The potential role of artificial intelligence in lung cancer screening using low-dose computed tomography

PA Grenier, AL Brun, F Mellot - Diagnostics, 2022 - mdpi.com
Two large randomized controlled trials of low-dose CT (LDCT)-based lung cancer screening
(LCS) in high-risk smoker populations have shown a reduction in the number of lung cancer …

Advancements in automated classification of chronic obstructive pulmonary disease based on computed tomography imaging features through deep learning …

Z Zhu - Respiratory Medicine, 2024 - Elsevier
Abstract Chronic Obstructive Pulmonary Disease (COPD) represents a global public health
issue that significantly impairs patients' quality of life and overall health. As one of the …

[HTML][HTML] The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data

LH Boulogne, J Lorenz, D Kienzle, R Schön… - Medical Image …, 2024 - Elsevier
Challenges drive the state-of-the-art of automated medical image analysis. The quantity of
public training data that they provide can limit the performance of their solutions. Public …

Emphysema quantification using ultra-low-dose chest CT: efficacy of deep learning-based image reconstruction

JA Yeom, KU Kim, M Hwang, JW Lee, KI Kim, YS Song… - Medicina, 2022 - mdpi.com
Background and Objectives: Although reducing the radiation dose level is important during
diagnostic computed tomography (CT) applications, effective image quality enhancement …

Reduce Measurement Variability at Longitudinal Quantitative CT to Improve Assessment of Emphysema

JM Goo - Radiology, 2024 - pubs.rsna.org
Dr Goo is a professor in the Department of Radiology at Seoul National University College of
Medicine. His research interests include lung cancer imaging, lung cancer screening, and …

Deep Learning–Based Kernel Adaptation Enhances Quantification of Emphysema on Low-Dose Chest CT for Predicting Long-Term Mortality

H Park, EJ Hwang, JM Goo - Investigative Radiology, 2024 - journals.lww.com
Objectives The aim of this study was to ascertain the predictive value of quantifying
emphysema using low-dose computed tomography (LDCT) post deep learning–based …

Predicting Postoperative Lung Function in Patients with Lung Cancer Using Imaging Biomarkers

OB Kwon, HU Lee, HE Park, JY Choi, JW Kim, SH Lee… - Diseases, 2024 - mdpi.com
There have been previous studies conducted to predict postoperative lung function with
pulmonary function tests (PFTs). Computing tomography (CT) can quantitatively measure …

Predicting postoperative lung function in lung cancer patients by using imaging biomarkers

OB Kwon, HU Lee, HE Park, JY Choi, JW Kim, SH Lee… - 2023 - researchsquare.com
Background There were previous studies to predict postoperative lung function with
pulmonary function test (PFT). Computing tomography (CT) can quantitatively measure …