Pre-deployment assessment of an AI model to assist radiologists in chest X-ray detection and identification of lead-less implanted electronic devices for pre-MRI safety …

RD White, M Demirer, V Gupta… - Journal of Medical …, 2022 - spiedigitallibrary.org
Purpose Chest X-ray (CXR) use in pre-MRI safety screening, such as for lead-less implanted
electronic device (LLIED) recognition, is common. To assist CXR interpretation, we “pre …

[HTML][HTML] Deep learning-based algorithm for the detection and characterization of MRI safety of cardiac implantable electronic devices on chest radiographs

UH Kim, MY Kim, EA Park, W Lee, WH Lim… - Korean Journal of …, 2021 - ncbi.nlm.nih.gov
Objective With the recent development of various MRI-conditional cardiac implantable
electronic devices (CIEDs), the accurate identification and characterization of CIEDs have …

Machine learning augmented interpretation of chest X-rays: a systematic review

HK Ahmad, MR Milne, QD Buchlak, N Ektas… - Diagnostics, 2023 - mdpi.com
Limitations of the chest X-ray (CXR) have resulted in attempts to create machine learning
systems to assist clinicians and improve interpretation accuracy. An understanding of the …

Neural network detection of pacemakers for MRI safety

MDV Thurston, DH Kim, HK Wit - Journal of Digital Imaging, 2022 - Springer
Flagging the presence of cardiac devices such as pacemakers before an MRI scan is
essential to allow appropriate safety checks. We assess the accuracy with which a machine …

[HTML][HTML] Integration of a deep learning system for automated chest x-ray interpretation in the emergency department: A proof-of-concept

C Mosquera, F Binder, FN Diaz, A Seehaus… - Intelligence-Based …, 2021 - Elsevier
Purpose The translation of deep learning (DL) techniques from research to effective clinical
implementations has to overcome an important gap between the DL-development setting …

Performing MRI on patients with MRI-conditional and non-conditional cardiac implantable electronic devices: an update for radiologists

A Cunqueiro, ML Lipton, RJ Dym, VR Jain, J Sterman… - Clinical Radiology, 2019 - Elsevier
Pacemakers and implantable cardioverter defibrillators are commonly encountered in
clinical practice, and entails special consideration when magnetic resonance imaging (MRI) …

Artificial intelligence-based software with CE mark for chest X-ray interpretation: Opportunities and challenges

SC Fanni, A Marcucci, F Volpi, S Valentino, E Neri… - Diagnostics, 2023 - mdpi.com
Chest X-ray (CXR) is the most important technique for performing chest imaging, despite its
well-known limitations in terms of scope and sensitivity. These intrinsic limitations of CXR …

Computer-aided detection and identification of implanted cardiac devices on chest radiography utilizing deep convolutional neural networks, a form of machine …

M Weinreich, B Weinreich, JJ Chudow… - Journal of the American …, 2019 - jacc.org
Background Identification of implanted cardiac devices is paramount to effective care of
patients in the emergency department, operating room, radiology suite, and …

Cross-population train/test deep learning model: abnormality screening in chest x-rays

D Das, KC Santosh, U Pal - 2020 IEEE 33rd international …, 2020 - ieeexplore.ieee.org
Automated radiological screening is an advancing field in which algorithms and predictive
models are used to detect abnormalities in Chest X-rays (CXRs). Traditionally, in machine …

Using artificial intelligence to stratify normal versus abnormal chest X-rays: external validation of a deep learning algorithm at East Kent Hospitals University NHS …

SR Blake, N Das, M Tadepalli, B Reddy, A Singh… - Diagnostics, 2023 - mdpi.com
Background: The chest radiograph (CXR) is the most frequently performed radiological
examination worldwide. The increasing volume of CXRs performed in hospitals causes …