Search Results for author: Zhiming Cui

Found 16 papers, 7 papers with code

TANet: Towards Fully Automatic Tooth Arrangement

1 code implementation ECCV 2020 Guodong Wei, Zhiming Cui, Yumeng Liu, Nenglun Chen, Runnan Chen, Guiqing Li, Wenping Wang

Determining optimal target tooth arrangements is a key step of treatment planning in digital orthodontics.

Pose Prediction

SNAF: Sparse-view CBCT Reconstruction with Neural Attenuation Fields

no code implementations30 Nov 2022 Yu Fang, Lanzhuju Mei, Changjian Li, YuAn Liu, Wenping Wang, Zhiming Cui, Dinggang Shen

Cone beam computed tomography (CBCT) has been widely used in clinical practice, especially in dental clinics, while the radiation dose of X-rays when capturing has been a long concern in CBCT imaging.

ToothInpaintor: Tooth Inpainting from Partial 3D Dental Model and 2D Panoramic Image

no code implementations25 Nov 2022 Yuezhi Yang, Zhiming Cui, Changjian Li, Wenping Wang

In this paper, we propose a neural network, called ToothInpaintor, that takes as input a partial 3D dental model and a 2D panoramic image and reconstructs the full tooth model with high-quality root(s).

Class-attention Video Transformer for Engagement Intensity Prediction

1 code implementation12 Aug 2022 Xusheng Ai, Victor S. Sheng, Chunhua Li, Zhiming Cui

In order to deal with variant-length long videos, prior works extract multi-modal features and fuse them to predict students' engagement intensity.

Learning towards Synchronous Network Memorizability and Generalizability for Continual Segmentation across Multiple Sites

no code implementations14 Jun 2022 Jingyang Zhang, Peng Xue, Ran Gu, Yuning Gu, Mianxin Liu, Yongsheng Pan, Zhiming Cui, Jiawei Huang, Lei Ma, Dinggang Shen

In clinical practice, a segmentation network is often required to continually learn on a sequential data stream from multiple sites rather than a consolidated set, due to the storage cost and privacy restriction.

Continual Learning

Two-Stream Graph Convolutional Network for Intra-oral Scanner Image Segmentation

1 code implementation19 Apr 2022 Yue Zhao, Lingming Zhang, Yang Liu, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen

The state-of-the-art deep learning-based methods often simply concatenate the raw geometric attributes (i. e., coordinates and normal vectors) of mesh cells to train a single-stream network for automatic intra-oral scanner image segmentation.

Graph Learning Image Segmentation +1

WSEBP: A Novel Width-depth Synchronous Extension-based Basis Pursuit Algorithm for Multi-Layer Convolutional Sparse Coding

1 code implementation28 Mar 2022 Haitong Tang, Shuang He, Lingbin Bian, Zhiming Cui, Nizhuan Wang

Specifically, we first propose a novel width-depth synchronous extension-based basis pursuit (WSEBP) algorithm which solves the ML-CSC problem without the limitation of the number of iterations compared to the SOTA algorithms and maximizes the performance by an effective initialization in each layer.

Image Classification

Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning

1 code implementation21 Nov 2021 Zheren Li, Zhiming Cui, Sheng Wang, Yuji Qi, Xi Ouyang, Qitian Chen, Yuezhi Yang, Zhong Xue, Dinggang Shen, Jie-Zhi Cheng

Specifically, the backbone network is firstly trained with a multi-style and multi-view unsupervised self-learning scheme for the embedding of invariant features to various vendor-styles.

Contrastive Learning Domain Generalization +2

Structure-Aware Long Short-Term Memory Network for 3D Cephalometric Landmark Detection

1 code implementation21 Jul 2021 Runnan Chen, Yuexin Ma, Nenglun Chen, Lingjie Liu, Zhiming Cui, Yanhong Lin, Wenping Wang

Detecting 3D landmarks on cone-beam computed tomography (CBCT) is crucial to assessing and quantifying the anatomical abnormalities in 3D cephalometric analysis.

Graph Attention regression

TSGCNet: Discriminative Geometric Feature Learning With Two-Stream Graph Convolutional Network for 3D Dental Model Segmentation

no code implementations CVPR 2021 Lingming Zhang, Yue Zhao, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen

State-of-the-art methods directly concatenate the raw attributes of 3D inputs, namely coordinates and normal vectors of mesh cells, to train a single-stream network for fully-automated tooth segmentation.

Graph Learning

Semi-supervised Anatomical Landmark Detection via Shape-regulated Self-training

no code implementations28 May 2021 Runnan Chen, Yuexin Ma, Lingjie Liu, Nenglun Chen, Zhiming Cui, Guodong Wei, Wenping Wang

The global shape constraint is the inherent property of anatomical landmarks that provides valuable guidance for more consistent pseudo labelling of the unlabeled data, which is ignored in the previously semi-supervised methods.

TSGCNet: Discriminative Geometric Feature Learning with Two-Stream GraphConvolutional Network for 3D Dental Model Segmentation

no code implementations26 Dec 2020 Lingming Zhang, Yue Zhao, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen

State-of-the-art methods directly concatenate the raw attributes of 3D inputs, namely coordinates and normal vectors of mesh cells, to train a single-stream network for fully-automated tooth segmentation.

Graph Learning

Mapping in a cycle: Sinkhorn regularized unsupervised learning for point cloud shapes

no code implementations ECCV 2020 Lei Yang, Wenxi Liu, Zhiming Cui, Nenglun Chen, Wenping Wang

We propose an unsupervised learning framework with the pretext task of finding dense correspondences between point cloud shapes from the same category based on the cycle-consistency formulation.

Unsupervised Learning of Intrinsic Structural Representation Points

1 code implementation CVPR 2020 Nenglun Chen, Lingjie Liu, Zhiming Cui, Runnan Chen, Duygu Ceylan, Changhe Tu, Wenping Wang

The 3D structure points produced by our method encode the shape structure intrinsically and exhibit semantic consistency across all the shape instances with similar structures.

ToothNet: Automatic Tooth Instance Segmentation and Identification From Cone Beam CT Images

no code implementations CVPR 2019 Zhiming Cui, Changjian Li, Wenping Wang

To the best of our knowledge, our method is the first to use neural networks to achieve automatic tooth segmentation and identification from CBCT images.

Instance Segmentation Region Proposal +1

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