Search Results for author: Zhiming Cui

Found 27 papers, 15 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

Cephalometric Landmark Detection across Ages with Prototypical Network

1 code implementation18 Jun 2024 Han Wu, Chong Wang, Lanzhuju Mei, Tong Yang, Min Zhu, Dingggang Shen, Zhiming Cui

To our knowledge, this is the first effort toward developing a unified solution and dataset for cephalometric landmark detection across age groups.

3D Vessel Reconstruction from Sparse-View Dynamic DSA Images via Vessel Probability Guided Attenuation Learning

1 code implementation17 May 2024 Zhentao Liu, Huangxuan Zhao, Wenhui Qin, Zhenghong Zhou, Xinggang Wang, Wenping Wang, Xiaochun Lai, Chuansheng Zheng, Dinggang Shen, Zhiming Cui

With the help of contrast agent, time-resolved 2D DSA images deliver comprehensive insights into blood flow information and can be utilized to reconstruct 3D vessel structures.

CLIP in Medical Imaging: A Comprehensive Survey

1 code implementation12 Dec 2023 Zihao Zhao, Yuxiao Liu, Han Wu, Yonghao Li, Sheng Wang, Lin Teng, Disheng Liu, Zhiming Cui, Qian Wang, Dinggang Shen

With the aim of facilitating a deeper understanding of this promising direction, this survey offers an in-depth exploration of the CLIP paradigm within the domain of medical imaging, regarding both refined CLIP pre-training and CLIP-driven applications.

3D Structure-guided Network for Tooth Alignment in 2D Photograph

1 code implementation17 Oct 2023 Yulong Dou, Lanzhuju Mei, Dinggang Shen, Zhiming Cui

In this paper, we propose a 3D structure-guided tooth alignment network that takes 2D photographs as input (e. g., photos captured by smartphones) and aligns the teeth within the 2D image space to generate an orthodontic comparison photograph featuring aesthetically pleasing, aligned teeth.

Tissue Segmentation of Thick-Slice Fetal Brain MR Scans with Guidance from High-Quality Isotropic Volumes

no code implementations13 Aug 2023 Shijie Huang, Xukun Zhang, Zhiming Cui, He Zhang, Geng Chen, Dinggang Shen

Accurate tissue segmentation of thick-slice fetal brain magnetic resonance (MR) scans is crucial for both reconstruction of isotropic brain MR volumes and the quantification of fetal brain development.

Domain Adaptation Segmentation +1

Multi-View Vertebra Localization and Identification from CT Images

1 code implementation24 Jul 2023 Han Wu, Jiadong Zhang, Yu Fang, Zhentao Liu, Nizhuan Wang, Zhiming Cui, Dinggang Shen

Additionally, we further propose a Sequence Loss to maintain the sequential structure embedded along the vertebrae.

Contrastive Learning

3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge

1 code implementation29 May 2023 Achraf Ben-Hamadou, Oussama Smaoui, Ahmed Rekik, Sergi Pujades, Edmond Boyer, Hoyeon Lim, Minchang Kim, Minkyung Lee, Minyoung Chung, Yeong-Gil Shin, Mathieu Leclercq, Lucia Cevidanes, Juan Carlos Prieto, Shaojie Zhuang, Guangshun Wei, Zhiming Cui, Yuanfeng Zhou, Tudor Dascalu, Bulat Ibragimov, Tae-Hoon Yong, Hong-Gi Ahn, Wan Kim, Jae-Hwan Han, Byungsun Choi, Niels van Nistelrooij, Steven Kempers, Shankeeth Vinayahalingam, Julien Strippoli, Aurélien Thollot, Hugo Setbon, Cyril Trosset, Edouard Ladroit

To address these challenges, the 3DTeethSeg'22 challenge was organized in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2022, with a call for algorithms tackling teeth localization, segmentation, and labeling from intraoral 3D scans.

Anatomy Segmentation

ChatCAD+: Towards a Universal and Reliable Interactive CAD using LLMs

1 code implementation25 May 2023 Zihao Zhao, Sheng Wang, Jinchen Gu, Yitao Zhu, Lanzhuju Mei, Zixu Zhuang, Zhiming Cui, Qian Wang, Dinggang Shen

The integration of Computer-Aided Diagnosis (CAD) with Large Language Models (LLMs) presents a promising frontier in clinical applications, notably in automating diagnostic processes akin to those performed by radiologists and providing consultations similar to a virtual family doctor.

In-Context Learning Retrieval

Construction of unbiased dental template and parametric dental model for precision digital dentistry

no code implementations7 Apr 2023 Lei Ma, Jingyang Zhang, Ke Deng, Peng Xue, Zhiming Cui, Yu Fang, Minhui Tang, Yue Zhao, Min Zhu, Zhongxiang Ding, Dinggang Shen

In this study, we develop an unbiased dental template by constructing an accurate dental atlas from CBCT images with guidance of teeth segmentation.

Image Cropping Segmentation

Geometry-Aware Attenuation Field Learning for Sparse-View CBCT Reconstruction

no code implementations26 Mar 2023 Zhentao Liu, Yu Fang, Changjian Li, Han Wu, YuAn Liu, Zhiming Cui, Dinggang Shen

This paper proposes a novel attenuation field encoder-decoder framework by first encoding the volumetric feature from multi-view X-ray projections, then decoding it into the desired attenuation field.

Decoder

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 +3

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

1 code implementation 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 +2

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