[HTML][HTML] Clinical implementation of deep learning in thoracic radiology: potential applications and challenges

EJ Hwang, CM Park - Korean journal of radiology, 2020 - ncbi.nlm.nih.gov
Chest X-ray radiography and computed tomography, the two mainstay modalities in thoracic
radiology, are under active investigation with deep learning technology, which has shown …

Deep learning reconstruction shows better lung nodule detection for ultra–low-dose chest CT

B Jiang, N Li, X Shi, S Zhang, J Li, GH de Bock… - Radiology, 2022 - pubs.rsna.org
Background Ultra–low-dose (ULD) CT could facilitate the clinical implementation of large-
scale lung cancer screening while minimizing the radiation dose. However, traditional image …

Lung nodule volume quantification and shape differentiation with an ultra-high resolution technique on a photon-counting detector computed tomography system

W Zhou, J Montoya, R Gutjahr, A Ferrero… - Journal of Medical …, 2017 - spiedigitallibrary.org
An ultra-high resolution (UHR) mode, with a detector pixel size of 0.25 mm× 0.25 mm
relative to isocenter, has been implemented on a whole body research photon-counting …

A generic framework to simulate realistic lung, liver and renal pathologies in CT imaging

J Solomon, E Samei - Physics in Medicine & Biology, 2014 - iopscience.iop.org
Abstract Realistic three-dimensional (3D) mathematical models of subtle lesions are
essential for many computed tomography (CT) studies focused on performance evaluation …

Statistical issues in the comparison of quantitative imaging biomarker algorithms using pulmonary nodule volume as an example

NA Obuchowski, HX Barnhart… - … methods in medical …, 2015 - journals.sagepub.com
Quantitative imaging biomarkers are being used increasingly in medicine to diagnose and
monitor patients' disease. The computer algorithms that measure quantitative imaging …

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR)

B Chen, H Barnhart, S Richard, M Robins… - Medical …, 2013 - Wiley Online Library
Purpose: Volume quantifications of lung nodules with multidetector computed tomography
(CT) images provide useful information for monitoring nodule developments. The accuracy …

Accuracy of lung nodule volumetry in low-dose CT with iterative reconstruction: an anthropomorphic thoracic phantom study

KW Doo, EY Kang, HS Yong, OH Woo… - The British Journal of …, 2014 - academic.oup.com
Objective: The purpose of this study was to assess accuracy of lung nodule volumetry in low-
dose CT with application of iterative reconstruction (IR) according to nodule size, nodule …

Comparison of 1D, 2D, and 3D nodule sizing methods by radiologists for spherical and complex nodules on thoracic CT phantom images

N Petrick, HJG Kim, D Clunie, K Borradaile, R Ford… - Academic radiology, 2014 - Elsevier
Rationale and Objectives To estimate and statistically compare the bias and variance of
radiologists measuring the size of spherical and complex synthetic nodules. Materials and …

Incorporation of CAD (computer-aided detection) with thin-slice lung CT in routine 18F-FDG PET/CT imaging read-out protocol for detection of lung nodules

U Bhure, M Cieciera, D Lehnick… - European Journal of …, 2023 - Springer
Objective To evaluate the detection rate and performance of 18F-FDG PET alone (PET), the
combination of PET and low-dose thick-slice CT (PET/lCT), PET and diagnostic thin-slice CT …

Effects of guided random sampling of TCCs on blood flow values in CT perfusion studies of lung tumors

A Gibaldi, D Barone, G Gavelli, S Malavasi… - Academic radiology, 2015 - Elsevier
Rationale and Objectives Tissue perfusion is commonly used to evaluate lung tumor lesions
through dynamic contrast-enhanced computed tomography (DCE-CT). The aim of this study …