Neighborhood evaluator for efficient super-resolution reconstruction of 2D medical images
Background: Deep learning-based super-resolution (SR) algorithms aim to reconstruct low-
resolution (LR) images into high-fidelity high-resolution (HR) images by learning the low …
resolution (LR) images into high-fidelity high-resolution (HR) images by learning the low …
3D Point-based Multi-Modal Context Clusters GAN for Low-Dose PET Image Denoising
To obtain high-quality Positron emission tomography (PET) images while minimizing
radiation hazards, various methods have been developed to acquire standard-dose PET …
radiation hazards, various methods have been developed to acquire standard-dose PET …
Deep Unfolding Network with Spatial Alignment for multi-modal MRI reconstruction
Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic
information, but some modalities are limited by the long scanning time. To accelerate the …
information, but some modalities are limited by the long scanning time. To accelerate the …
Cross-Modality Reference and Feature Mutual-Projection for 3D Brain MRI Image Super-Resolution
L Wang, W Zhang, W Chen, Z He, Y Jia… - Journal of Imaging …, 2024 - Springer
High-resolution (HR) magnetic resonance imaging (MRI) can reveal rich anatomical
structures for clinical diagnoses. However, due to hardware and signal-to-noise ratio …
structures for clinical diagnoses. However, due to hardware and signal-to-noise ratio …
Application of Multi-objective Optimization in 3D Image Reconstruction.
F Zhang - Traitement du Signal, 2024 - search.ebscohost.com
Abstract 3D image reconstruction technology holds significant potential for applications in
medical imaging, industrial inspection, and virtual reality, offering more intuitive and precise …
medical imaging, industrial inspection, and virtual reality, offering more intuitive and precise …