State of the art in abdominal CT: the limits of iterative reconstruction algorithms

A Mileto, LS Guimaraes, CH McCollough, JG Fletcher… - Radiology, 2019 - pubs.rsna.org
The development and widespread adoption of iterative reconstruction (IR) algorithms for CT
have greatly facilitated the contemporary practice of radiation dose reduction during …

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 …

Image quality and lesion detection on deep learning reconstruction and iterative reconstruction of submillisievert chest and abdominal CT

R Singh, SR Digumarthy, VV Muse… - American Journal of …, 2020 - Am Roentgen Ray Soc
OBJECTIVE. The objective of this study was to compare image quality and clinically
significant lesion detection on deep learning reconstruction (DLR) and iterative …

Image quality assessment of abdominal CT by use of new deep learning image reconstruction: initial experience

CT Jensen, X Liu, EP Tamm… - American Journal of …, 2020 - Am Roentgen Ray Soc
OBJECTIVE. The purpose of this study was to perform quantitative and qualitative evaluation
of a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic …

Reduced-dose deep learning reconstruction for abdominal CT of liver metastases

CT Jensen, S Gupta, MM Saleh, X Liu, VK Wong… - Radiology, 2022 - pubs.rsna.org
Background Assessment of liver lesions is constrained as CT radiation doses are lowered;
evidence suggests deep learning reconstructions mitigate such effects. Purpose To evaluate …

CT noise-reduction methods for lower-dose scanning: strengths and weaknesses of iterative reconstruction algorithms and new techniques

P Mohammadinejad, A Mileto, L Yu, S Leng… - Radiographics, 2021 - pubs.rsna.org
Iterative reconstruction (IR) algorithms are the most widely used CT noise-reduction method
to improve image quality and have greatly facilitated radiation dose reduction within the …

Management of incidental liver lesions on CT: a white paper of the ACR Incidental Findings Committee

RM Gore, PJ Pickhardt, KJ Mortele, EK Fishman… - Journal of the American …, 2017 - Elsevier
Abstract The ACR Committee on Incidental Findings presents recommendations for
managing liver lesions that are incidentally detected on CT. These recommendations …

Detection of colorectal hepatic metastases is superior at standard radiation dose CT versus reduced dose CT

CT Jensen, NA Wagner-Bartak, LN Vu, X Liu, B Raval… - Radiology, 2019 - pubs.rsna.org
Purpose To evaluate colorectal cancer hepatic metastasis detection and characterization
between reduced radiation dose (RD) and standard dose (SD) contrast material–enhanced …

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 …

Image quality in liver CT: low-dose deep learning vs standard-dose model-based iterative reconstructions

S Park, JH Yoon, I Joo, MH Yu, JH Kim, J Park… - European …, 2022 - Springer
Objectives To compare the overall image quality and detectability of significant (malignant
and pre-malignant) liver lesions of low-dose liver CT (LDCT, 33.3% dose) using deep …