260 citations · 1.5k across the 65 of their papers we have counts for
10 papers · 1 filter
Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR images
Kuang Gong, Jaewon Yang, Kyungsang Kim +3
Positron Emission Tomography (PET) is a functional imaging modality widely used in neuroscience studies. To obtain meaningful quantitative results from PET images, attenuation corr…
Medical Image Segmentation Based on Multi-Modal Convolutional Neural Network: Study on Image Fusion Schemes
Zhe Guo, Xiang Li, Heng Huang +2
Image analysis using more than one modality (i.e. multi-modal) has been increasingly applied in the field of biomedical imaging. One of the challenges in performing the multimodal…
End-to-end Lung Nodule Detection in Computed Tomography
Dufan Wu, Kyungsang Kim, Bin Dong +2
Computer aided diagnostic (CAD) system is crucial for modern med-ical imaging. But almost all CAD systems operate on reconstructed images, which were optimized for radiologists. Co…
Image Segmentation and Classification for Sickle Cell Disease using Deformable U-Net
Mo Zhang, Xiang Li, Mengjia Xu +1
Reliable cell segmentation and classification from biomedical images is a crucial step for both scientific research and clinical practice. A major challenge for more robust segment…
Iterative PET Image Reconstruction Using Convolutional Neural Network Representation
Kuang Gong, Jiahui Guan, Kyungsang Kim +4
PET image reconstruction is challenging due to the ill-poseness of the inverse problem and limited number of detected photons. Recently deep neural networks have been widely and su…
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
Yiping Lu, Aoxiao Zhong, Quanzheng Li +1
In our work, we bridge deep neural network design with numerical differential equations. We show that many effective networks, such as ResNet, PolyNet, FractalNet and RevNet, can b…
Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis
Seongah Jeong, Xiang Li, Jiarui Yang +2
We propose a novel denoising framework for task functional Magnetic Resonance Imaging (tfMRI) data to delineate the high-resolution spatial pattern of the brain functional connecti…
Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis
Xiang Li, Aoxiao Zhong, Ming Lin +6
Tissue characterization has long been an important component of Computer Aided Diagnosis (CAD) systems for automatic lesion detection and further clinical planning. Motivated by th…
Learning the Sparse and Low Rank PARAFAC Decomposition via the Elastic Net
Songting Shi, Xiang Li, Arkadiusz Sitek +1
In this article, we derive a Bayesian model to learning the sparse and low rank PARAFAC decomposition for the observed tensor with missing values via the elastic net, with property…
A Cascaded Convolutional Neural Network for X-ray Low-dose CT Image Denoising
Dufan Wu, Kyungsang Kim, Georges El Fakhri +1
Image denoising techniques are essential to reducing noise levels and enhancing diagnosis reliability in low-dose computed tomography (CT). Machine learning based denoising methods…