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International Journal of Biomedical Imaging
Volume 2011, Article ID 920401, 16 pages
http://dx.doi.org/10.1155/2011/920401
Research Article

Automation of Hessian-Based Tubularity Measure Response Function in 3D Biomedical Images

Physiological Imaging Research Laboratory, Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA

Received 4 August 2010; Revised 12 October 2010; Accepted 10 December 2010

Academic Editor: Yangbo Ye

Copyright © 2011 Oleksandr P. Dzyubak and Erik L. Ritman. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [11 citations]

The following is the list of published articles that have cited the current article.

  • Engin Turetken, Carlos Becker, Przemyslaw Glowacki, Fethallah Benmansour, and Pascal Fua, “Detecting Irregular Curvilinear Structures in Gray Scale and Color Imagery Using Multi-directional Oriented Flux,” 2013 IEEE International Conference on Computer Vision, pp. 1553–1560, . View at Publisher · View at Google Scholar
  • Andrzej Materka, Marek Kocinski, Jacek Blumenfeld, Artur Klepaczko, Andreas Deistung, Barthelemy Serres, and Jurgen R. Reichenbach, “Automated modeling of tubular blood vessels in 3D MR angiography images,” 2015 9th International Symposium on Image and Signal Processing and Analysis (ISPA), pp. 54–59, . View at Publisher · View at Google Scholar
  • Bruno C. Gregorio da Silva, Ricardo J. Ferrari, Juliana Carvalho-Tavares, Bruno C. Gregorio da Silva, Ricardo J. Ferrari, and Juliana Carvalho Tavares, “Detection of Leukocytes in Intravital Video Microscopy Based on the Analysis of Hessian Matrix Eigenvalues,” 2015 28th SIBGRAPI Conference on Graphics, Patterns and Images, pp. 345–352, . View at Publisher · View at Google Scholar
  • Jacek Blumenfeld, Marek Kocinski, and Andrzej Materka, “A centerline-based algorithm for estimation of blood vessels radii from 3D raster images,” 2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), pp. 38–43, . View at Publisher · View at Google Scholar
  • Marek Kocinski, Andrzej Materka, Andreas Deistung, and Jurgen R. Reichenbach, “Centerline-based surface modeling of blood-vessel trees in cerebral 3D MRA,” 2016 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), pp. 85–90, . View at Publisher · View at Google Scholar
  • Yue Huang, Xuezhi Sun, Guangshu Hu, and Yunying Huang, “An automated approach for cerebral microvascularity labeling in microscopy images,” Microscopy Research and Technique, vol. 75, no. 3, pp. 388–396, 2011. View at Publisher · View at Google Scholar
  • Xiangang Jiang, and Yunli Qiu, “An extraction method of cerebral vessels based on multi-threshold otsu classification and hessian matrix enhancement filtering,” Lecture Notes in Electrical Engineering, vol. 269, pp. 2675–2682, 2014. View at Publisher · View at Google Scholar
  • Richard F. Spaide, “Retinal Vascular Cystoid Macular Edema,” Retina, vol. 36, no. 10, pp. 1823–1842, 2016. View at Publisher · View at Google Scholar
  • Martin Trapp, Florian Schulze, Alexey A. Novikov, Laszlo Tirian, Barry J. Dickson, and Katja Bühler, “Adaptive and Background-Aware GAL4 Expression Enhancement of Co-registered Confocal Microscopy Images,” Neuroinformatics, 2016. View at Publisher · View at Google Scholar
  • Paulo Guilherme de Lima Freire, Bruno César Gregório da Silva, Carlos Henrique Villa Pinto, Camilo Aparecido Ferri Moreira, and Ricardo José Ferrari, “Midsaggital Plane Detection in Magnetic Resonance Images Using Phase Congruency, Hessian Matrix and Symmetry Information: A Comparative Study,” Computational Science and Its Applications – ICCSA 2018, vol. 10960, pp. 245–260, 2018. View at Publisher · View at Google Scholar
  • Bruno C. Gregório da Silva, Juliana Carvalho-Tavares, and Ricardo J. Ferrari, “Detecting and tracking leukocytes in intravital video microscopy using a Hessian-based spatiotemporal approach,” Multidimensional Systems and Signal Processing, 2018. View at Publisher · View at Google Scholar