We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App

Largest Model Trained On Echocardiography Images Assesses Heart Structure and Function

By MedImaging International staff writers
Posted on 03 May 2024
Print article
Image: The powerful machine learning algorithm can “interpret” echocardiogram images and assess key findings (Photo courtesy of 123RF)
Image: The powerful machine learning algorithm can “interpret” echocardiogram images and assess key findings (Photo courtesy of 123RF)

Foundation models represent an exciting frontier in generative artificial intelligence (AI), yet many lack the specialized medical data needed to make them applicable in healthcare settings. While there are existing AI models for echocardiograms, these are typically trained on relatively small datasets comprising tens of thousands of examples. In a significant advancement, a team of AI experts has now compiled a dataset that includes over one million echocardiograms, or cardiac ultrasound videos, complete with clinical interpretations. Utilizing this vast database, they have developed EchoCLIP, a sophisticated machine-learning algorithm capable of interpreting echocardiogram images and analyzing crucial findings.

The team of investigators at Cedars-Sinai (Los Angeles, CA, USA) built a dataset of 1,032,975 cardiac ultrasound videos and corresponding expert interpretations. This extensive collection enabled the development of EchoCLIP, which offers clinician-level evaluations of heart function, past surgeries, and implanted devices. Moreover, EchoCLIP can identify a single patient across multiple videos and timepoints, recognizing clinically significant changes in heart conditions. EchoCLIP holds promise in revolutionizing how cardiologists assess echocardiograms by providing preliminary cardiac assessments, tracking changes over time, and identifying common cardiac conditions.

In studies, EchoCLIP has demonstrated high accuracy in measuring cardiac function and identifying devices such as pacemakers and repaired mitral and aortic valves. Additionally, it has proven capable of recognizing unique patients across different studies and detecting important clinical changes like post-surgical modifications. The development of EchoCLIP has also facilitated the generation of preliminary text interpretations of echocardiogram images, further enhancing its utility in clinical settings.

“To our knowledge, this is the largest model trained on echocardiography images,” said corresponding author David Ouyang, MD, a faculty member in the Department of Cardiology at the Smidt Heart Institute. “EchoCLIP’s uniquely strong performance in image interpretation is a result of its training on almost tenfold more data than existing models. Our results suggest that large datasets of medical imaging and expert-adjudicated interpretations can serve as the basis for training medical foundation models, which are a form of generative artificial intelligence.”

Related Links:

Gold Member
Solid State Kv/Dose Multi-Sensor
Brachytherapy Planning System
Oncentra Brachy
CT Phantom
CIRS Model 610 AAPM CT Performance Phantom
Ceiling-Mounted Digital Radiography System
Radiography 5000 C

Print article


Nuclear Medicine

view channel
Image: Researchers have identified a new imaging biomarker for tumor responses to ICB therapy (Photo courtesy of 123RF)

New PET Biomarker Predicts Success of Immune Checkpoint Blockade Therapy

Immunotherapies, such as immune checkpoint blockade (ICB), have shown promising clinical results in treating melanoma, non-small cell lung cancer, and other tumor types. However, the effectiveness of these... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.