniss-Edge Scanning Microscopy (KESM) as discussed by the authors has been successfully used to scan whole mouse brains stained in Golgi (neuronal morphology), Nissl (somata), and India ink (vasculature), providing unprecedented insights into the systemlevel architectural layout of microstructures within the mouse brain.
Journal ArticleDOI
Specimen preparation, imaging, and analysis protocols for knife-edge scanning microscopy.
Yoonsuck Choe,David Mayerich,Jaerock Kwon,Daniel E. Miller,Chul Sung,Ji Ryang Chung,Todd Huffman,John Keyser,Louise C. Abbott +8 more
TL;DR: The pipeline, including specimen preparation (fixing, staining, and embedding), KESM configuration and setup, sectioning and imaging with the KESS, image processing, data preparation, and data visualization and analysis are described, with the emphasis on specimen preparation and visualization/analysis of obtained KESm data.
Journal ArticleDOI
Statistical geometric computation on tolerances for dimensioning
Songgang Xu,John Keyser +1 more
TL;DR: A new geometric model for representing statistically-based tolerance regions by utilizing generalizing root sum square methods for compositing and cascading over tolerance zones is presented and a generalized RSS method is proposed for modeling geometric representations of tolerances in the statistical way.
Journal ArticleDOI
Hardware Accelerated Segmentation of Complex Volumetric Filament Networks
David Mayerich,John Keyser +1 more
TL;DR: A novel method to trace filaments through scalar volume data sets that is robust to both noisy and undersampled data is described, and graphics hardware is used to accelerate the tracing algorithm, making it more useful for large data sets.
Proceedings Article
2009 SIAM/ACM Joint Conference on Geometric and Physical Modeling
Wim Bronsvoort,Daniel Gonsor,William C. Regli,Thomas A. Grandine,Jan H. Vandenbrande,Jens Gravesen,John Keyser +6 more
TL;DR: The 2009 SIAM/ACM Joint Conference on Geometric and Physical Modeling as mentioned in this paper was held in San Francisco, from October 5 to October 8, 2009, and attracted high-quality, original research contributions that strive to advance all sorts of aspects of geometric and physical modeling, and their application in design, analysis and manufacturing, as well as in biomedical, geophysical, digital entertainment, and other areas.