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Table of Contents
Method-Oriented Papers
Detail matters: high-frequency content for realistic synthetic brain MRI generation
Joint Image and Label Self-Super-Resolution
Super-resolution by Latent Space Exploration: Training with Poorly-aligned Clinical and Micro CT Image Dataset
A Glimpse into the Future: Disease Progression Simulation for Breast Cancer in Mammograms
Synth-by-Reg (SbR): Contrastive learning for synthesis-based registration of paired images
Learning-based Template Synthesis For Groupwise Image Registration
The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties
Transfer Learning in Optical Microscopy
X-ray synthesis based on triangular mesh models using GPU-accelerated ray tracing for multi-modal breast image registration
Application-Oriented Papers
Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial Networks
SequenceGAN: Generating Fundus Fluorescence Angiography Sequences from Structure Fundus Image
Cerebral Blood Volume Prediction based on Multi-modality Magnetic Resonance Imaging
Cine-MRI simulation to evaluate tumor tracking
GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models.
Detail matters: high-frequency content for realistic synthetic brain MRI generation
Joint Image and Label Self-Super-Resolution
Super-resolution by Latent Space Exploration: Training with Poorly-aligned Clinical and Micro CT Image Dataset
A Glimpse into the Future: Disease Progression Simulation for Breast Cancer in Mammograms
Synth-by-Reg (SbR): Contrastive learning for synthesis-based registration of paired images
Learning-based Template Synthesis For Groupwise Image Registration
The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties
Transfer Learning in Optical Microscopy
X-ray synthesis based on triangular mesh models using GPU-accelerated ray tracing for multi-modal breast image registration
Application-Oriented Papers
Frozen-to-Paraffin: Categorization of Histological Frozen Sections by the Aid of Paraffin Sections and Generative Adversarial Networks
SequenceGAN: Generating Fundus Fluorescence Angiography Sequences from Structure Fundus Image
Cerebral Blood Volume Prediction based on Multi-modality Magnetic Resonance Imaging
Cine-MRI simulation to evaluate tumor tracking
GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models.