AI for ultrasounds

FUJIFILM SonoSite taps the Allen Institute for Artificial Intelligence (AI2) Incubator to interpret ultrasound images

Mel J. Yeates
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SEATTLE and BOTHELL, Wash.—FUJIFILM SonoSite, Inc., a company that specializes in developing cutting-edge point-of-care ultrasound solutions, and the Allen Institute of Artificial Intelligence (AI2) Incubator, builder of AI-first startups, have announced a collaboration to interpret ultrasound images with AI, which will enable new ultrasound applications and enhanced accuracy.
 
“The AI2 Incubator was a perfect place to look for help in creating breakthrough technology. They have the type of talent that is hard to recruit, combined with the ambition of a startup. We look forward to collaborating more,” said Rich Fabian, president and chief operating officer of FUJIFILM SonoSite.
 
Fujifilm SonoSite has enlisted assistance from the AI2 Incubator to deploy deep learning models on portable ultrasound products. Together the AI2 Incubator and Fujifilm SonoSite will work to improve image analysis, allowing for the interpretation of a much wider range of ultrasound scenarios.
 
“The combination of deep learning and medical imaging is very exciting for the future of detection - better care and catching anomalies earlier and faster is a core mission,” added Diku Mandavia, M.D., FACEP, FRCPC, senior vice president and chief medical officer of FUJIFILM SonoSite.
 
Within the field of medical imaging, deep learning-based AI techniques have brought breakthroughs across a wide range of scenarios, including detecting tuberculosis (TB) in x-ray scans and diagnosing metastatic breast cancer in pathology slides. Compared to other modalities like x-ray, CT and PET, ultrasound is portable, more affordable and does not expose patients to ionizing radiation.
 
Ultrasound’s comparative disadvantage was traditionally its lower image quality. While great improvements have been made over the past two decades, deep learning algorithms now stand to significantly increase both the accuracy and rapid assessment ability of ultrasound technology.
 
“In tackling this challenge, we are pushing deep learning, computer vision, and medical imaging into uncharted territory,” noted Dr. Vu Ha, technical director at the AI2 Incubator. “In building new AI-based capabilities in affordable ultrasound devices, we hope to bring them to underserved markets to improve healthcare around the world.”

FUJIFILM SonoSite also announced in July the launch of a strategic relationship with Partners HealthCare to apply artificial intelligence to improve the utility and functionality of portable ultrasound. The organizations will collaborate to enhance ultrasound technology with AI to enable clinicians to perform scans at the point-of-care, further expanding the accessibility of this technology for clinicians and patients.

According to Andrew Liteplo, M.D., MGH Department of Emergency Medicine, “If we build scanners that can be used by non-expert users both inside and outside the hospital, we can likely reduce the time delay between trauma and diagnosis, which will translate to more rapid interventions and improved outcomes.”

The collaboration will be executed through the MGH & BWH Center for Clinical Data Science, helped by the extensive data assets, computational infrastructure and clinical expertise of the Partners HealthCare system.

“Allowing for even greater integration of ultrasound into our healthcare delivery system requires smarter machines,” stated Keith Dreyer, DO, Ph.D., FACR, FSIIM, chief data science officer at Partners HealthCare. “In emergency settings, the efficiency and cost-effectiveness of portable ultrasound makes is a critical companion to other imaging modalities.”

The first project under the collaboration will target some of the more complex emergency medicine procedures using AI-enabled portable ultrasound.

“This collaboration is really focused on embedding AI in portable ultrasound with the goal of providing assistance in 2D image interpretation along with the automation of measurements and calculations - the type of automation that will allow us to increase the accessibility of this critical technology while still delivering high diagnostic value,” Mandavia emphasized in a press release.

“We have always listened carefully to our customers to ensure their needs are being met and I am proud that we will be able to offer them AI enhanced technology to expand their utilization of ultrasound, increasing the quality of care they can provide while saving our healthcare system money,” Fabian concluded.

Mel J. Yeates

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