4.6 Review

Retinal Vessel Segmentation Using Deep Learning: A Review

Related references

Note: Only part of the references are listed.
Article Computer Science, Software Engineering

FRNet: an end-to-end feature refinement neural network for medical image segmentation

Dan Wang et al.

Summary: The paper introduces a lightweight end-to-end feature refinement network (FRNet) to address the issue of spatial information loss in medical image segmentation. By incorporating spatial refinement path, semantic refinement path, and feature adaptive fusion block (FAF block), high accuracy is achieved in different tasks without the need for post-processing.

VISUAL COMPUTER (2021)

Article Computer Science, Information Systems

Computer-aided retinal vessel segmentation in retinal images: convolutional neural networks

Esin Uysal et al.

Summary: This study proposes a hybrid method utilizing a deep learning model and data augmentation techniques to automatically extract retinal blood vessels. Testing in the DRIVE database showed that the system achieved high accuracy and precision in vessel extraction.

MULTIMEDIA TOOLS AND APPLICATIONS (2021)

Review Computer Science, Artificial Intelligence

Applications of deep learning in fundus images: A review

Tao Li et al.

Summary: The use of deep learning in fundus image analysis is increasingly popular due to its powerful performance in various applications. This review paper introduces 143 application papers and 33 publicly available datasets, providing summaries, analyses, and solutions for common limitations in each task. The authors also promise to regularly update the state-of-the-art results and newly-released datasets on their GitHub page to keep up with the rapid development in the field.

MEDICAL IMAGE ANALYSIS (2021)

Article Computer Science, Artificial Intelligence

A refined equilibrium generative adversarial network for retinal vessel segmentation

Yukun Zhou et al.

Summary: This study presents an end-to-end synthetic neural network to enhance segmentation of elusive vessels, achieving satisfactory results by maximizing multi-scale feature representation. SEGAN, MSFRB, and AM all contribute to the network's performance improvements according to various evaluations.

NEUROCOMPUTING (2021)

Article Biochemical Research Methods

Multi-Label Classification Scheme Based on Local Regression for Retinal Vessel Segmentation

Beiji Zou et al.

Summary: This paper proposes a local regression scheme and a multi-label classification method to segment small retinal vessels in fundus images. By determining the multi-label based on vessel pattern and training a CNN, the method effectively locates and generates retinal vessel images.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2021)

Article Automation & Control Systems

Lightweight Attention Convolutional Neural Network for Retinal Vessel Image Segmentation

Xiang Li et al.

Summary: This article introduces a convolutional neural network integrated with an attention mechanism for retinal vessel image segmentation, showing superior performance in experiments and significantly reducing the number of parameters.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)

Review Computer Science, Artificial Intelligence

A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification

Muthu Rama Krishnan Mookiah et al.

Summary: The paper reviews 158 papers published between 2012 and 2020 on retinal blood vessel segmentation and classification, focusing on methods based on machine and deep learning. The methods are divided into different categories for discussion, including evaluation of advantages and limitations, summarizing results, and attempting to assess the accuracy improvement of DL methods.

MEDICAL IMAGE ANALYSIS (2021)

Article Computer Science, Artificial Intelligence

SCS-Net: A Scale and Context Sensitive Network for Retinal Vessel Segmentation

Huisi Wu et al.

Summary: Segmenting retinal vessels accurately is crucial for detecting and diagnosing eye diseases, but it is challenging due to scale variations and complex anatomical contexts. This study proposes a novel scale and context sensitive network (SCS-Net) with modules like scale-aware feature aggregation and adaptive feature fusion to achieve better segmentation performance in challenging cases with large scale variations and complex context environments.

MEDICAL IMAGE ANALYSIS (2021)

Article Computer Science, Artificial Intelligence

A hybrid deep segmentation network for fundus vessels via deep-learning framework

Lei Yang et al.

Summary: This paper proposes a new hybrid deep image segmentation method for fundus vessels that utilizes a multitask segmentation network and a fusion network to accurately segment both thick and thin vessels from fundus images. An effective loss function is designed to address the imbalanced ratio between thick and thin vessels, and an improved U-net network model is used to ensure segmentation performance.

NEUROCOMPUTING (2021)

Article Computer Science, Information Systems

Accurate Retinal Vessel Segmentation in Color Fundus Images via Fully Attention-Based Networks

Kaiqi Li et al.

Summary: This study introduces a Fully Attention-based Network (FANet) utilizing attention mechanisms to adaptively learn and aggregate multi-scale information for retinal vessel segmentation. The experiments demonstrate its effectiveness in identifying irregular, noisy, and multi-scale background information.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2021)

Article Biochemical Research Methods

A Global and Local Enhanced Residual U-Net for Accurate Retinal Vessel Segmentation

Sheng Lian et al.

Summary: This study proposes a Global and Local enhanced residual U-nEt (GLUE) method for accurate retinal vessel segmentation, which combines global and local information for improved performance. Experimental results demonstrate that the method consistently enhances segmentation accuracy over the conventional U-Net.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2021)

Article Computer Science, Information Systems

CSU-Net: A Context Spatial U-Net for Accurate Blood Vessel Segmentation in Fundus Images

Bo Wang et al.

Summary: A novel CSU-Net model is proposed for blood vessel segmentation, utilizing a two-channel encoder and feature fusion, attention skip modules to improve segmentation accuracy. Evaluation on three public datasets demonstrates that CSU-Net outperforms current state-of-the-art methods.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2021)

Article Computer Science, Information Systems

Contrast Enhancement of Fundus Images by Employing Modified PSO for Improving the Performance of Deep Learning Models

Khursheed Aurangzeb et al.

Summary: Computer-Aided diagnosis is widely used for detecting diseases, and enhancing fundus images can help improve the visibility of minor changes in retinal vasculature, thereby increasing the accuracy of deep learning models for diagnosing critical diseases.

IEEE ACCESS (2021)

Article Computer Science, Artificial Intelligence

CcNet: A cross-connected convolutional network for segmenting retinal vessels using multi-scale features

Shouting Feng et al.

NEUROCOMPUTING (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Parallel Architecture of Fully Convolved Neural Network for Retinal Vessel Segmentation

V. Sathananthavathi et al.

JOURNAL OF DIGITAL IMAGING (2020)

Article Engineering, Electrical & Electronic

Dilated Deep Neural Network for Segmentation of Retinal Blood Vessels in Fundus Images

Raj Biswas et al.

IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING (2020)

Article Engineering, Biomedical

Multi-path convolutional neural network in fundus segmentation of blood vessels

Chun Tian et al.

BIOCYBERNETICS AND BIOMEDICAL ENGINEERING (2020)

Article Computer Science, Artificial Intelligence

NFN plus : A novel network followed network for retinal vessel segmentation

Yicheng Wu et al.

NEURAL NETWORKS (2020)

Article Computer Science, Interdisciplinary Applications

A size-invariant convolutional network with dense connectivity applied to retinal vessel segmentation measured by a unique index

Zhongshuo Zhuo et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2020)

Article Computer Science, Interdisciplinary Applications

Dense Dilated Network With Probability Regularized Walk for Vessel Detection

Lei Mou et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

SUD-GAN: Deep Convolution Generative Adversarial Network Combined with Short Connection and Dense Block for Retinal Vessel Segmentation

Tiejun Yang et al.

JOURNAL OF DIGITAL IMAGING (2020)

Article Computer Science, Artificial Intelligence

Multi-scale channel importance sorting and spatial attention mechanism for retinal vessels segmentation

Xianlun Tang et al.

APPLIED SOFT COMPUTING (2020)

Proceedings Paper Acoustics

DENSE RESIDUAL NETWORK FOR RETINAL VESSEL SEGMENTATION

Changlu Guo et al.

2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (2020)

Proceedings Paper Computer Science, Artificial Intelligence

Fundus Image Segmentation Based on Improved Generative Adversarial Network for Retinal Vessel Analysis

Jin He et al.

2020 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND BIG DATA (ICAIBD 2020) (2020)

Article Computer Science, Information Systems

Hard Attention Net for Automatic Retinal Vessel Segmentation

Dongyi Wang et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2020)

Article Computer Science, Information Systems

Retinal Vessel Segmentation Combined With Generative Adversarial Networks and Dense U-Net

Xiaoyu Guo et al.

IEEE ACCESS (2020)

Proceedings Paper Engineering, Biomedical

ERRORNET: LEARNING ERROR REPRESENTATIONS FROM LIMITED DATA TO IMPROVE VASCULAR SEGMENTATION

Nima Tajbakhsh et al.

2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020) (2020)

Proceedings Paper Engineering, Biomedical

A DATA-AWARE DEEP SUPERVISED METHOD FOR RETINAL VESSEL SEGMENTATION

Suraj Mishra et al.

2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020) (2020)

Proceedings Paper Engineering, Biomedical

LEARNING TO SEGMENT VESSELS FROM POORLY ILLUMINATED FUNDUS IMAGES

Vibha Nasery et al.

2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020) (2020)

Proceedings Paper Computer Science, Theory & Methods

Dense Residual Convolutional Auto Encoder For Retinal Blood Vessels Segmentation

R. Adarsh et al.

2020 6TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING AND COMMUNICATION SYSTEMS (ICACCS) (2020)

Article Computer Science, Information Systems

Attention Guided U-Net With Atrous Convolution for Accurate Retinal Vessels Segmentation

Yan Lv et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

Chaining a U-Net With a Residual U-Net for Retinal Blood Vessels Segmentation

Gendry Alfonso Francia et al.

IEEE ACCESS (2020)

Article Computer Science, Artificial Intelligence

Deep Retinal Image Segmentation With Regularization Under Geometric Priors

Venkateswararao Cherukuri et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2020)

Review Computer Science, Information Systems

Application of deep learning for retinal image analysis: A review

Maryam Badar et al.

COMPUTER SCIENCE REVIEW (2020)

Article Computer Science, Information Systems

Deep Guidance Network for Biomedical Image Segmentation

Pengshuai Yin et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

Residual Connection-Based Encoder Decoder Network (RCED-Net) for Retinal Vessel Segmentation

Tariq Mahmood Khan et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

Automatic Retinal Vessel Segmentation via Deeply Supervised and Smoothly Regularized Network

Yi Lin et al.

IEEE ACCESS (2019)

Article Computer Science, Theory & Methods

A Survey on Deep Learning: Algorithms, Techniques, and Applications

Samira Pouyanfar et al.

ACM COMPUTING SURVEYS (2019)

Article Computer Science, Artificial Intelligence

DUNet: A deformable network for retinal vessel segmentation

Qiangguo Jin et al.

KNOWLEDGE-BASED SYSTEMS (2019)

Article Computer Science, Information Systems

BTS-DSN: Deeply supervised neural network with short connections for retinal vessel segmentation

Song Guo et al.

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2019)

Article Computer Science, Interdisciplinary Applications

Scale-space approximated convolutional neural networks for retinal vessel segmentation

Kyoung Jin Noh et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2019)

Article Biology

Multi-proportion channel ensemble model for retinal vessel segmentation

Peng Tang et al.

COMPUTERS IN BIOLOGY AND MEDICINE (2019)

Article Computer Science, Information Systems

A Three-Stage Deep Learning Model for Accurate Retinal Vessel Segmentation

Zengqiang Yan et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2019)

Article Computer Science, Artificial Intelligence

Strided fully convolutional neural network for boosting the sensitivity of retinal blood vessels segmentation

Toufique Ahmed Soomro et al.

EXPERT SYSTEMS WITH APPLICATIONS (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Towards Accurate Segmentation of Retinal Vessels and the Optic Disc in Fundoscopic Images with Generative Adversarial Networks

Jaemin Son et al.

JOURNAL OF DIGITAL IMAGING (2019)

Review Computer Science, Artificial Intelligence

A review of retinal blood vessels extraction techniques: challenges, taxonomy, and future trends

Khan Bahadar Khan et al.

PATTERN ANALYSIS AND APPLICATIONS (2019)

Article Computer Science, Artificial Intelligence

Deep vessel segmentation by learning graphical connectivity

Seung Yeon Shin et al.

MEDICAL IMAGE ANALYSIS (2019)

Article Computer Science, Information Systems

Retinal Vessels Segmentation Based on Dilated Multi-Scale Convolutional Neural Network

Yun Jiang et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

Micro-Vessel Image Segmentation Based on the AD-UNet Model

Zhongming Luo et al.

IEEE ACCESS (2019)

Proceedings Paper Computer Science, Theory & Methods

U-GAN: Generative Adversarial Networks with U-Net for Retinal Vessel Segmentation

Cong Wu et al.

14TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND EDUCATION (ICCSE 2019) (2019)

Article Computer Science, Information Systems

A Fundus Retinal Vessels Segmentation Scheme Based on the Improved Deep Learning U-Net Model

Xiuqin Pan et al.

IEEE ACCESS (2019)

Proceedings Paper Engineering, Biomedical

SD-Unet: A Structured Dropout U-Net for Retinal Vessel Segmentation

Changlu Guo et al.

2019 IEEE 19TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE) (2019)

Proceedings Paper Imaging Science & Photographic Technology

RESIDUAL U-NET FOR RETINAL VESSEL SEGMENTATION

Di Li et al.

2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) (2019)

Article Computer Science, Information Systems

S-UNet: A Bridge-Style U-Net Framework With a Saliency Mechanism for Retinal Vessel Segmentation

Jingfei Hu et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

A New Hybrid Algorithm for Retinal Vessels Segmentation on Fundus Images

Dhimas Arief Dharmawan et al.

IEEE ACCESS (2019)

Article Computer Science, Information Systems

Impact of Image Enhancement Technique on CNN Model for Retinal Blood Vessels Segmentation

Toufique Ahmed Soomro et al.

IEEE ACCESS (2019)

Review Computer Science, Information Systems

Deep Learning Models for Retinal Blood Vessels Segmentation: A Review

Toufique Ahmed Soomro et al.

IEEE ACCESS (2019)

Article Engineering, Biomedical

Retinal blood vessel segmentation using fully convolutional network with transfer learning

Zhexin Jiang et al.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2018)

Article Computer Science, Artificial Intelligence

Retinal vessel segmentation based on Fully Convolutional Neural Networks

Americo Oliveira et al.

EXPERT SYSTEMS WITH APPLICATIONS (2018)

Article Engineering, Biomedical

Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation

Zengqiang Yan et al.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2018)

Article Computer Science, Artificial Intelligence

Synthesizing retinal and neuronal images with generative adversarial nets

He Zhao et al.

MEDICAL IMAGE ANALYSIS (2018)

Article Computer Science, Interdisciplinary Applications

A novel retinal vessel detection approach based on multiple deep convolution neural networks

Yanhui Guo et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2018)

Proceedings Paper Computer Science, Theory & Methods

Deep Supervision with Additional Labels for Retinal Vessel Segmentation Task

Yishuo Zhang et al.

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT II (2018)

Proceedings Paper Computer Science, Theory & Methods

Towards a Glaucoma Risk Index Based on Simulated Hemodynamics from Fundus Images

Jose Ignacio Orlando et al.

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT II (2018)

Proceedings Paper Computer Science, Theory & Methods

A No-Reference Quality Metric for Retinal Vessel Tree Segmentation

Adrian Galdran et al.

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT I (2018)

Article Computer Science, Artificial Intelligence

A survey on deep learning in medical image analysis

Geert Litjens et al.

MEDICAL IMAGE ANALYSIS (2017)

Article Engineering, Biomedical

Multi-level deep supervised networks for retinal vessel segmentation

Juan Mo et al.

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY (2017)

Article Computer Science, Interdisciplinary Applications

Segmentation of optic disc, fovea and retinal vasculature using a single convolutional neural network

Jen Hong Tan et al.

JOURNAL OF COMPUTATIONAL SCIENCE (2017)

Article Multidisciplinary Sciences

Retinal Vessel Segmentation via Structure Tensor Coloring and Anisotropy Enhancement

Mehmet Nergiz et al.

SYMMETRY-BASEL (2017)

Article Engineering, Electrical & Electronic

Multi-level deep neural network for efficient segmentation of blood vessels in fundus images

L. Ngo et al.

ELECTRONICS LETTERS (2017)

Article Engineering, Biomedical

A generalized method for the detection of vascular structure in pathological retinal images

Jaskirat Kaur et al.

BIOCYBERNETICS AND BIOMEDICAL ENGINEERING (2017)

Article Computer Science, Artificial Intelligence

Optimized clinical segmentation of retinal blood vessels by using combination of adaptive filtering, fuzzy entropy and skeletonization

Khosro Rezaee et al.

APPLIED SOFT COMPUTING (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Densely Connected Convolutional Networks

Gao Huang et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Deformable Convolutional Networks

Jifeng Dai et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)

Article Biology

Blood vessel extraction and optic disc removal using curvelet transform and kernel fuzzy c-means

Sudeshna Sil Kar et al.

COMPUTERS IN BIOLOGY AND MEDICINE (2016)

Article Computer Science, Interdisciplinary Applications

Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores

Jiong Zhang et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)

Article Computer Science, Interdisciplinary Applications

Segmenting Retinal Blood Vessels With Deep Neural Networks

Pawel Liskowski et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)

Article Computer Science, Artificial Intelligence

Tree Topology Estimation

Rolando Estrada et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2015)

Article Computer Science, Artificial Intelligence

ImageNet Large Scale Visual Recognition Challenge

Olga Russakovsky et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2015)

Review Computer Science, Artificial Intelligence

Deep learning in neural networks: An overview

Juergen Schmidhuber

NEURAL NETWORKS (2015)

Proceedings Paper Computer Science, Artificial Intelligence

Biologically-Inspired Supervised Vasculature Segmentation in SLO Retinal Fundus Images

Samaneh Abbasi-Sureshjani et al.

IMAGE ANALYSIS AND RECOGNITION (ICIAR 2015) (2015)

Article Radiology, Nuclear Medicine & Medical Imaging

Using morphological transforms to enhance the contrast of medical images

Hamid Hassanpour et al.

EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE (2015)

Article Engineering, Biomedical

Computerized screening of diabetic retinopathy employing blood vessel segmentation in retinal images

S. Wilfred Franklin et al.

BIOCYBERNETICS AND BIOMEDICAL ENGINEERING (2014)

Article Biochemical Research Methods

True color scanning laser ophthalmoscopy and optical coherence tomography handheld probe

Francesco LaRocca et al.

BIOMEDICAL OPTICS EXPRESS (2014)

Article Engineering, Biomedical

Automatic wavelet-based retinal blood vessels segmentation and vessel diameter estimation

Abdolhossein Fathi et al.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2013)

Article Computer Science, Interdisciplinary Applications

Blood vessel segmentation methodologies in retinal images - A survey

M. M. Fraz et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2012)

Article Endocrinology & Metabolism

Global Prevalence and Major Risk Factors of Diabetic Retinopathy

Joanne W. Y. Yau et al.

DIABETES CARE (2012)

Article Engineering, Biomedical

An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation

Muhammad Moazam Fraz et al.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2012)

Article Computer Science, Artificial Intelligence

Retinal vessel segmentation using a probabilistic tracking method

Yi Yin et al.

PATTERN RECOGNITION (2012)

Article Computer Science, Artificial Intelligence

Segmentation of retinal blood vessels using the radial projection and semi-supervised approach

Xinge You et al.

PATTERN RECOGNITION (2011)

Article Computer Science, Artificial Intelligence

The Graph Neural Network Model

Franco Scarselli et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS (2009)

Article Automation & Control Systems

Enhancement of blood vessels in digital fundus photographs via the application of multiscale line operators

D. J. J. Farnell et al.

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS (2008)

Article Biology

An improved matched filter for blood vessel detection of digital retinal images

Mohammed Al-Rawi et al.

COMPUTERS IN BIOLOGY AND MEDICINE (2007)

Article Computer Science, Interdisciplinary Applications

Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification

Joao V. B. Soares et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2006)

Article Multidisciplinary Sciences

Reducing the dimensionality of data with neural networks

G. E. Hinton et al.

SCIENCE (2006)

Article Computer Science, Artificial Intelligence

A fast learning algorithm for deep belief nets

Geoffrey E. Hinton et al.

NEURAL COMPUTATION (2006)

Article Computer Science, Interdisciplinary Applications

Ridge-based vessel segmentation in color images of the retina

J Staal et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2004)

Article Computer Science, Artificial Intelligence

Predictions of a model of spatial attention using sum- and max-pooling functions

FH Hamker

NEUROCOMPUTING (2004)