[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 …
interventional radiology. Starting in the early 1970s, this imaging modality is still evolving …
A review of deep learning CT reconstruction: concepts, limitations, and promise in clinical practice
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 …
art method for CT image formation. Comparisons to existing filter back-projection, iterative …
Artificial intelligence in emergency radiology: where are we going?
M Cellina, M Cè, G Irmici, V Ascenti, E Caloro… - Diagnostics, 2022 - mdpi.com
Emergency Radiology is a unique branch of imaging, as rapidity in the diagnosis and
management of different pathologies is essential to saving patients' lives. Artificial …
management of different pathologies is essential to saving patients' lives. Artificial …
Deep learning reconstruction for contrast-enhanced CT of the upper abdomen: similar image quality with lower radiation dose in direct comparison with iterative …
Objective To evaluate the effect of a commercial deep learning algorithm on the image
quality of chest CT, focusing on the upper abdomen. Methods One hundred consecutive …
quality of chest CT, focusing on the upper abdomen. Methods One hundred consecutive …
The effect of deep learning reconstruction on abdominal CT densitometry and image quality: a systematic review and meta-analysis
Objective To determine the difference in CT values and image quality of abdominal CT
images reconstructed by filtered back-projection (FBP), hybrid iterative reconstruction (IR) …
images reconstructed by filtered back-projection (FBP), hybrid iterative reconstruction (IR) …
Deep learning image reconstruction for improvement of image quality of abdominal computed tomography: comparison with hybrid iterative reconstruction
Y Ichikawa, Y Kanii, A Yamazaki, N Nagasawa… - Japanese Journal of …, 2021 - Springer
Purpose To evaluate the usefulness of the deep learning image reconstruction (DLIR) to
enhance the image quality of abdominal CT, compared to iterative reconstruction technique …
enhance the image quality of abdominal CT, compared to iterative reconstruction technique …
[HTML][HTML] Fast and low-dose medical imaging generation empowered by hybrid deep-learning and iterative reconstruction
S Liao, Z Mo, M Zeng, J Wu, Y Gu, G Li, G Quan… - Cell Reports …, 2023 - cell.com
Fast and low-dose reconstructions of medical images are highly desired in clinical routines.
We propose a hybrid deep-learning and iterative reconstruction (hybrid DL-IR) framework …
We propose a hybrid deep-learning and iterative reconstruction (hybrid DL-IR) framework …
Deep learning image reconstruction for improving image quality of contrast-enhanced dual-energy CT in abdomen
M Sato, Y Ichikawa, K Domae, K Yoshikawa, Y Kanii… - European …, 2022 - Springer
Objectives To evaluate the usefulness of deep learning image reconstruction (DLIR) to
improve the image quality of dual-energy computed tomography (DECT) of the abdomen …
improve the image quality of dual-energy computed tomography (DECT) of the abdomen …
Deep learning image reconstruction algorithm reduces image noise while alters radiomics features in dual-energy CT in comparison with conventional iterative …
J Zhong, Y **a, Y Chen, J Li, W Lu, X Shi, J Feng… - European …, 2023 - Springer
Objectives To compare image quality between a deep learning image reconstruction (DLIR)
algorithm and conventional iterative reconstruction (IR) algorithms in dual-energy CT …
algorithm and conventional iterative reconstruction (IR) algorithms in dual-energy CT …
Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration
Y Noda, N Kawai, S Nagata, F Nakamura, T Mori… - European …, 2022 - Springer
Objectives To evaluate the image quality and iodine concentration (IC) measurements in
pancreatic protocol dual-energy computed tomography (DECT) reconstructed using deep …
pancreatic protocol dual-energy computed tomography (DECT) reconstructed using deep …