Keyphrases
Age-related Macular Degeneration
22%
Angle-closure Glaucoma
16%
Anterior Chamber Angle
20%
Anterior Segment OCT
17%
Anterior Segment Optical Coherence Tomography (AS-OCT)
35%
Automatic Detection
26%
Blood Vessels
20%
Cataract
19%
Classification Basis
15%
Computer-aided Diagnosis (CADx)
18%
Computer-aided Diagnosis System
17%
Cup-to-disc Ratio
47%
Deep Learning
42%
Diabetic Retinopathy
14%
Fundus Image
81%
Gallbladder
22%
Generative Adversarial Networks
19%
Glaucoma
64%
Glaucoma Classification
19%
Glaucoma Detection
45%
Glaucoma Diagnosis
48%
Glaucoma Screening
26%
Image-based
21%
Macula
16%
Medical Image Segmentation
16%
Nuclear Cataract
32%
Ocular Diseases
18%
Opacity
14%
Ophthalmologist
16%
Optic Cup
79%
Optic Cup Segmentation
27%
Optic Disc
75%
Optic Disc Segmentation
35%
Optical Coherence Tomography
46%
Optical Coherence Tomography Images
60%
Pathologic Myopia
21%
Peripapillary Atrophy
15%
Ratio Estimation
15%
Retina
22%
Retinal Fundus Images
64%
Retinal Image
53%
Singapore
18%
Slit-lamp Images
14%
Speckle Reduction
16%
State-of-the-art Techniques
24%
Sub-pixel Classification
23%
Superpixel
23%
Tortuosity
15%
U-Net
15%
Wireless Capsule Endoscopy
15%
Computer Science
Aided Diagnosis
32%
Annotation
17%
Attention (Machine Learning)
19%
Automatic Detection
13%
Automatic Segmentation
11%
Context Information
11%
Contrastive Learning
9%
Convolutional Network
9%
Convolutional Neural Network
47%
Convolutional Neural Network
9%
Deep Learning
58%
Deep Neural Network
10%
Disease Progression
9%
Experimental Result
100%
Feature Extraction
15%
Feature Selection
15%
Generative Adversarial Networks
21%
Image Analysis
34%
Image Classification
23%
Image Enhancement
9%
Image Quality
24%
Image Segmentation
36%
Imaging Modality
19%
Instance Learning
9%
Learning Approach
9%
Learning Framework
18%
local feature
15%
Medical Imaging
14%
Network Segmentation
11%
Neural Network
16%
Object Detection
9%
Reference Image
9%
Robot
17%
Segmentation Method
11%
Segmentation Performance
16%
Segmentation Task
8%
Sparsity
10%
Speckle Reduction
18%
super resolution
9%
Superpixel
40%
Support Vector Machine
23%
Support Vector Machine
23%
Surgical Training
21%
Training Data
14%
Training Sample
8%
Transfer Learning
9%
U-Net
14%
Vessel Segmentation
10%
Visual Feature
24%
Visual Impairment
13%
