69 citations · 207 across the 11 of their papers we have counts for
5 papers · 1 filter
VolumeNet: A Lightweight Parallel Network for Super-Resolution of Medical Volumetric Data
Yinhao Li, Yutaro Iwamoto, Lanfen Lin +2
Deep learning-based super-resolution (SR) techniques have generally achieved excellent performance in the computer vision field. Recently, it has been proven that three-dimensional…
Unsupervised MRI Super-Resolution Using Deep External Learning and Guided Residual Dense Network with Multimodal Image Priors
Yutaro Iwamoto, Kyohei Takeda, Yinhao Li +2
Deep learning techniques have led to state-of-the-art image super resolution with natural images. Normally, pairs of high-resolution and low-resolution images are used to train the…
Interactive Deep Refinement Network for Medical Image Segmentation
Titinunt Kitrungrotsakul, Iwamoto Yutaro, Lanfen Lin +3
Deep learning techniques have successfully been employed in numerous computer vision tasks including image segmentation. The techniques have also been applied to medical image segm…
Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network
Rui Xu, Tiantian Liu, Xinchen Ye +1
Many deep learning based methods have been proposed for retinal vessel segmentation, however few of them focus on the connectivity of segmented vessels, which is quite important fo…
UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation
Huimin Huang, Lanfen Lin, Ruofeng Tong +6
Recently, a growing interest has been seen in deep learning-based semantic segmentation. UNet, which is one of deep learning networks with an encoder-decoder architecture, is widel…