A robust technique based on VLM and Frangi filter for retinal vessel extraction and denoising
出版年份 2018 全文链接
标题
A robust technique based on VLM and Frangi filter for retinal vessel extraction and denoising
作者
关键词
Retinal vessels, Imaging techniques, Blood vessels, Retina, Preprocessing, Employment, Image processing, Support vector machines
出版物
PLoS One
Volume 13, Issue 2, Pages e0192203
出版商
Public Library of Science (PLoS)
发表日期
2018-02-13
DOI
10.1371/journal.pone.0192203
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Retinal blood vessels segmentation by using Gumbel probability distribution function based matched filter
- (2016) Nagendra Pratap Singh et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding
- (2016) Khan BahadarKhan et al. PLoS One
- Unsupervised Retinal Vessel Segmentation Using Combined Filters
- (2016) Wendeson S. Oliveira et al. PLoS One
- Segmentation of retinal vessels by means of directional response vector similarity and region growing
- (2015) István Lázár et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Trainable COSFIRE filters for vessel delineation with application to retinal images
- (2015) George Azzopardi et al. MEDICAL IMAGE ANALYSIS
- A New Approach to Segment Both Main and Peripheral Retinal Vessels Based on Gray-Voting and Gaussian Mixture Model
- (2015) Peishan Dai et al. PLoS One
- Retinal Vessel Segmentation: An Efficient Graph Cut Approach with Retinex and Local Phase
- (2015) Yitian Zhao et al. PLoS One
- Active Contours Driven by Multi-Feature Gaussian Distribution Fitting Energy with Application to Vessel Segmentation
- (2015) Lei Wang et al. PLoS One
- Automated Method for Identification and Artery-Venous Classification of Vessel Trees in Retinal Vessel Networks
- (2014) Vinayak S. Joshi et al. PLoS One
- Retinal vessel segmentation by improved matched filtering: evaluation on a new high-resolution fundus image database
- (2013) Jan Odstrcilik et al. IET Image Processing
- Blood vessel segmentation methodologies in retinal images – A survey
- (2012) M.M. Fraz et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Modified two-dimensional Otsu image segmentation algorithm and fast realisation
- (2012) Q. Chen et al. IET Image Processing
- Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement
- (2012) Peter Bankhead et al. PLoS One
- An approach to localize the retinal blood vessels using bit planes and centerline detection
- (2011) M.M. Fraz et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Digital Ocular Fundus Imaging: A Review
- (2011) Rui Bernardes et al. OPHTHALMOLOGICA
- Segmentation of retinal blood vessels using the radial projection and semi-supervised approach
- (2011) Xinge You et al. PATTERN RECOGNITION
- Retinal Image Analysis Using Curvelet Transform and Multistructure Elements Morphology by Reconstruction
- (2010) M S Miri et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- General Retinal Vessel Segmentation Using Regularization-Based Multiconcavity Modeling
- (2010) Benson S Y Lam et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Registration of OCT fundus images with color fundus photographs based on blood vessel ridges
- (2010) Ying Li et al. OPTICS EXPRESS
- Parallel Multiscale Feature Extraction and Region Growing: Application in Retinal Blood Vessel Detection
- (2009) M.A. Palomera-Perez et al. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE
- An Active Contour Model for Segmenting and Measuring Retinal Vessels
- (2009) B. Al-Diri et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Vessel enhancement filter using directional filter bank
- (2008) Phan T.H. Truc et al. COMPUTER VISION AND IMAGE UNDERSTANDING
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