Segmentation and feature extraction of retinal vascular morphology

No abstract is available for this paper.

• Publication year

  2017

• Venue

  Medical Imaging

• Publication date

  2017-02-24

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1117/12.2253744
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A Cross-Modality Learning Approach for Vessel Segmentation in Retinal Images

  2016influential reference
• Deep Learning

  2015cited by this paper
• QUARTZ: Quantitative Analysis of Retinal Vessel Topology and size - An automated system for quantification of retinal vessels morphology

  2015cited by this paper
• Trainable COSFIRE filters for vessel delineation with application to retinal images

  2015cited by this paper
• Adam: A Method for Stochastic Optimization

  2014cited by this paper
• Representation Learning: A Review and New Perspectives

  2012cited by this paper
• Blood vessel segmentation methodologies in retinal images - A survey

  2012cited by this paper
• An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation

  2012cited by this paper
• Flexible, High Performance Convolutional Neural Networks for Image Classification

  2011cited by this paper
• A committee of neural networks for traffic sign classification

  2011cited by this paper
• Retinal Imaging and Image Analysis

  2010cited by this paper
• Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification

  2007cited by this paper
• A Fast Learning Algorithm for Deep Belief Nets

  2006cited by this paper
• Ridge-based vessel segmentation in color images of the retina

  2004cited by this paper
• Retinal arteriolar narrowing and risk of coronary heart disease in men and women. The Atherosclerosis Risk in Communities Study.

  2002cited by this paper
• Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response

  2000cited by this paper

• Can we make a more efficient U-Net for blood vessel segmentation?

  2020cites this paper
• Sparsely Activated Networks: A new method for decomposing and compressing data

  2019cites this paper
• Application of Deep Learning in Fundus Image Processing for Ophthalmic Diagnosis -- A Review.

  2019cites this paper
• Deep Learning in Cardiology

  2019cites this paper
• A Review on Image Segmentation Techniques and Performance Measures

  2018cites this paper
• Ophthalmic Diagnosis and Deep Learning - A Survey

  2018cites this paper
• Ophthalmic diagnosis using deep learning with fundus images - A critical review

  2018cites this paper
• PixelBNN: Augmenting the PixelCNN with Batch Normalization and the Presentation of a Fast Architecture for Retinal Vessel Segmentation

  2017cites this paper
• Automated arteriole and venule classification using deep learning for retinal images from the UK Biobank cohort

  2017cites this paper