On Hallucinations in Tomographic Image Reconstruction [PDF]
IEEE Transactions on Medical Imaging, 2020 Tomographic image reconstruction is generally an ill-posed linear inverse problem. Such ill-posed inverse problems are typically regularized using prior knowledge of the sought-after object property.
Sayantan Bhadra +3 more
semanticscholar +6 more sources
Optimizing computed tomography image reconstruction for focal hepatic lesions: Deep learning image reconstruction vs iterative reconstruction [PDF]
HeliyonBackground: Deep learning image reconstruction (DLIR) is a novel computed tomography (CT) reconstruction technique that minimizes image noise, enhances image quality, and enables radiation dose reduction.
Varin Jaruvongvanich +10 more
doaj +2 more sources
Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction [PDF]
Computer Vision and Pattern Recognition, 2021 Hyperspectral image (HSI) reconstruction aims to recover the 3D spatial-spectral signal from a 2D measurement in the coded aperture snapshot spectral imaging (CASSI) system.
Yuanhao Cai +7 more
semanticscholar +1 more source
RealFusion 360° Reconstruction of Any Object from a Single Image [PDF]
Computer Vision and Pattern Recognition, 2023 We consider the problem of reconstructing a full 360° photographic model of an object from a single image of it. We do so by fitting a neural radiance field to the image, but find this problem to be severely ill-posed.
Luke Melas-Kyriazi +3 more
semanticscholar +1 more source
Review of Super-Resolution Image Reconstruction Algorithms [PDF]
Jisuanji kexue yu tansuo, 2022 In human visual perception system, high-resolution (HR) image is an important medium to clearly express its spatial structure, detailed features, edge texture and other information, and it has a very wide range of practical value in medicine, criminal ...
ZHONG Mengyuan, JIANG Lin
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Review of Image Super-resolution Reconstruction Algorithms Based on Deep Learning [PDF]
Jisuanji kexue yu tansuo, 2022 The essence of image super-resolution reconstruction technology is to break through the limitation of hardware conditions, and reconstruct a high-resolution image from a low-resolution image which contains less infor-mation through the image super ...
YANG Caidong, LI Chengyang, LI Zhongbo, XIE Yongqiang, SUN Fangwei, QI Jin
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Splatter Image: Ultra-Fast Single-View 3D Reconstruction [PDF]
Computer Vision and Pattern Recognition, 2023 We introduce the Splatter Image, an ultra-efficient approach for monocular 3D object reconstruction. Splatter Image is based on Gaussian Splatting, which allows fast and high-quality reconstruction of 3D scenes from multiple images.
Stanislaw Szymanowicz +2 more
semanticscholar +1 more source
Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstruction [PDF]
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2022 We propose a novel and unified method, measurement-conditioned denoising diffusion probabilistic model (MC-DDPM), for under-sampled medical image reconstruction based on DDPM.
Yutong Xie, Quanzheng Li
semanticscholar +1 more source
NeRP: Implicit Neural Representation Learning With Prior Embedding for Sparsely Sampled Image Reconstruction [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2021 Image reconstruction is an inverse problem that solves for a computational image based on sampled sensor measurement. Sparsely sampled image reconstruction poses additional challenges due to limited measurements. In this work, we propose a methodology of
Liyue Shen, J. Pauly, Lei Xing
semanticscholar +1 more source
Multi-institutional Collaborations for Improving Deep Learning-based Magnetic Resonance Image Reconstruction Using Federated Learning [PDF]
Computer Vision and Pattern Recognition, 2021 Fast and accurate reconstruction of magnetic resonance (MR) images from under-sampled data is important in many clinical applications. In recent years, deep learning-based methods have been shown to produce superior performance on MR image reconstruction.
Pengfei Guo +4 more
semanticscholar +1 more source