title: Level Sets for Retinal Vasculature Segmentation Using Seeds from Ridges and Edges from Phase Maps.
abstract: In this paper, we present a novel modification to level set based automatic retinal vasculature segmentation approaches. The method introduces ridge sample extraction for sampling the vasculature centerline and phase map based edge detection for accurate region boundary detection. Segmenting the vasculature in fundus images has been generally challenging for level set methods employing classical edge-detection methodologies. Furthermore, initialization with seed points determined by sampling vessel centerlines using ridge identification makes the method completely automated. The resulting algorithm is able to segment vasculature in fundus imagery accurately and automatically. Quantitative results supplemented with visual ones support this observation. The methodology could be applied to the broader class of vessel segmentation problems encountered in medical image analytics.
authors: Computer Engineering Department, Karadeniz Technical University, Turkey ; Cognitive Systems Laboratory, Northeastern University, Boston MA, USA.
authors: Bekir
authors: B
authors: Dizdaroğlu
authors: Cognitive Systems Laboratory, Northeastern University, Boston MA, USA.
authors: Esra
authors: E
authors: Ataer-Cansizoglu
authors: Martinos Imaging Center, Massachusetts General Hospital, Boston MA, USA.
authors: Jayashree
authors: J
authors: Kalpathy-Cramer
authors: Department of Ophthalmology, Oregon Health & Science University, Portland OR, USA.
authors: Katie
authors: K
authors: Keck
authors: Department of Ophthalmology, Oregon Health & Science University, Portland OR, USA ; Department of Medical Informatics, Oregon Health & Science University, Portland, OR, USA.
authors: Michael F
authors: MF
authors: Chiang
authors: Cognitive Systems Laboratory, Northeastern University, Boston MA, USA.
authors: Deniz
authors: D
authors: Erdogmus
keywords: Fundus image; level sets; phase map for edge detection; principal curves as ridges; retinal vasculature analysis; vessel segmentation