title: Segmentation and quantification of blood vessels for OCT-based micro-angiograms using hybrid shape/intensity compounding.
abstract: Optical coherence tomography (OCT) based microangiography is capable of visualizing 3D functional blood vessel networks within microcirculatory tissue beds in vivo. To provide the quantitative information of vasculature from the microangiograms such as vessel diameter and morphology, it is necessary to develop efficient vessel segmentation algorithms. In this paper, we propose to develop a hybrid Hessian/intensity based method to segment and quantify shape and diameter of the blood vessels innervating capillary beds that are imaged by functional OCT in vivo. The proposed method utilizes multi-scale Hessian filters to segment tubular structures such as blood vessels, but compounded by the intensity-based segmentation method to mitigate the limitations of Hessian filters' sensitivity to the selection of scale parameters. Such compounding segmentation scheme takes advantage of the morphological nature of Hessian filters while correcting for the scale parameter selection by intensity-based segmentation. The proposed algorithm is tested on a wound healing model and its performance of segmentation vessels is quantified by a publicly available manual segmentation dataset. We believe that this method will play an important role in the quantification of micro-angiograms for microcirculation research in ophthalmology and diagnosing retinal eye diseases involved with microcirculation.
authors.affiliation: Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.
authors.forename: Siavash
authors.initials: S
authors.lastname: Yousefi
authors.affiliation: Department of Bioengineering, University of Washington, Seattle, WA 98195, USA; Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.
authors.forename: Ting
authors.initials: T
authors.lastname: Liu
authors.affiliation: Department of Bioengineering, University of Washington, Seattle, WA 98195, USA. Electronic address: wangrk@uw.edu.
authors.forename: Ruikang K
authors.initials: RK
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D000818:Animals; D016477:Artifacts; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D008297:Male; D008812:Mice, Hairless; D008833:Microcirculation; D055806:Microvessels / Q000473:pathology* / Q000503:physiopathology; D023421:Models, Animal; D018919:Neovascularization, Physiologic; D010363:Pattern Recognition, Automated; D011237:Predictive Value of Tests; D012867:Skin / Q000098:blood supply*; D013997:Time Factors; D041623:Tomography, Optical Coherence / Q000379:methods*; D014945:Wound Healing
keywords: Hessian filters; Intensity-based segmentation; Optical coherence tomography; Optical microangiography; Vessel network