title: Random Forests for Dura Mater Microvasculature Segmentation Using Epifluorescence Images.
abstract: Automatic segmentation of microvascular structures is a critical step in quantitatively characterizing vessel remodeling and other physiological changes in the dura mater or other tissues. We developed a supervised random forest (RF) classifier for segmenting thin vessel structures using multiscale features based on Hessian, oriented second derivatives, Laplacian of Gaussian and line features. The latter multiscale line detector feature helps in detecting and connecting faint vessel structures that would otherwise be missed. Experimental results on epifluorescence imagery show that the RF approach produces foreground vessel regions that are almost 20 and 25 percent better than Niblack and Otsu threshold-based segmentations respectively.
authors.affiliation: Computational Imaging and VisAnalysis (CIVA) Lab, Department of Computer Science, Columbia, MO 65201 USA.
authors.forename: Yasmin M
authors.initials: YM
authors.lastname: Kassim
authors.affiliation: Computational Imaging and VisAnalysis (CIVA) Lab, Department of Computer Science, Columbia, MO 65201 USA.
authors.forename: V B
authors.initials: VB
authors.lastname: Surya Prasath
authors.affiliation: Computational Imaging and VisAnalysis (CIVA) Lab, Department of Computer Science, Columbia, MO 65201 USA.
authors.forename: Rengarajan
authors.initials: R
authors.lastname: Pelapur
authors.affiliation: Research Service, Harry S. Truman Memorial Veterans Hospital, Columbia, MO 65201 USA; Department of Medical Pharmacology and Physiology, University of Missouri-Columbia, MO 65211 USA.
authors.forename: Olga V
authors.initials: OV
authors.lastname: Glinskii
authors.affiliation: Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Harvard TH Chan School of Public Health, Harvard University, Boston, USA.
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Maude
authors.affiliation: Research Service, Harry S. Truman Memorial Veterans Hospital, Columbia, MO 65201 USA; Department of Pathology and Anatomical Sciences, University of Missouri-Columbia, MO 65211 USA.
authors.forename: Vladislav V
authors.initials: VV
authors.lastname: Glinsky
authors.affiliation: Department of Medical Pharmacology and Physiology, University of Missouri-Columbia, MO 65211 USA; National Center for Gender Physiology, University of Missouri-Columbia, MO 65211 USA.
authors.forename: Virginia H
authors.initials: VH
authors.lastname: Huxley
authors.affiliation: Computational Imaging and VisAnalysis (CIVA) Lab, Department of Computer Science, Columbia, MO 65201 USA.
authors.forename: Kannappan
authors.initials: K
authors.lastname: Palaniappan
mesh_terms: D000465:Algorithms; D000818:Animals; D004388:Dura Mater / Q000033:anatomy & histology / Q000098:blood supply*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D051379:Mice; D055806:Microvessels / Q000033:anatomy & histology* / Q000502:physiology; D061848:Optical Imaging / Q000379:methods* / Q000401:mortality; D066253:Vascular Remodeling