63 citations · 66 across the 4 of their papers we have counts for
5 papers
Two-Stream Graph Convolutional Network for Intra-oral Scanner Image Segmentation
Yue Zhao, Lingming Zhang, Yang Liu +6
Precise segmentation of teeth from intra-oral scanner images is an essential task in computer-aided orthodontic surgical planning. The state-of-the-art deep learning-based methods…
A Self-Supervised Deep Framework for Reference Bony Shape Estimation in Orthognathic Surgical Planning
Deqiang Xiao, Hannah Deng, Tianshu Kuang +11
Virtual orthognathic surgical planning involves simulating surgical corrections of jaw deformities on 3D facial bony shape models. Due to the lack of necessary guidance, the planni…
TSGCNet: Discriminative Geometric Feature Learning with Two-Stream GraphConvolutional Network for 3D Dental Model Segmentation
Lingming Zhang, Yue Zhao, Deyu Meng +5
The ability to segment teeth precisely from digitized 3D dental models is an essential task in computer-aided orthodontic surgical planning. To date, deep learning based methods ha…
HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation
Kelei He, Chunfeng Lian, Bing Zhang +6
Accurate segmentation of the prostate is a key step in external beam radiation therapy treatments. In this paper, we tackle the challenging task of prostate segmentation in CT imag…
MetricUNet: Synergistic Image- and Voxel-Level Learning for Precise CT Prostate Segmentation via Online Sampling
Kelei He, Chunfeng Lian, Ehsan Adeli +5
Fully convolutional networks (FCNs), including UNet and VNet, are widely-used network architectures for semantic segmentation in recent studies. However, conventional FCN is typica…