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GE Healthcare's Caption AI

Updated: Feb 14

Caption Health AI

No matter how experienced they may be with ultrasound, medical professionals can benefit from the AI technology that allows them to provide top-tier ultrasound exams to patients wherever and whenever they require them.

The Core Issue

A fundamental challenge exists which must be addressed. This challenge is the core issue that needs to be dealt with. Ultrasound can provide accurate results, yet it requires an extensive amount of training to become proficient in its use and the quality of the pictures produced may vary. The exam requires a combination of hand-eye coordination and visuals that can be difficult to master. Traditional software does not offer instruction on how to use the transducer to take a picture or any kind of real-time assessment of the images being taken. Poor images can bring about missed chances, wrong diagnoses, repeated studies, and incongruent interpretation.

Caption AI Solution

Caption Health AI Software

Caption AI is AI-driven technology that enables healthcare professionals to acquire diagnostic ultrasound images with ease. The software provides assistance throughout the scanning and image-capture procedure in real time, and also assesses the quality of the images and computes ejection fraction, which is a significant indicator of cardiac health.

Seeing the technology in action.

The Quality Meter provides users with an immediate indication of how well they are doing in obtaining a diagnostic-grade ultrasound image. This meter increases as the user progresses towards the recommended view, becoming green when the image is clinically sound. The AutoCapture feature then records the clip automatically.

Real-time instructions from Caption Guidance help users emulate the skills of a sonographer to ensure they can record a diagnostic-quality ultrasound image, guiding them to make the appropriate transducer movements for optimal capture.

The interpretation of the caption has the capacity to compute ejection fraction during the process of scanning from a maximum of three cardiac views, namely, AP4, AP2 and PLAX (a first in the industry).

Utilize a Scanning Method

Caption Health AI Software

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Individuals have the freedom to establish and adhere to a customizable protocol of ultrasound views that is either instruction-based or process-oriented. As they scan, they can quickly access the view they require.

When starting any examination, a diagram should be used to show the correct placement of the ultrasound transducer. A reference image can then be used as an illustration of what should be observed while the scan is taking place.

The program consistently monitors the ideal pictures seen during each scan, making sure that the most superior image from each perspective is always obtained. People have the option to investigate each angle with the guarantee that they can easily access the most excellent two-second snippet from their scan with a single click.

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Encrypted & Secure Data

Validation from Clinical Studies

Caption AI technology is completely shielded and follows HIPAA privacy regulations. The AI software can be safely downloaded and is routinely refreshed to guarantee data security.

A Scalable and Evolving Platform

By working with an exclusive group of developers, they're able to provide a comprehensive array of world-class algorithms that help with the analysis of ultrasound images. This enhances the dependability of the system, and shows the capability to provide early illness diagnosis.

The range of clinical uses for Caption Health's AI platform is expansive. Already, it has been applied to the capture and analysis of echocardiograms, and further development is being done to develop AI-based guidance and interpretation for lung ultrasound.

Clinically Validated

Clinical validation of the efficacy of their AI algorithms is present in peer-reviewed publications, in addition to ongoing clinical trials.

The Use of Artificial Intelligence Guidance for Rheumatic Heart Disease Screening by Novices AHA SCIENTIFIC SESSIONS 2022 OCTOBER 30, 2022

Machine Learning for Detection of Presence and Severity of Aortic Stenosis from B-Mode Ultrasound Images: Results of a Blinded Clinical Trial AHA SCIENTIFIC SESSIONS 2022 OCTOBER 30, 2022

Initial Experience with Artificial Intelligence-Guided Echocardiography Acquisition in Rural America: Implementation and Quality Assessment AHA SCIENTIFIC SESSIONS 2022 OCTOBER 30, 2022

Feasibility of Automated Quantification of Left Ventricular Function in Cancer Patients by Nurses Using Artificial Intelligence Guided Transthoracic Imaging ASE SCIENTIFIC SESSIONS 2022 JUNE 13, 2022

Utility of a Machine Learning Algorithm to Increase Physician Trainee Confidence In and Usage of Point-of-care Echocardiography ACC SCIENTIFIC SESSION 2022 APRIL 2, 2022

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