Carina Medical is a startup that spun out of multiple labs at the University of Virginia and the University of Kentucky. Our team is dedicated to transfer academic research into clinical products using the cutting edge AI technology to improve cancer treatment.
Lexington, KY -- Carina Medical has received a $2M award from the National Cancer Institute to continue the development of AI based auto-segmentation software for radiation therapy treatment planning.
Carina Medical will continue to develop novel solutions for more efficient radiation treatment planning. It will support both CT and MRI based organ segmentation and site-specific segmentation models to increase the robustness of AI system.
Carina Medical works with the University of Kentucky and the University of California, Davis to develop and validate the auto-segmentation product.
Frankfort, KY -- The Cabinet for Economic Development KY Innovation awarded Carina Medical $150K SBIR/STTR Matching Funds.
“SBIR/STTR funds are a vital component in launching and growing innovative, high-tech companies here in Kentucky,” said Gov. Matt Bevin. “The commonwealth’s matching program is one of the strongest in the nation, enabling us to support early-stage companies with cutting-edge technologies. This year’s recipients are a testament to the outstanding work being done in our state across many disciplines. We look forward to watching them flourish right here in America’s engineering and manufacturing center of excellence.”
San Antonio, TX -- The Carina Medical team, composed of Xue Feng, Ph.D. and Quan Chen, Ph.D., won the first place in AAPM Auto-segmentation on MRI for Head-and-Neck Radiation Treatment Planning Challenge (RT-MAC) at 2019 AAPM annual meeting.
In this open competition, teams from around the world are competing to develop algorithms that learns the contouring of structures on Head-and-Neck MRI images. This grand challenge is held for multiple phases. Phase 1 was completed before the 2019 AAPM annual meeting when teams apply their algorithms to segment 12 test images and upload their results for challenge organizers to evaluate. Phase 2 was conducted live at the AAPM annual meeting when teams were provided with 10 new test images to segment. In both phases, Carina Medical team edged out Varian team to win the 1st place.
The analysis performed by the challenge organizers has showed that the contouring accuracy of Carina Medical’s algorithm has surpassed that of human experts’ manual contouring. This is another proof of the superiority of Carina Medical’s AI technology. The more accurate and faster segmentation will not only reduce the health care cost and provide a better treatment plan, but also make advanced treatment technique such as adaptive radiation therapy more practical.
Lexington, KY –- Carina Medical has received a $300,000 Phase I SBIR award from the National Institute of Health to develop AI assisted auto-segmentation software for radiation therapy treatment planning.
More than 60 percent of cancer patients will encounter radiation therapy during their course of treatment. In radiation treatment, both tumor and health organs have to be accurately contoured so that radiation oncology teams can produce plans that deliver enough dose to the tumor while sparing health organs. In current clinical practice, the main method of segmenting OARs is through manual contouring, which can be both time-consuming and inaccurate. A fast and accurate contouring software can not only reduce the health care cost and provide a better treatment plan, but also helps the adoption of adaptive radiation therapy, which was bottlenecked by contouring.
Carina Medical will work with the University of Kentucky to develop and validate the auto-segmentation product.
Granada, Spain –- Carina Medical Co-Founder, Dr. Xue Feng, is the first place winner in the BraTS 2018 Challenge, Survial Task. The goal of the competition was to identify the best machine learning algorithms for brain tumor segmentation and overall survival prediction. Dr. Feng finished first in the survival prediction task, winning a cash prize and an invitation to speak on the topic in BrainLes workshop at MICCAI 2018 conference.
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