Results 141 to 150 of about 412,052 (160)

The future of CT: deep learning reconstruction

Clinical Radiology, 2021
There have been substantial advances in computed tomography (CT) technology since its introduction in the 1970s. More recently, these advances have focused on image reconstruction. Deep learning reconstruction (DLR) is the latest complex reconstruction algorithm to be introduced, which harnesses advances in artificial intelligence (AI) and affordable ...
C M, McLeavy, M H, Chunara, R J, Gravell, A, Rauf, A, Cushnie, C, Staley Talbot, R M, Hawkins   +6 more
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Deep learning based MRI reconstruction with transformer

Computer Methods and Programs in Biomedicine, 2023
Magnetic resonance imaging (MRI) has become one of the most powerful imaging techniques in medical diagnosis, yet the prolonged scanning time becomes a bottleneck for application. Reconstruction methods based on compress sensing (CS) have made progress in reducing this cost by acquiring fewer points in the k-space.
Zhengliang Wu, Weibin Liao, Chao Yan, Mangsuo Zhao, Guowen Liu, Ning Ma, Xuesong Li   +6 more
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Deep Learning Image Reconstruction for CT

Radiology, 2023
Filtered back projection (FBP) has been the standard CT image reconstruction method for 4 decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in several clinical applications. However, with faster and more advanced CT scanners, FBP has become increasingly obsolete.
Koetzier, Lennart R., Mastrodicasa, Domenico, Szczykutowicz, Timothy P., van der Werf, Niels R., Wang, Adam S., Sandfort, Veit, van der Molen, Aart J., Fleischmann, Dominik, Willemink, Martin J.   +8 more
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Deep Learning for Biomedical Image Reconstruction

2023
Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. The background theory of deep learning is introduced step-by-step, and by incorporating modeling fundamentals this book explains how to implement deep learning in a variety of modalities, including X-ray, CT, MRI ...
openaire   +1 more source

Deep learning for tomographic image reconstruction

Nature Machine Intelligence, 2020
Deep-learning-based tomographic imaging is an important application of artificial intelligence and a new frontier of machine learning. Deep learning has been widely used in computer vision and image analysis, which deal with existing images, improve these images, and produce features from them.
Ge Wang, Jong Chul Ye, Bruno De Man
openaire   +1 more source

Deep Learning: For Imaging Reconstruction

2022
Val M. Runge, Johannes T. Heverhagen
openaire   +1 more source

Deep Learning for Image Reconstruction

2019
Markus Haltmeier, Stephan Antholzer, Johannes Schwab   +2 more
openaire   +1 more source

Deep-learning-based MRI reconstruction

2019
Ge Wang, Yi Zhang, Xiaojing Ye, Xuanqin Mou   +3 more
openaire   +1 more source

Deep Learning for CT Image Reconstruction

2023
Haimiao Zhang, Bin Dong, Ge Wang, Baodong Liu   +3 more
openaire   +1 more source

Multidirectional deep learning for data reconstruction

84th EAGE Annual Conference & Exhibition, 2023
M.M. Abedi, D. Pardo
openaire   +1 more source