Keyphrases
Corneal Endothelial Cell Segmentation
100%
Transformer
54%
Generative Adversarial Networks
50%
Transformer Network
41%
Medical Image Segmentation
41%
Long-range Dependence
39%
Low Contrast
37%
State-of-the-art Techniques
36%
Corneal Endothelial Cells
34%
Hybrid Transformer
31%
Experiment Results
31%
Specular Microscope
25%
Boundary Perception
25%
Multi-scale Perception
25%
Confocal Microscope
25%
Modality Transfer
25%
Spatial Uncertainty
25%
Uncertainty-aware
25%
Prior-Guided
25%
Global-local Transformer
25%
Local Transformer
25%
Uncertainty Maps
25%
Structure Segmentation
25%
Network Structure
25%
Structural Prior
25%
Uncertainty Estimation
25%
Segmentation-based
25%
Self-attention Network
25%
Spatial Attention
25%
Multi-branch
25%
Physiological Structure
25%
Medical Image
25%
Convolution Neural Network
25%
Receptive Field
24%
Global Context
22%
Scale Uncertainty
20%
Clinical Indicators
20%
Cornea
20%
Full Use
20%
Cellular Structure
18%
Ambiguous Region
18%
Network Applications
17%
Microscope Image
16%
Segmentation Problem
16%
Promising Solutions
14%
Local Details
14%
Non-contact Specular Microscopy
12%
Fourier Frequency
12%
Cell Size Variation
12%
Self-collected
12%
Computer Science
Image Segmentation
50%
Cell Segmentation
50%
Generative Adversarial Networks
50%
Range Dependency
41%
Segmentation Task
41%
Microscope Image
37%
Spatial Method
25%
Confocal Microscope
25%
Attention (Machine Learning)
25%
Parameter Estimation
25%
Network Structures
25%
Bayesian Networks
25%
Interpretability
25%
Vessel Segmentation
25%
Convolutional Neural Network
25%
Global Context
20%
Discriminator
19%
Receptive Field
16%
Deep Learning
14%
Knowledge Structure
12%
Enhancement Module
12%
Local Affinity
12%
Image Enhancement
12%
Frequency Domain
12%
Training Process
12%
Classification Accuracy
12%
Feature Fusion
12%
Estimation Accuracy
12%
Granularity
10%
Segmentation Performance
10%
Data Augmentation
9%
Modeling Information
8%
Desirable Property
8%
Contrast Condition
8%
Semantic Feature
8%
Global Information
8%
Target Location
8%
Representation Learning
8%
Local Information
8%
Convolutional Neural Network
8%
Feature Space
8%
de-noising
6%
Engineering
State-of-the-Art Method
52%
Multiscale
50%
Tasks
40%
Medical Image
37%
Receptive Field
37%
Deep Learning
36%
Confocal Microscope
25%
Medical Image Segmentation
25%
Coefficient of Variation
25%
Boundary Cell
25%
Context Information
25%
Spatial Attention
25%
Segmentation Method
25%
Texture Feature
25%
Feature Extraction
25%
Position Information
25%
Attention Gate
25%
Discriminator
21%
Granularity
18%
Parameter Estimation
16%
Local Model
12%
Feature Space
12%
Image Enhancement
12%
Frequency Domain
12%
Image Processing
9%
High Resolution
9%
Knowledge Structure
8%
Good Agreement
8%
Similarity Index
8%
Joints (Structural Components)
8%
Good Correlation
8%
Classification Accuracy
8%
Ground Truth
8%
Aleatoric Uncertainty
6%
Epistemic Uncertainty
6%
Image Synthesis
6%
Experimental Result
6%
Image Translation
6%
Region of Interest
6%
Network Model
6%
Network Application
6%
Rationality
6%
Dimensional Data
6%
