Search Results for author: Guodong Zeng

Found 11 papers, 3 papers with code

A Noise-level-aware Framework for PET Image Denoising

no code implementations15 Mar 2022 Ye Li, Jianan Cui, Junyu Chen, Guodong Zeng, Scott Wollenweber, Floris Jansen, Se-In Jang, Kyungsang Kim, Kuang Gong, Quanzheng Li

Our hypothesis is that by explicitly providing the local relative noise level of the input image to a deep convolutional neural network (DCNN), the DCNN can outperform itself trained on image appearance only.

Image Denoising SSIM

Dispensed Transformer Network for Unsupervised Domain Adaptation

no code implementations28 Oct 2021 Yunxiang Li, Jingxiong Li, Ruilong Dan, Shuai Wang, Kai Jin, Guodong Zeng, Jun Wang, Xiangji Pan, Qianni Zhang, Huiyu Zhou, Qun Jin, Li Wang, Yaqi Wang

To mitigate this problem, a novel unsupervised domain adaptation (UDA) method named dispensed Transformer network (DTNet) is introduced in this paper.

Unsupervised Domain Adaptation

GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation

1 code implementation30 Sep 2021 Yunxiang Li, Shuai Wang, Jun Wang, Guodong Zeng, Wenjun Liu, Qianni Zhang, Qun Jin, Yaqi Wang

In this paper, we propose a novel end-to-end U-Net like Group Transformer Network (GT U-Net) for the tooth root segmentation.


AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy

1 code implementation2 May 2021 Yunxiang Li, Guodong Zeng, Yifan Zhang, Jun Wang, Qianni Zhang, Qun Jin, Lingling Sun, Qisi Lian, Neng Xia, Ruizi Peng, Kai Tang, Yaqi Wang, Shuai Wang

Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results will hamper timely follow-up which is crucial to the patients' treatment outcome.

Anatomy General Classification

ICMSC: Intra- and Cross-modality Semantic Consistency for Unsupervised Domain Adaptation on Hip Joint Bone Segmentation

no code implementations23 Dec 2020 Guodong Zeng, Till D. Lerch, Florian Schmaranzer, Guoyan Zheng, Juergen Burger, Kate Gerber, Moritz Tannast, Klaus Siebenrock, Nicolas Gerber

In this paper, we propose intra- and cross-modality semantic consistency (ICMSC) for UDA and our key insight is that the segmentation of synthesised images in different styles should be consistent.

Image Segmentation Medical Image Segmentation +3

Holistic Decomposition Convolution for Effective Semantic Segmentation of 3D MR Images

no code implementations24 Dec 2018 Guodong Zeng, Guoyan Zheng

In this paper, we propose a novel Holistic Decomposition Convolution (HDC), for an effective and efficient semantic segmentation of volumetric images.

Image Segmentation Semantic Segmentation

Fully Automatic Segmentation of Lumbar Vertebrae from CT Images using Cascaded 3D Fully Convolutional Networks

no code implementations5 Dec 2017 Rens Janssens, Guodong Zeng, Guoyan Zheng

We present a method to address the challenging problem of segmentation of lumbar vertebrae from CT images acquired with varying fields of view.

Multi-stream 3D FCN with Multi-scale Deep Supervision for Multi-modality Isointense Infant Brain MR Image Segmentation

no code implementations28 Nov 2017 Guodong Zeng, Guoyan Zheng

We present a method to address the challenging problem of segmentation of multi-modality isointense infant brain MR images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF).

Image Segmentation Infant Brain Mri Segmentation +2

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