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04/17/2023
Unsupervised Image Denoising with Score Function
Though achieving excellent performance in some cases, current unsupervis...
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03/16/2023
Decentralized Riemannian natural gradient methods with Kronecker-product approximations
With a computationally efficient approximation of the second-order infor...
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03/08/2023
DULDA: Dual-domain Unsupervised Learned Descent Algorithm for PET image reconstruction
Deep learning based PET image reconstruction methods have achieved promi...
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02/08/2023
SwinCross: Cross-modal Swin Transformer for Head-and-Neck Tumor Segmentation in PET/CT Images
Radiotherapy (RT) combined with cetuximab is the standard treatment for ...
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02/05/2023
Diffusion Model for Generative Image Denoising
In supervised learning for image denoising, usually the paired clean ima...
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12/21/2022
Investigation of Network Architecture for Multimodal Head-and-Neck Tumor Segmentation
Inspired by the recent success of Transformers for Natural Language Proc...
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11/07/2022
Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine – The Bethesda Report (AI Summit 2022)
The SNMMI Artificial Intelligence (SNMMI-AI) Summit, organized by the SN...
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09/13/2022
PET image denoising based on denoising diffusion probabilistic models
Due to various physical degradation factors and limited counts received,...
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09/08/2022
FedDAR: Federated Domain-Aware Representation Learning
Cross-silo Federated learning (FL) has become a promising tool in machin...
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09/07/2022
Spach Transformer: Spatial and Channel-wise Transformer Based on Local and Global Self-attentions for PET Image Denoising
Position emission tomography (PET) is widely used in clinics and researc...
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03/15/2022
A Noise-level-aware Framework for PET Image Denoising
In PET, the amount of relative (signal-dependent) noise present in diffe...
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03/05/2022
Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstruction
We propose a novel and unified method, measurement-conditioned denoising...
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02/08/2022
Trained Model in Supervised Deep Learning is a Conditional Risk Minimizer
We proved that a trained model in supervised deep learning minimizes the...
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02/01/2022
Federated Active Learning (F-AL): an Efficient Annotation Strategy for Federated Learning
Federated learning (FL) has been intensively investigated in terms of co...
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06/18/2021
Direct Reconstruction of Linear Parametric Images from Dynamic PET Using Nonlocal Deep Image Prior
Direct reconstruction methods have been developed to estimate parametric...
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04/08/2021
BEFD: Boundary Enhancement and Feature Denoising for Vessel Segmentation
Blood vessel segmentation is crucial for many diagnostic and research ap...
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12/29/2020
MS-GWNN:multi-scale graph wavelet neural network for breast cancer diagnosis
Breast cancer is one of the most common cancers in women worldwide, and ...
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12/23/2020
IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks
Missing value imputation is a challenging and well-researched topic in d...
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12/08/2020
A General Computational Framework to Measure the Expressiveness of Complex Networks Using a Tighter Upper Bound of Linear Regions
The expressiveness of deep neural network (DNN) is a perspective to unde...
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09/26/2020
Deep Learning-based Four-region Lung Segmentation in Chest Radiography for COVID-19 Diagnosis
Purpose. Imaging plays an important role in assessing severity of COVID ...
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09/14/2020
Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-Scale Generative Adversarial Network
Arterial spin labeling (ASL) magnetic resonance imaging (MRI) is a power...
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09/13/2020
Clinically Translatable Direct Patlak Reconstruction from Dynamic PET with Motion Correction Using Convolutional Neural Network
Patlak model is widely used in 18F-FDG dynamic positron emission tomogra...
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05/22/2020
Deep Learning Based Detection and Localization of Cerebal Aneurysms in Computed Tomography Angiography
Detecting cerebral aneurysms is an important clinical task of brain comp...
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05/19/2020
Self-supervised Dynamic CT Perfusion Image Denoising with Deep Neural Networks
Dynamic computed tomography perfusion (CTP) imaging is a promising appro...
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05/08/2020
A Graph Gaussian Embedding Method for Predicting Alzheimer's Disease Progression with MEG Brain Networks
Characterizing the subtle changes of functional brain networks associate...
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12/16/2019
Penalized-likelihood PET Image Reconstruction Using 3D Structural Convolutional Sparse Coding
Positron emission tomography (PET) is widely used for clinical diagnosis...
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10/07/2019
Multi-label Detection and Classification of Red Blood Cells in Microscopic Images
Cell detection and cell type classification from biomedical images play ...
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10/01/2019
Predicting Alzheimer's Disease by Hierarchical Graph Convolution from Positron Emission Tomography Imaging
Imaging-based early diagnosis of Alzheimer Disease (AD) has become an ef...
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07/26/2019
Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images
Segmenting coronary arteries is challenging, as classic unsupervised met...
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07/07/2019
ASCNet: Adaptive-Scale Convolutional Neural Networks for Multi-Scale Feature Learning
Extracting multi-scale information is key to semantic segmentation. Howe...
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06/09/2019
Consensus Neural Network for Medical Imaging Denoising with Only Noisy Training Samples
Deep neural networks have been proved efficient for medical image denois...
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12/03/2018
Automated Segmentation of Cervical Nuclei in Pap Smear Images using Deformable Multi-path Ensemble Model
Pap smear testing has been widely used for detecting cervical cancers ba...
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10/05/2018
Computationally Efficient Cascaded Training for Deep Unrolled Network in CT Imaging
Dose reduction in computed tomography (CT) has been of great research in...
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10/01/2018
Network Modeling and Pathway Inference from Incomplete Data ("PathInf")
In this work, we developed a network inference method from incomplete da...
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08/06/2018
Multi-Estimator Full Left Ventricle Quantification through Ensemble Learning
Cardiovascular disease accounts for 1 in every 4 deaths in United States...
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07/04/2018
Learning Personalized Representation for Inverse Problems in Medical Imaging Using Deep Neural Network
Recently deep neural networks have been widely and successfully applied ...
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05/31/2018
Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)
Simultaneous modeling of the spatio-temporal variation patterns of brain...
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12/17/2017
Attenuation Correction for Brain PET imaging using Deep Neural Network based on Dixon and ZTE MR images
Positron Emission Tomography (PET) is a functional imaging modality wide...
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11/06/2017
End-to-End Abnormality Detection in Medical Imaging
Nearly all of the deep learning based image analysis methods work on rec...
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10/31/2017
Medical Image Segmentation Based on Multi-Modal Convolutional Neural Network: Study on Image Fusion Schemes
Image analysis using more than one modality (i.e. multi-modal) has been ...
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10/27/2017
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
In our work, we bridge deep neural network design with numerical differe...
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10/23/2017
Image Segmentation and Classification for Sickle Cell Disease using Deformable U-Net
Reliable cell segmentation and classification from biomedical images is ...
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10/09/2017
Iterative PET Image Reconstruction Using Convolutional Neural Network Representation
PET image reconstruction is challenging due to the ill-poseness of the i...
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07/21/2017
Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis
We propose a novel denoising framework for task functional Magnetic Reso...
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07/19/2017
Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis
Tissue characterization has long been an important component of Computer...
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05/29/2017
Learning the Sparse and Low Rank PARAFAC Decomposition via the Elastic Net
In this article, we derive a Bayesian model to learning the sparse and l...
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05/11/2017