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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...
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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...
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03/01/2022
Multi-Task Multi-Scale Learning For Outcome Prediction in 3D PET Images
Background and Objectives: Predicting patient response to treatment and ...
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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...
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11/02/2021
A Tri-attention Fusion Guided Multi-modal Segmentation Network
In the field of multimodal segmentation, the correlation between differe...
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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...
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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...
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03/19/2020
Brain tumor segmentation with missing modalities via latent multi-source correlation representation
Multimodal MR images can provide complementary information for accurate ...
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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...
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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...
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03/18/2020