no code implementations • 5 Mar 2022 • Yihua Sun, Qingsong Yao, Yuanyuan Lyu, Jianji Wang, Yi Xiao, Hongen Liao, S. Kevin Zhou
Digital chest tomosynthesis (DCT) is a technique to produce sectional 3D images of a human chest for pulmonary disease screening, with 2D X-ray projections taken within an extremely limited range of angles.
no code implementations • 4 Nov 2021 • Yuanyuan Wang, Yao Zhang, Qiong He, Hongen Liao, Jianwen Luo
This paper proposes a semi-automatic system based on quantitative characterization of the specific image patterns in lung ultrasound (LUS) images, in order to assess the lung conditions of patients with COVID-19 pneumonia, as well as to differentiate between the severe / and no-severe cases.
no code implementations • 15 Mar 2021 • Liutong Zhang, Lei Zhou, Ruiyang Li, Xianyu Wang, Boxuan Han, Hongen Liao
In this paper, we pre-sent a cascaded feature warping network to perform the coarse-to-fine registration.
1 code implementation • 2 May 2020 • Bingyu Xin, Yifan Hu, Yefeng Zheng, Hongen Liao
We use the synthesized modalities by TC-MGAN to boost the tumor segmentation accuracy, and the results demonstrate its effectiveness.
1 code implementation • ICCV 2019 • Jiahui Zhang, Dawei Sun, Zixin Luo, Anbang Yao, Lei Zhou, Tianwei Shen, Yurong Chen, Long Quan, Hongen Liao
First, to capture the local context of sparse correspondences, the network clusters unordered input correspondences by learning a soft assignment matrix.
1 code implementation • ECCV 2018 • Jiahui Zhang, Hao Zhao, Anbang Yao, Yurong Chen, Li Zhang, Hongen Liao
We introduce Spatial Group Convolution (SGC) for accelerating the computation of 3D dense prediction tasks.
Ranked #9 on 3D Semantic Scene Completion on SemanticKITTI
no code implementations • 5 Sep 2018 • Ke Wang, Han Song, Jiahui Zhang, Xinran Zhang, Hongen Liao
In this paper, we proposed a method which can fuse different modalities 3D data to get a large-scale and dense point cloud.