16 citations · 77 across the 14 of their papers we have counts for
15 papers
UNet-2022: Exploring Dynamics in Non-isomorphic Architecture
Jiansen Guo, Hong-Yu Zhou, Liansheng Wang +1
Recent medical image segmentation models are mostly hybrid, which integrate self-attention and convolution layers into the non-isomorphic architecture. However, one potential drawb…
Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning
Yangji He, Weihan Liang, Dongyang Zhao +4
This paper presents new hierarchically cascaded transformers that can improve data efficiency through attribute surrogates learning and spectral tokens pooling. Vision transformers…
Advancing 3D Medical Image Analysis with Variable Dimension Transform based Supervised 3D Pre-training
Shu Zhang, Zihao Li, Hong-Yu Zhou +2
The difficulties in both data acquisition and annotation substantially restrict the sample sizes of training datasets for 3D medical imaging applications. As a result, constructing…
ConvNets vs. Transformers: Whose Visual Representations are More Transferable?
Hong-Yu Zhou, Chixiang Lu, Sibei Yang +1
Vision transformers have attracted much attention from computer vision researchers as they are not restricted to the spatial inductive bias of ConvNets. However, although Transform…
SSMD: Semi-Supervised Medical Image Detection with Adaptive Consistency and Heterogeneous Perturbation
Hong-Yu Zhou, Chengdi Wang, Haofeng Li +4
Semi-Supervised classification and segmentation methods have been widely investigated in medical image analysis. Both approaches can improve the performance of fully-supervised met…
Generalized Organ Segmentation by Imitating One-shot Reasoning using Anatomical Correlation
Hong-Yu Zhou, Hualuo Liu, Shilei Cao +5
Learning by imitation is one of the most significant abilities of human beings and plays a vital role in human's computational neural system. In medical image analysis, given sever…