title: MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE.
abstract: Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy. A robust denoising process is necessary in order to extract accurate vascular morphology information. For this purpose, we propose a multiscale tensor with anisotropic diffusion model which progressively and adaptively updates the amount of smoothing while preserving vessel boundaries accurately. Based on a coherency enhancing flow with planar confidence measure and fused 3D structure information, our method integrates multiple scales for microvasculature preservation and noise removal membrane structures. Experimental results on simulated synthetic images and epifluorescence images show the advantage of our improvement over other related diffusion filters. We further show that the proposed multiscale integration approach improves denoising accuracy of different tensor diffusion methods to obtain better microvasculature segmentation.
authors.affiliation: Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211 USA.
authors.forename: V B S
authors.initials: VB
authors.lastname: Prasath
authors.affiliation: Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211 USA.
authors.forename: R
authors.initials: R
authors.lastname: Pelapur
authors.affiliation: Department of Medical Pharmacology and Physiology, University of Missouri-Columbia, Columbia, MO 65211 USA ; National Center for Gender Physiology, University of Missouri-Columbia, Columbia, MO 65211 USA ; Research Service, Harry S. Truman Memorial Veterans Hospital, Columbia, MO 65201 USA.
authors.forename: O V
authors.initials: OV
authors.lastname: Glinskii
authors.affiliation: National Center for Gender Physiology, University of Missouri-Columbia, Columbia, MO 65211 USA ; Department of Pathology and Anatomical Sciences, University of Missouri-Columbia, Columbia, MO 65211 USA ; Research Service, Harry S. Truman Memorial Veterans Hospital, Columbia, MO 65201 USA.
authors.forename: V V
authors.initials: VV
authors.lastname: Glinsky
authors.affiliation: Department of Medical Pharmacology and Physiology, University of Missouri-Columbia, Columbia, MO 65211 USA ; National Center for Gender Physiology, University of Missouri-Columbia, Columbia, MO 65211 USA.
authors.forename: V H
authors.initials: VH
authors.lastname: Huxley
authors.affiliation: Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211 USA.
authors.forename: K
authors.initials: K
authors.lastname: Palaniappan
keywords: Fluorescence; anisotropic filtering; denoising; microscopy; multiscale; vasculature