How far have we come? Artificial intelligence for chest radiograph interpretation
Due to recent advances in artificial intelligence, there is renewed interest in automating
interpretation of imaging tests. Chest radiographs are particularly interesting due to many …
interpretation of imaging tests. Chest radiographs are particularly interesting due to many …
Artificial intelligence solutions for analysis of X-ray images
SJ Adams, RDE Henderson, X Yi… - … of Radiologists Journal, 2021 - journals.sagepub.com
Artificial intelligence (AI) presents a key opportunity for radiologists to improve quality of care
and enhance the value of radiology in patient care and population health. The potential …
and enhance the value of radiology in patient care and population health. The potential …
Computer-aided diagnosis in chest radiography: a survey
B Van Ginneken, BMTH Romeny… - IEEE Transactions on …, 2001 - ieeexplore.ieee.org
The traditional chest radiograph is still ubiquitous in clinical practice, and will likely remain
so for quite some time. Yet, its interpretation is notoriously difficult. This explains the …
so for quite some time. Yet, its interpretation is notoriously difficult. This explains the …
Artificial intelligence for clinical interpretation of bedside chest radiographs
Background Supine chest radiography for bedridden patients in intensive care units (ICUs)
is one of the most frequently ordered imaging studies worldwide. Purpose To evaluate the …
is one of the most frequently ordered imaging studies worldwide. Purpose To evaluate the …
Association of artificial intelligence–aided chest radiograph interpretation with reader performance and efficiency
Importance The efficient and accurate interpretation of radiologic images is paramount.
Objective To evaluate whether a deep learning–based artificial intelligence (AI) engine used …
Objective To evaluate whether a deep learning–based artificial intelligence (AI) engine used …
Assessment of convolutional neural networks for automated classification of chest radiographs
Purpose To assess the ability of convolutional neural networks (CNNs) to enable high-
performance automated binary classification of chest radiographs. Materials and Methods In …
performance automated binary classification of chest radiographs. Materials and Methods In …
Chest radiograph interpretation with deep learning models: assessment with radiologist-adjudicated reference standards and population-adjusted evaluation
Background Deep learning has the potential to augment the use of chest radiography in
clinical radiology, but challenges include poor generalizability, spectrum bias, and difficulty …
clinical radiology, but challenges include poor generalizability, spectrum bias, and difficulty …
Artificial intelligence applications for thoracic imaging
G Chassagnon, M Vakalopoulou, N Paragios… - European journal of …, 2020 - Elsevier
Artificial intelligence is a hot topic in medical imaging. The development of deep learning
methods and in particular the use of convolutional neural networks (CNNs), have led to …
methods and in particular the use of convolutional neural networks (CNNs), have led to …
Comparison of chest radiograph interpretations by artificial intelligence algorithm vs radiology residents
Importance Chest radiography is the most common diagnostic imaging examination
performed in emergency departments (EDs). Augmenting clinicians with automated …
performed in emergency departments (EDs). Augmenting clinicians with automated …
Computer-aided diagnosis in chest radiography: results of large-scale observer tests at the 1996–2001 RSNA scientific assemblies
H Abe, H MacMahon, R Engelmann, Q Li, J Shiraishi… - Radiographics, 2003 - pubs.rsna.org
Since 1996, computer-aided diagnosis (CAD) schemes have been presented as interactive
demonstrations on computer workstations at each scientific assembly of the Radiological …
demonstrations on computer workstations at each scientific assembly of the Radiological …