Latest news with #See-Mode
Yahoo
3 days ago
- Health
- Yahoo
RadNet acquires See-Mode to bolster AI ultrasound screening for thyroid cancer
RadNet, a DeepHealth company, has acquired See-Mode, an artificial intelligence (AI)-based ultrasound imaging developer. The US company's acquisition, the terms of which have not been publicly disclosed, will provide it with ultrasound provisions for the detection of thyroid cancer. See-Mode's AI software uses single or multinodular thyroid ultrasound images to detect nodules and produce standardised reports. The software automatically classifies nodules in accordance with the American College of Radiology's (ACR) Thyroid Imaging Reporting and Data System (TI-RADS). Research indicates that thyroid cancer is one of the fastest developing cancer diagnoses globally. Alongside breast cancer, women are most often affected by the disease. See-Mode's AI-powered thyroid ultrasound analysis system, which gained US Food and Drug Administration (FDA) clearance in September 2024, has demonstrated a 30% reduction in scan time as a result of increased workflow efficiency, said Dr Howard Berger, president and CEO of RadNet. 'Due to the inherent complexity of radiology and user and radiologist-dependent expertise, the opportunity to improve care through AI is significant. 'With demand exceeding available appointment slots for many of our over 900 ultrasound units, the increase in capacity created by See-Mode's technology should improve our ability to drive better access and more revenue through RadNet's existing centres.' Various research indicates that there is a growing shortfall in radiologists that is set to worsen in the coming decades, making AI a compelling prospect in mitigating the shortfall by helping drive efficiencies through automation. A report by the Association of American Medical Colleges (AAMC) forecasts that the radiologist shortfall in the US could reach almost 42,000 by 2036. In the UK, a 2023 report by the Royal College of Radiologists (RCR) found that the country currently has a 30% shortfall in radiologists that is forecast to rise to 40% by 2028 unless meaningful action is taken. RadNet intends to expand the efficiencies the See-Mode acquisition will help drive across other imaging modalities including breast cancer screening in its more than two million annual ultrasound studies, Dr Berger added. According to GlobalData analysis, the global ultrasound market is forecast to reach a valuation of almost $12bn by 2024. To consolidate its market dominance in the space, GE HealthCare is also continuing to implement AI into its ultrasound provision in order to drive efficiencies. "RadNet acquires See-Mode to bolster AI ultrasound screening for thyroid cancer" was originally created and published by Medical Device Network, a GlobalData owned brand. The information on this site has been included in good faith for general informational purposes only. It is not intended to amount to advice on which you should rely, and we give no representation, warranty or guarantee, whether express or implied as to its accuracy or completeness. You must obtain professional or specialist advice before taking, or refraining from, any action on the basis of the content on our site. Sign in to access your portfolio
Techday NZ
3 days ago
- Health
- Techday NZ
DeepHealth boosts ultrasound AI by integrating See-Mode team
DeepHealth will incorporate See-Mode Technologies' expertise and AI technologies for thyroid and breast ultrasound into its population health solutions following RadNet's acquisition of See-Mode Technologies. See-Mode's commercially available AI-powered ultrasound detection, characterisation, and reporting solutions for thyroid and breast will be added to DeepHealth's suite of services. These technologies automatically detect and characterise thyroid nodules and breast lesions during ultrasound imaging, aiming to improve diagnostic accuracy and streamline clinical workflows through the generation of standardised reports. The integration is set against the backdrop of rising global rates of thyroid cancer, which is among the fastest-growing cancer diagnoses worldwide. Alongside breast cancer, it remains a prevalent pathology, particularly impacting women. Real-world deployment of See-Mode's FDA-cleared thyroid ultrasound AI at selected RadNet imaging centres has already shown operational benefits, with workflow efficiency improvements and enhancements to diagnostic accuracy. The company reported that the inclusion of See-Mode's automated detection and reporting has resulted in up to a 30 per cent reduction in scan time in the centres where it has been piloted. Dr. Howard Berger, President and Chief Executive Officer of RadNet, commented, "Thyroid cancer is one of the fastest growing cancer diagnoses worldwide and, alongside breast cancer, is among the most common cancers affecting women. In the US alone, approximately 20 million ultrasound exams are performed annually for thyroid and breast combined. With ultrasound imaging inherently complex and user and radiologist-dependent, the opportunity to improve care through AI is significant." Dr. Berger further noted, "Early deployment of See-Mode's FDA-approved thyroid ultrasound AI across a portion of our imaging centers has demonstrated up to a 30% reduction in scan time as a result of increased workflow efficiency from See-Mode's automated detection and reporting. With demand exceeding available appointment slots for many of our over 900 ultrasound units, the increase in capacity created by See-Mode's technology should improve our ability to drive better access and more revenue through RadNet's existing centers. Furthermore, there is already a reimbursement code that makes a portion of our approximately 250,000 annual thyroid ultrasounds eligible for additional reimbursement. We aim to expand these efficiencies to breast screening and other clinical areas in our more than two million annual ultrasound studies. These opportunities will also be sold and marketed by DeepHealth to third parties as we further commercialize the offerings." See-Mode's AI technologies are currently cleared for commercial distribution in the United States, Canada, Australia, New Zealand, and Singapore. The acquisition supports DeepHealth's stated objective to strengthen its portfolio of AI-driven population health solutions and to address clinical and operational challenges in high-volume care settings. Dr. Milad Mohammadzadeh, Co-Founder of See-Mode, added: "Ultrasound is complex, time-consuming, and high-volume—exactly where AI can make a difference. By joining RadNet and DeepHealth's combined access to real-world clinical data and expertise at an unprecedented scale, we have an extraordinary platform to build the future of ultrasound." Echoing these remarks, Kees Wesdorp, President and Chief Executive Officer of RadNet's Digital Health division, said: "We are excited to integrate See-Mode's technology in thyroid and breast ultrasound into DeepHealth's comprehensive portfolio of AI-powered solutions for breast, lung, prostate, and brain, to address clinical and operational challenges in high-volume care settings. The technology and the team's expertise will be the basis for future AI-powered ultrasound solutions that will add to the growth engine of DeepHealth." According to the information provided, DeepHealth currently operates more than 900 ultrasound units, conducting over two million ultrasound examinations each year. The company expects that the integration of See-Mode's technology will allow it to manage greater demand, improve workflow efficiencies, and address current appointment slot limitations. Industry sources cited in the release note that in the United States alone, approximately 20 million ultrasound exams are performed each year for thyroid and breast combined. RadNet and DeepHealth aim to capitalise on these volumes by promoting their expanded suite of AI-driven solutions to both internal and third-party customers. See-Mode's team and technology base in Singapore and Australia will join the DeepHealth operations, contributing their expertise to ongoing and future development of AI-driven ultrasound solutions. This collaboration is expected to facilitate the development of new applications in high-volume diagnostic imaging and to support improved access and outcomes across RadNet's network of imaging centres.
