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Realistic Endoscopic Image Generation Method Using Virtual-to-real Image-domain Translation
Virtual endoscopic images are generated by using a volume rendering method from a CT volume of a patient.
Depth Estimation from Single-shot Monocular Endoscope Image Using Image Domain Adaptation And Edge-Aware Depth Estimation
The identification accuracy of the network improved from 69. 2% to 74. 1% by using the estimated depth images.
Micro CT Image-Assisted Cross Modality Super-Resolution of Clinical CT Images Utilizing Synthesized Training Dataset
Unsupervised SR methods are required that do not need paired LR and HR images.
Super-resolution of clinical CT volumes with modified CycleGAN using micro CT volumes
This paper presents a super-resolution (SR) method with unpaired training dataset of clinical CT and micro CT volumes.
Multi-modality super-resolution loss for GAN-based super-resolution of clinical CT images using micro CT image database
This paper newly introduces multi-modality loss function for GAN-based super-resolution that can maintain image structure and intensity on unpaired training dataset of clinical CT and micro CT volumes.
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