b'Hongming Shan'

research

∙ 04/23/2023

FAN-Net: Fourier-Based Adaptive Normalization For Cross-Domain Stroke Lesion Segmentation

Since stroke is the main cause of various cerebrovascular diseases, deep...

0 Weiyi Yu, et al. ∙

research

∙ 04/17/2023

CLIP-Lung: Textual Knowledge-Guided Lung Nodule Malignancy Prediction

Lung nodule malignancy prediction has been enhanced by advanced deep-lea...

0 Yiming Lei, et al. ∙

research

∙ 04/10/2023

BerDiff: Conditional Bernoulli Diffusion Model for Medical Image Segmentation

Medical image segmentation is a challenging task with inherent ambiguity...

0 Tao Chen, et al. ∙

research

∙ 04/04/2023

CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalization

Low-dose computed tomography (CT) images suffer from noise and artifacts...

0 Qi Gao, et al. ∙

research

∙ 03/16/2023

Cross-head Supervision for Crowd Counting with Noisy Annotations

Noisy annotations such as missing annotations and location shifts often ...

0 Mingliang Dai, et al. ∙

research

∙ 03/13/2023

Twin Contrastive Learning with Noisy Labels

Learning from noisy data is a challenging task that significantly degene...

0 Zhizhong Huang, et al. ∙

research

∙ 02/21/2023

LIT-Former: Linking In-plane and Through-plane Transformers for Simultaneous CT Image Denoising and Deblurring

This paper studies 3D low-dose computed tomography (CT) imaging. Althoug...

0 Zhihao Chen, et al. ∙

research

∙ 01/15/2023

CORE: Learning Consistent Ordinal REpresentations for Image Ordinal Estimation

The goal of image ordinal estimation is to estimate the ordinal label of...

1 Yiming Lei, et al. ∙

research

∙ 11/14/2022

Temporal Modeling Matters: A Novel Temporal Emotional Modeling Approach for Speech Emotion Recognition

Speech emotion recognition (SER) plays a vital role in improving the int...

0 Jiaxin Ye, et al. ∙

research

∙ 10/21/2022

GaitMAST: Motion-Aware Spatio-Temporal Feature Learning Network for Cross-View Gait Recognition

As a unique biometric that can be perceived at a distance, gait has broa...

0 Jingqi Li, et al. ∙

research

∙ 10/17/2022

When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework and A New Benchmark

To minimize the impact of age variation on face recognition, age-invaria...

0 Zhizhong Huang, et al. ∙

research

∙ 07/24/2022

FD-MAR: Fourier Dual-domain Network for CT Metal Artifact Reduction

The presence of high-density objects such as metal implants and dental f...

7 Zilong Li, et al. ∙

research

∙ 05/09/2022

Site Generalization: Stroke Lesion Segmentation on Magnetic Resonance Images from Unseen Sites

There are considerable interests in automatic stroke lesion segmentation...

0 Weiyi Yu, et al. ∙

research

∙ 05/06/2022

Forget Less, Count Better: A Domain-Incremental Self-Distillation Learning Benchmark for Lifelong Crowd Counting

Crowd Counting has important applications in public safety and pandemic ...

9 Jiaqi Gao, et al. ∙

research

∙ 03/29/2022

Synergizing Physics/Model-based and Data-driven Methods for Low-Dose CT

Since 2016, deep learning (DL) has advanced tomographic imaging with rem...

0 Wenjun Xia, et al. ∙

research

∙ 03/22/2022

Convolutional Neural Network to Restore Low-Dose Digital Breast Tomosynthesis Projections in a Variance Stabilization Domain

Digital breast tomosynthesis (DBT) exams should utilize the lowest possi...

9 Rodrigo de Barros Vimieiro, et al. ∙

research

∙ 03/15/2022

Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels

The performance of medical image classification has been enhanced by dee...

0 Yiming Lei, et al. ∙

research

∙ 11/23/2021

Exploring Non-Contrastive Representation Learning for Deep Clustering

Existing deep clustering methods rely on contrastive learning for repres...

6 Zhizhong Huang, et al. ∙

research

∙ 11/12/2021

Impact of loss functions on the performance of a deep neural network designed to restore low-dose digital mammography

Digital mammography is still the most common imaging tool for breast can...

9 Hongming Shan, et al. ∙

research

∙ 08/24/2021

DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoising

LDCT has drawn major attention in the medical imaging field due to the p...

5 Zhizhong Huang, et al. ∙

research

∙ 05/15/2021

AgeFlow: Conditional Age Progression and Regression with Normalizing Flows

Age progression and regression aim to synthesize photorealistic appearan...

10 Zhizhong Huang, et al. ∙

research

∙ 03/27/2021

SelfGait: A Spatiotemporal Representation Learning Method for Self-supervised Gait Recognition

Gait recognition plays a vital role in human identification since gait i...

0 Yiqun Liu, et al. ∙

research

∙ 03/24/2021

MANAS: Multi-Scale and Multi-Level Neural Architecture Search for Low-Dose CT Denoising

Lowering the radiation dose in computed tomography (CT) can greatly redu...

0 Zexin Lu, et al. ∙

research

∙ 03/02/2021

When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework

To minimize the effects of age variation in face recognition, previous w...

22 Zhizhong Huang, et al. ∙

research

∙ 02/01/2021

RoutingGAN: Routing Age Progression and Regression with Disentangled Learning

Although impressive results have been achieved for age progression and r...

0 Zhizhong Huang, et al. ∙

research

∙ 01/31/2021

Meta ordinal weighting net for improving lung nodule classification

The progression of lung cancer implies the intrinsic ordinal relationshi...

0 Yiming Lei, et al. ∙

research

∙ 12/07/2020

Meta Ordinal Regression Forest For Learning with Unsure Lung Nodules

Deep learning-based methods have achieved promising performance in early...

0 Yiming Lei, et al. ∙

research

∙ 12/07/2020

PFA-GAN: Progressive Face Aging with Generative Adversarial Network

Face aging is to render a given face to predict its future appearance, w...

5 Zhizhong Huang, et al. ∙

research

∙ 08/16/2020

Deep Learning Predicts Cardiovascular Disease Risks from Lung Cancer Screening Low Dose Computed Tomography

The high risk population of cardiovascular disease (CVD) is simultaneous...

18 Hanqing Chao, et al. ∙

research

∙ 08/07/2020

Deep Ordinal Regression Forests

Ordinal regression is a type of regression techniques used for predictin...

28 Haiping Zhu, et al. ∙

research

∙ 07/08/2020

Low-dimensional Manifold Constrained Disentanglement Network for Metal Artifact Reduction

Deep neural network based methods have achieved promising results for CT...

5 Chuang Niu, et al. ∙

research

∙ 06/23/2020

Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network

Cine cardiac magnetic resonance imaging (MRI) is widely used for diagnos...

0 Hongming Shan, et al. ∙

research

∙ 12/09/2019

Deep Efficient End-to-end Reconstruction (DEER) Network for Low-dose Few-view Breast CT from Projection Data

Breast CT provides image volumes with isotropic resolution in high contr...

22 Huidong Xie, et al. ∙

research

∙ 11/13/2019

Deep Encoder-decoder Adversarial Reconstruction (DEAR) Network for 3D CT from Few-view Data

X-ray computed tomography (CT) is widely used in clinical practice. The ...

27 Huidong Xie, et al. ∙

research

∙ 10/24/2019

Look globally, age locally: Face aging with an attention mechanism

Face aging is of great importance for cross-age recognition and entertai...

0 Haiping Zhu, et al. ∙

research

∙ 10/13/2019

Parameter Constrained Transfer Learning for Low Dose PET Image Denoising

Positron emission tomography (PET) is widely used in clinical practice. ...

19 Yu Gong, et al. ∙

research

∙ 09/25/2019

Deep-learning-based Breast CT for Radiation Dose Reduction

Cone-beam breast computed tomography (CT) provides true 3D breast images...

14 Wenxiang Cong, et al. ∙

research

∙ 08/05/2019

Multi-Contrast Super-Resolution MRI Through a Progressive Network

Magnetic resonance imaging (MRI) is widely used for screening, diagnosis...

0 Hongming Shan, et al. ∙

research

∙ 07/23/2019

Simultaneous reconstruction of the initial pressure and sound speed in photoacoustic tomography using a deep-learning approach

Photoacoustic tomography seeks to reconstruct an acoustic initial pressu...

0 Hongming Shan, et al. ∙

research

∙ 07/06/2019

MRI Super-Resolution with Ensemble Learning and Complementary Priors

Magnetic resonance imaging (MRI) is a widely used medical imaging modali...

0 Hongming Shan, et al. ∙

research

∙ 07/02/2019

Dual Network Architecture for Few-view CT --Trained on ImageNet Data and Transferred for Medical Imaging

X-ray computed tomography (CT) reconstructs cross-sectional images from ...

1 Huidong Xie, et al. ∙

research

∙ 05/27/2019

Ordinal Distribution Regression for Gait-based Age Estimation

Computer vision researchers prefer to estimate the age from face images ...

0 Haiping Zhu, et al. ∙

research

∙ 01/17/2019

Quadratic Autoencoder for Low-Dose CT Denoising

Recently, deep learning has transformed many fields including medical im...

12 Fenglei Fan, et al. ∙

research

∙ 11/08/2018

Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods?

Commercial iterative reconstruction techniques on modern CT scanners tar...

8 Hongming Shan, et al. ∙

research

∙ 10/30/2018

Soft Activation Mapping of Lung Nodules in Low-Dose CT images

As a popular deep learning model, the convolutional neural network (CNN)...

8 Yiming Lei, et al. ∙

research

∙ 05/02/2018

Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising

Computed tomography (CT) is a popular medical imaging modality in clinic...

0 Chenyu You, et al. ∙

research

∙ 02/15/2018

3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network

Low-dose computed tomography (CT) has attracted a major attention in the...

0 Hongming Shan, et al. ∙

research

∙ 02/15/2018

Shamap: Shape-based Manifold Learning

For manifold learning, it is assumed that high-dimensional sample/data p...

0 Fenglei Fan, et al. ∙

Hongming Shan

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