Robust retinal blood vessel segmentation using a patch-based statistical adaptive multi-scale line detector
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Robust retinal blood vessel segmentation using a patch-based statistical adaptive multi-scale line detector
Authors
Keywords
-
Journal
DIGITAL SIGNAL PROCESSING
Volume 139, Issue -, Pages 104075
Publisher
Elsevier BV
Online
2023-05-09
DOI
10.1016/j.dsp.2023.104075
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A novel framework for retinal vessel segmentation using optimal improved frangi filter and adaptive weighted spatial FCM
- (2022) Sakambhari Mahapatra et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Multifilters-Based Unsupervised Method for Retinal Blood Vessel Segmentation
- (2022) Nayab Muzammil et al. Applied Sciences-Basel
- Recent trends and advances in fundus image analysis: A review
- (2022) Shahzaib Iqbal et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Screening of Glaucoma disease from retinal vessel images using semantic segmentation
- (2021) Rakhshanda Imtiaz et al. COMPUTERS & ELECTRICAL ENGINEERING
- Improvement of thin retinal vessel extraction using mean matting method
- (2021) V. Sathananthavathi et al. INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY
- Retina blood vessels segmentation based on the combination of the supervised and unsupervised methods
- (2021) Lingling Fang et al. MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING
- Deep learning architecture based on segmented fundus image features for classification of diabetic retinopathy
- (2021) Sraddha Das et al. Biomedical Signal Processing and Control
- Encoder Enhanced Atrous (EEA) Unet architecture for Retinal Blood vessel segmentation
- (2021) Sathananthavathi V. et al. Cognitive Systems Research
- Width-wise vessel bifurcation for improved retinal vessel segmentation
- (2021) Tariq M. Khan et al. Biomedical Signal Processing and Control
- Fundus image segmentation via hierarchical feature learning
- (2021) Song Guo COMPUTERS IN BIOLOGY AND MEDICINE
- An automated slice sorting technique for multi-slice computed tomography liver cancer images using convolutional network
- (2021) Amandeep Kaur et al. EXPERT SYSTEMS WITH APPLICATIONS
- A new baseline for retinal vessel segmentation: Numerical identification and correction of methodological inconsistencies affecting 100+ papers
- (2021) György Kovács et al. MEDICAL IMAGE ANALYSIS
- Automatic detection of blood vessels and evaluation of retinal disorder from color fundus images
- (2020) Malaya Kumar Nath et al. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
- Retinal vasculature segmentation and measurement framework for color fundus and SLO images
- (2020) Samiksha Pachade et al. Biocybernetics and Biomedical Engineering
- A fractional filter based efficient algorithm for retinal blood vessel segmentation
- (2020) Anil K. Shukla et al. Biomedical Signal Processing and Control
- Automatic classification of retinal blood vessels based on multilevel thresholding and graph propagation
- (2020) Beatriz Remeseiro et al. VISUAL COMPUTER
- Retinal vessel segmentation using multifractal characterization
- (2020) Dhevendra Alagan Palanivel et al. APPLIED SOFT COMPUTING
- Fuzzy based image edge detection algorithm for blood vessel detection in retinal images
- (2020) F. Orujov et al. APPLIED SOFT COMPUTING
- Computer-aided retinal vessel segmentation in retinal images: convolutional neural networks
- (2020) Esin Uysal et al. MULTIMEDIA TOOLS AND APPLICATIONS
- VSSC Net: Vessel Specific Skip chain Convolutional Network for blood vessel segmentation
- (2020) Pearl Mary Samuel et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Unsupervised sorting of retinal vessels using locally consistent Gaussian mixtures
- (2020) D. Relan et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Dense U-net Based on Patch-Based Learning for Retinal Vessel Segmentation
- (2019) Chang Wang et al. Entropy
- Retinal blood vessel extraction employing effective image features and combination of supervised and unsupervised machine learning methods
- (2019) Mahdi Hashemzadeh et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
- DUNet: A deformable network for retinal vessel segmentation
- (2019) Qiangguo Jin et al. KNOWLEDGE-BASED SYSTEMS
- CcNet: A cross-connected convolutional network for segmenting retinal vessels using multi-scale features
- (2019) Shouting Feng et al. NEUROCOMPUTING
- BTS-DSN: Deeply supervised neural network with short connections for retinal vessel segmentation
- (2019) Song Guo et al. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
- GGM classifier with multi-scale line detectors for retinal vessel segmentation
- (2019) Mohammad A. U. Khan et al. Signal Image and Video Processing
- Strided fully convolutional neural network for boosting the sensitivity of retinal blood vessels segmentation
- (2019) Toufique Ahmed Soomro et al. EXPERT SYSTEMS WITH APPLICATIONS
- A Multi-Scale Directional Line Detector for Retinal Vessel Segmentation
- (2019) Ahsan Khawaja et al. SENSORS
- Retinal vessel segmentation using neural network
- (2018) Sumathi Thangaraj et al. IET Image Processing
- Robust retinal blood vessel segmentation using line detectors with multiple masks
- (2018) Birendra Biswal et al. IET Image Processing
- A generalized multi-scale line-detection method to boost retinal vessel segmentation sensitivity
- (2018) Mohammad A. U. Khan et al. PATTERN ANALYSIS AND APPLICATIONS
- Blood vessel segmentation in retinal fundus images using Gabor filters, fractional derivatives, and Expectation Maximization
- (2018) Hugo Aguirre-Ramos et al. APPLIED MATHEMATICS AND COMPUTATION
- A Three-stage Deep Learning Model for Accurate Retinal Vessel Segmentation
- (2018) Zengqiang Yan et al. IEEE Journal of Biomedical and Health Informatics
- A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images
- (2017) Jose Ignacio Orlando et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- 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
- Retinal vessel extraction using Lattice Neural Networks with dendritic processing
- (2015) Roberto Vega et al. COMPUTERS IN BIOLOGY AND MEDICINE
- An effective retinal blood vessel segmentation method using multi-scale line detection
- (2012) Uyen T.V. Nguyen et al. PATTERN RECOGNITION
- Tradeoffs between accuracy measures for electronic health care data algorithms
- (2011) Jessica Chubak et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now