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。A Novel Hybrid Approach Based on Deep CNN to Detect Glaucoma Using Fundus Imaging
Rabbia Mahum et al.
ELECTRONICS (2022)
IMNets: Deep Learning Using an Incremental Modular Network Synthesis Approach for Medical Imaging Applications
Redha Ali et al.
APPLIED SCIENCES-BASEL (2022)
Automated Diabetic Retinopathy Detection Using Horizontal and Vertical Patch Division-Based Pre-Trained DenseNET with Digital Fundus Images
Sabiha Gungor Kobat et al.
DIAGNOSTICS (2022)
SKCV: Stratified K-fold cross-validation on ML classifiers for predicting cervical cancer
Sashikanta Prusty et al.
FRONTIERS IN NANOTECHNOLOGY (2022)
ECNet: An evolutionary convolutional network for automated glaucoma detection using fundus images
Deepak Ranjan Nayak et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)
Automated segmentation of the opt ic disc from fundus images using an asymmetric deep learning network
Lei Wang et al.
PATTERN RECOGNITION (2021)
Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images
Danial Sharifrazi et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)
Feature selection with kernelized multi-class support vector machine
Yinan Guo et al.
PATTERN RECOGNITION (2021)
Diabetic Retinopathy Fundus Image Classification and Lesions Localization System Using Deep Learning
Wejdan L. Alyoubi et al.
SENSORS (2021)
A multi-context CNN ensemble for small lesion detection
B. Savelli et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2020)
Ophthalmic diagnosis using deep learning with fundus images - A critical review
Sourya Sengupta et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2020)
Multi-indices quantification of optic nerve head in fundus image via multitask collaborative learning
Rongchang Zhao et al.
MEDICAL IMAGE ANALYSIS (2020)
Siam-U-Net: encoder-decoder siamese network for knee cartilage tracking in ultrasound images
Matteo Dunnhofer et al.
MEDICAL IMAGE ANALYSIS (2020)
An automated early diabetic retinopathy detection through improved blood vessel and optic disc segmentation
Shailesh Kumar et al.
OPTICS AND LASER TECHNOLOGY (2020)
HeadLocNet: Deep convolutional neural networks for accurate classification and multi-landmark localization of head CTs
Dongqing Zhang et al.
MEDICAL IMAGE ANALYSIS (2020)
Multi-scale deep context convolutional neural networks for semantic segmentation
Quan Zhou et al.
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS (2019)
Hemorrhage detection in fundus image based on 2D Gaussian fitting and human visual characteristicse
Jun Wu et al.
OPTICS AND LASER TECHNOLOGY (2019)
Blood vessel segmentation from fundus image by a cascade classification framework
Xiaohong Wang et al.
PATTERN RECOGNITION (2019)
Deep Learning With Asymmetric Connections and Hebbian Updates
Yali Amit
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE (2019)
Diabetic retinopathy detection through novel tetragonal local octa patterns and extreme learning machines
Tahira Nazir et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2019)
Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey
Norah Asiri et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2019)
Brain tumor classification using deep CNN features via transfer learning
S. Deepak et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2019)
Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images
Davood Karimi et al.
MEDICAL IMAGE ANALYSIS (2019)
Color fundus image registration techniques and applications for automated analysis of diabetic retinopathy progression: A review
Sajib Kumar Saha et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2019)
Exudate detection in fundus images using deeply-learnable features
Parham Khojasteh et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2019)
An ensemble deep learning based approach for red lesion detection in fundus images
Jose Ignacio Orlando et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2018)
Deep convolutional learning for Content Based Image Retrieval
Maria Tzelepi et al.
NEUROCOMPUTING (2018)
Deep-learning-based automatic computer-aided diagnosis system for diabetic retinopathy
Romany F. Mansour
BIOMEDICAL ENGINEERING LETTERS (2018)
Retinal vessel segmentation in colour fundus images using Extreme Learning Machine
Chengzhang Zhu et al.
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2017)
A new unified framework for the early detection of the progression to diabetic retinopathy from fundus images
Georgios Leontidis
COMPUTERS IN BIOLOGY AND MEDICINE (2017)
Automatic detection of microaneurysms in colour fundus images for diabetic retinopathy screening
Sarni Suhaila Rahim et al.
NEURAL COMPUTING & APPLICATIONS (2016)
A new supervised retinal vessel segmentation method based on robust hybrid features
Shahab Aslani et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2016)
Hierarchical retinal blood vessel segmentation based on feature and ensemble learning
Shuangling Wang et al.
NEUROCOMPUTING (2015)
Integrated Optic Disc and Cup Segmentation with Deep Learning
Gilbert Lim et al.
2015 IEEE 27TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2015) (2015)
Automated detection of microaneurysms using scale-adapted blob analysis and semi-adapted blob analysis and semi-supervised learning
Kedir M. Adal et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2014)
Detection and classification of retinal lesions for grading of diabetic retinopathy
M. Usman Akram et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2014)
An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading
Balint Antal et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2012)