69 citations · 217 across the 13 of their papers we have counts for
4 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…
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…