Supervised Deep Learning for Perioperative Cardiovascular Monitoring
V Wøien - 2022 - ntnuopen.ntnu.no
På grunn av høy risiko for kardiovaskulære komplikasjoner under hjertekirurgi, overvåker
leger pasientens hjerte i den perioperative fasen. Ekkokardiografi er mye brukt til å vurdere …
leger pasientens hjerte i den perioperative fasen. Ekkokardiografi er mye brukt til å vurdere …
Automatic detection of mitral annular plane systolic excursion from transesophageal echocardiography using deep learning
T Nordal - 2019 - ntnuopen.ntnu.no
Perioperativ monitorering av hjertet til pasienter som gjennomgår operasjoner er nødvendig
for å forsikre at hjertets funksjon gjennoprettes. I dag gjennomføres periopertiv monitorering …
for å forsikre at hjertets funksjon gjennoprettes. I dag gjennomføres periopertiv monitorering …
[HTML][HTML] Basal strain estimation in transesophageal echocardiography using unsupervised deep learning
T Haukom - 2019 - ntnuopen.ntnu.no
Pasienter med behov for hjertekirurgi løper en risiko for alvorlige komplikasjoner under og
etter inngrepet, og blir derfor overvåket gjennom den perioperative perioden …
etter inngrepet, og blir derfor overvåket gjennom den perioperative perioden …
[HTML][HTML] Automated segmental cardiac monitoring by advanced computerized artificial intelligence on intra-operative three-dimensional ultrasound recordings
AA Taskén - 2021 - ntnuopen.ntnu.no
Medisinsk ultralyd er et effektivt verktøy for å hente ut data fra menneskekroppens indre og
praktiseres ofte i kirurgien for å vurdere hjertefunksjon. Perioperativ hjerteovervåking er …
praktiseres ofte i kirurgien for å vurdere hjertefunksjon. Perioperativ hjerteovervåking er …
Leveraging Deep Learning Models for Accurate and Reproducible Cardiac Measurements in Echocardiography
A Stojmenski, M Mihajlov - … on E-mobility, Power Control and …, 2024 - ieeexplore.ieee.org
The primary metrics recorded during ultrasound sessions focused on cardiac assessment
are focused on the size of the heart's features, its two chambers and pre-chambers …
are focused on the size of the heart's features, its two chambers and pre-chambers …
Basal strain estimation in transesophageal echocardiography (TEE) using deep learning based unsupervised deformable image registration
As of today, perioperative monitoring in the operating room is based on vital signs and
clinical observations by the anesthesiologist. This, however, does not offer a complete …
clinical observations by the anesthesiologist. This, however, does not offer a complete …
Automatic analysis in echocardiography using machine learning
A Østvik - 2021 - ntnuopen.ntnu.no
Echocardiography is the cornerstone of modern cardiac imaging due to its availability, low
cost and real-time functionality. The modality has enabled sophisticated non-invasive …
cost and real-time functionality. The modality has enabled sophisticated non-invasive …
Using machine learning to predict perfusionists' critical decision-making during cardiac surgery
The cardiac surgery operating room is a high-risk and complex environment in which
multiple experts work as a team to provide safe and excellent care to patients. During the …
multiple experts work as a team to provide safe and excellent care to patients. During the …
[HTML][HTML] Automated estimation of mitral annular plane systolic excursion by artificial intelligence from 3D ultrasound recordings
Perioperative monitoring of cardiac function is beneficial for early detection of cardiovascular
complications. The standard of care for cardiac monitoring performed by trained …
complications. The standard of care for cardiac monitoring performed by trained …
Pragmatic Evaluation of a Deep-Learning Algorithm to Automate Ejection Fraction on Hand-Held, Point-of-Care Echocardiography in a Cardiac Surgical Operating …
EJ MacKay, S Bharat, RA Mukaddim, R Erkamp… - … of Cardiothoracic and …, 2024 - Elsevier
Objective To test the correlation of ejection fraction (EF) estimated by a deep-learning-
based, automated algorithm (Auto EF) versus an EF estimated by Simpson's method. Design …
based, automated algorithm (Auto EF) versus an EF estimated by Simpson's method. Design …