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Deep learning for PET image reconstruction
This article reviews the use of a subdiscipline of artificial intelligence (AI), deep learning, for
the reconstruction of images in positron emission tomography (PET). Deep learning can be …
the reconstruction of images in positron emission tomography (PET). Deep learning can be …
Artificial intelligence in image reconstruction: the change is here
Innovations in CT have been impressive among imaging and medical technologies in both
the hardware and software domain. The range and speed of CT scanning improved from the …
the hardware and software domain. The range and speed of CT scanning improved from the …
Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study
Objectives To assess the impact on image quality and dose reduction of a new deep
learning image reconstruction (DLIR) algorithm compared with a hybrid iterative …
learning image reconstruction (DLIR) algorithm compared with a hybrid iterative …
Deep equilibrium architectures for inverse problems in imaging
Recent efforts on solving inverse problems in imaging via deep neural networks use
architectures inspired by a fixed number of iterations of an optimization method. The number …
architectures inspired by a fixed number of iterations of an optimization method. The number …
Deep learning for biomedical image reconstruction: A survey
Medical imaging is an invaluable resource in medicine as it enables to peer inside the
human body and provides scientists and physicians with a wealth of information …
human body and provides scientists and physicians with a wealth of information …
Hypernetwork-based physics-driven personalized federated learning for CT imaging
In clinical practice, computed tomography (CT) is an important noninvasive inspection
technology to provide patients' anatomical information. However, its potential radiation risk is …
technology to provide patients' anatomical information. However, its potential radiation risk is …
Artificial intelligence with deep learning in nuclear medicine and radiology
The use of deep learning in medical imaging has increased rapidly over the past few years,
finding applications throughout the entire radiology pipeline, from improved scanner …
finding applications throughout the entire radiology pipeline, from improved scanner …
The use of deep learning methods in low-dose computed tomography image reconstruction: a systematic review
Conventional reconstruction techniques, such as filtered back projection (FBP) and iterative
reconstruction (IR), which have been utilised widely in the image reconstruction process of …
reconstruction (IR), which have been utilised widely in the image reconstruction process of …
Deep learning–based image reconstruction for brain CT: improved image quality compared with adaptive statistical iterative reconstruction-Veo (ASIR-V)
I Kim, H Kang, HJ Yoon, BM Chung, NY Shin - Neuroradiology, 2021 - Springer
Purpose To compare the image quality of brain computed tomography (CT) images
reconstructed with deep learning–based image reconstruction (DLIR) and adaptive …
reconstructed with deep learning–based image reconstruction (DLIR) and adaptive …
Low‐dose CT reconstruction with Noise2Noise network and testing‐time fine‐tuning
Purpose Deep learning‐based image denoising and reconstruction methods demonstrated
promising performance on low‐dose CT imaging in recent years. However, most existing …
promising performance on low‐dose CT imaging in recent years. However, most existing …