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Dinggang Shen
76 publications
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73 publications
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44 publications
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33 publications
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24 publications
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21 publications
Thierry Denoeux
19 publications
Paul Honeine
14 publications
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Xiaowei Wang
9 publications

∙ 09/12/2023

Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation

Single-modality medical images generally do not contain enough informati...

0 Ling Huang, et al. ∙

∙ 07/24/2023

Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review

Deep learning has become a popular tool for medical image analysis, but ...

0 Aghiles Kebaili, et al. ∙

∙ 06/23/2022

Evidence fusion with contextual discounting for multi-modality medical image segmentation

As information sources are usually imperfect, it is necessary to take in...

0 Ling Huang, et al. ∙

∙ 06/23/2022

A novel adversarial learning strategy for medical image classification

Deep learning (DL) techniques have been extensively utilized for medical...

0 Zong Fan, et al. ∙

∙ 05/03/2022

Application of belief functions to medical image segmentation: A review

Belief function theory, a formal framework for uncertainty analysis and ...

0 Ling Huang, et al. ∙

∙ 03/22/2022

A Quantitative Comparison between Shannon and Tsallis Havrda Charvat Entropies Applied to Cancer Outcome Prediction

In this paper, we propose to quantitatively compare loss functions based...

0 Thibaud Brochet, et al. ∙

∙ 03/01/2022

Multi-Task Multi-Scale Learning For Outcome Prediction in 3D PET Images

Background and Objectives: Predicting patient response to treatment and ...

0 Amine Amyar, et al. ∙

∙ 01/31/2022

Lymphoma segmentation from 3D PET-CT images using a deep evidential network

An automatic evidential segmentation method based on Dempster-Shafer the...

0 Ling Huang, et al. ∙

∙ 12/20/2021

Deep Co-supervision and Attention Fusion Strategy for Automatic COVID-19 Lung Infection Segmentation on CT Images

Due to the irregular shapes,various sizes and indistinguishable boundari...

11 Haigen Hu, et al. ∙

∙ 11/08/2021

Feature-enhanced Generation and Multi-modality Fusion based Deep Neural Network for Brain Tumor Segmentation with Missing MR Modalities

Using multimodal Magnetic Resonance Imaging (MRI) is necessary for accur...

18 Tongxue Zhou, et al. ∙

∙ 11/02/2021

A Tri-attention Fusion Guided Multi-modal Segmentation Network

In the field of multimodal segmentation, the correlation between differe...

0 Tongxue Zhou, et al. ∙

∙ 10/20/2021

Artificial Intelligence-Based Detection, Classification and Prediction/Prognosis in PET Imaging: Towards Radiophenomics

Artificial intelligence (AI) techniques have significant potential to en...

0 Fereshteh Yousefirizi, et al. ∙

∙ 08/11/2021

Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation

Lymphoma detection and segmentation from whole-body Positron Emission To...

0 Ling Huang, et al. ∙

∙ 04/27/2021

Evidential segmentation of 3D PET/CT images

PET and CT are two modalities widely used in medical image analysis. Acc...

0 Ling Huang, et al. ∙

∙ 04/13/2021

Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities

Magnetic Resonance Imaging (MRI) is a widely used imaging technique to a...

0 Tongxue Zhou, et al. ∙

∙ 04/12/2021

Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy

Pulmonary optical endomicroscopy (POE) is an imaging technology in real ...

0 Thibaud Brochet, et al. ∙

∙ 02/05/2021

3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint

In the field of multimodal segmentation, the correlation between differe...

4 Tongxue Zhou, et al. ∙

∙ 01/29/2021

Belief function-based semi-supervised learning for brain tumor segmentation

Precise segmentation of a lesion area is important for optimizing its tr...

0 Ling Huang, et al. ∙

∙ 01/18/2021

Covid-19 classification with deep neural network and belief functions

Computed tomography (CT) image provides useful information for radiologi...

0 Ling Huang, et al. ∙

∙ 04/22/2020

A review: Deep learning for medical image segmentation using multi-modality fusion

Multi-modality is widely used in medical imaging, because it can provide...

0 Tongxue Zhou, et al. ∙

∙ 04/14/2020

An automatic COVID-19 CT segmentation based on U-Net with attention mechanism

The coronavirus disease (COVID-19) pandemic has led a devastating effect...

13 Tongxue Zhou, et al. ∙

∙ 04/14/2020

An automatic COVID-19 CT segmentation network using spatial and channel attention mechanism

The coronavirus disease (COVID-19) pandemic has led to a devastating eff...

0 Tongxue Zhou, et al. ∙

∙ 03/19/2020

Brain tumor segmentation with missing modalities via latent multi-source correlation representation

Multimodal MR images can provide complementary information for accurate ...

0 Tongxue Zhou, et al. ∙

∙ 03/19/2020

RADIOGAN: Deep Convolutional Conditional Generative adversarial Network To Generate PET Images

One of the most challenges in medical imaging is the lack of data. It is...

0 Amine Amyar, et al. ∙

∙ 03/18/2020

Weakly Supervised PET Tumor Detection Using Class Response

One of the most challenges in medical imaging is the lack of data and an...

0 Amine Amyar, et al. ∙

∙ 03/18/2020

Weakly Supervised PET Tumor Detection UsingClass Response

One of the most challenges in medical imaging is the lack of data and an...

0 Amine Amyar, et al. ∙

∙ 09/12/2017

Une véritable approche ℓ_0 pour l'apprentissage de dictionnaire

Sparse representation learning has recently gained a great success in si...

0 Yuan Liu, et al. ∙

∙ 12/16/2016

Medical Image Synthesis with Context-Aware Generative Adversarial Networks

Computed tomography (CT) is critical for various clinical applications, ...

0 Dong Nie, et al. ∙

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