Deep learning image reconstruction for CT: technical principles and clinical prospects

LR Koetzier, D Mastrodicasa, TP Szczykutowicz… - Radiology, 2023 - pubs.rsna.org
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 …

A review of deep learning CT reconstruction: concepts, limitations, and promise in clinical practice

TP Szczykutowicz, GV Toia, A Dhanantwari… - Current Radiology …, 2022 - Springer
Abstract Purpose of Review Deep Learning reconstruction (DLR) is the current state-of-the-
art method for CT image formation. Comparisons to existing filter back-projection, iterative …

Quantum iterative reconstruction for abdominal photon-counting detector CT improves image quality

T Sartoretti, A Landsmann, D Nakhostin, M Eberhard… - Radiology, 2022 - pubs.rsna.org
Background An iterative reconstruction (IR) algorithm was introduced for clinical photon-
counting detector (PCD) CT. Purpose To investigate the image quality and the optimal …

Improving image quality and reducing radiation dose for pediatric CT by using deep learning reconstruction

SL Brady, AT Trout, E Somasundaram, CG Anton, Y Li… - Radiology, 2021 - pubs.rsna.org
Background CT deep learning reconstruction (DLR) algorithms have been developed to
remove image noise. How the DLR affects image quality and radiation dose reduction has …

[HTML][HTML] Validation of deep-learning image reconstruction for low-dose chest computed tomography scan: emphasis on image quality and noise

JH Kim, HJ Yoon, E Lee, I Kim, YK Cha… - Korean journal of …, 2021 - ncbi.nlm.nih.gov
Objective Iterative reconstruction degrades image quality. Thus, further advances in image
reconstruction are necessary to overcome some limitations of this technique in low-dose …

[HTML][HTML] Computed tomography 2.0: new detector technology, AI, and other developments

M Lell, M Kachelrieß - Investigative Radiology, 2023 - journals.lww.com
Computed tomography (CT) dramatically improved the capabilities of diagnostic and
interventional radiology. Starting in the early 1970s, this imaging modality is still evolving …

Virtual noncontrast abdominal imaging with photon-counting detector CT

V Mergen, D Racine, L Jungblut, T Sartoretti, S Bickel… - Radiology, 2022 - pubs.rsna.org
Background Accurate CT attenuation and diagnostic quality of virtual noncontrast (VNC)
images acquired with photon-counting detector (PCD) CT are needed to replace true …

CT iterative vs deep learning reconstruction: comparison of noise and sharpness

C Park, KS Choo, Y Jung, HS Jeong, JY Hwang… - European …, 2021 - Springer
Objectives To compare image noise and sharpness of vessels, liver, and muscle in lower
extremity CT angiography between “adaptive statistical iterative reconstruction-V”(ASIR-V) …

[HTML][HTML] Task-based characterization of a deep learning image reconstruction and comparison with filtered back-projection and a partial model-based iterative …

D Racine, F Becce, A Viry, P Monnin, B Thomsen… - Physica Medica, 2020 - Elsevier
Purpose We aimed to thoroughly characterize image quality of a novel deep learning image
reconstruction (DLIR), and investigate its potential for dose reduction in abdominal CT in …

Advanced CT techniques for assessing hepatocellular carcinoma

Y Nakamura, T Higaki, Y Honda, F Tatsugami… - La radiologia …, 2021 - Springer
Hepatocellular carcinoma (HCC) is the sixth-most common cancer in the world, and hepatic
dynamic CT studies are routinely performed for its evaluation. Ongoing studies are …