THANK YOU FOR SUBSCRIBING
Weekly Brief
Be first to read the latest tech news, Industry Leader's Insights, and CIO interviews of medium and large enterprises exclusively from Healthcare Tech Outlook
AI can empower clinicians with ultrasound image acquisition capability to bring the advantages of ultrasound to more patients, standardize the quality of care, and help healthcare facilities realize cost and time savings.
Viviana Moran, Director, Department of OBGYN & Women’s Health, Montefiore Health System
Ultrasound imaging is considered as one of the fastest, safest, and cheapest medical diagnostic tools available. Ultrasound is a device like no other in medicine because of its well-known qualities. Most significantly, this is a work of the hand and the eye, coupling the art of reasoning, common sense, and a unique opportunity for the physician to be in direct contact with the patient. There is a feast of innovation happening across this imaging modality, and there are high expectations around the capabilities of Artificial Intelligence (AI). Eventhough using AI in ultrasound is still at an early stage of development; the potential opportunities to deploy this technology remain high. Here is more to know.
AI leads to the automation of time-consuming activities, and it makes picking out the ideal image from the vast data set and quantification easier. Many high-end systems already deployed some level of AI, and new systems going forward will also have some AI levels in them. Implementing AI into the background of some ultrasound systems began a few years ago. The objective is to increase workflow and speed. AI can identify, color code, and segment the anatomy in the scanning part. It can also choose the best scanning slice view for a specific evaluation, extract it from a 3D dataset, and enhance the reproducibility regardless of the sonographer’s expertise.
The potential for utilizing AI within the identification and diagnosis phases of the ultrasound imaging workflow remains high, and solutions are still early. The key drivers behind deploying AI within detection and diagnosis are concentrated on increasing productivity and diagnostic confidence and also improving the ease of use for new users. Medical practitioners have been using AI technology to offer detection support as a second read solution. This allows radiologists to compare their findings with automated detection software powered by AI.
