A software for automatic detecting and segmenting tumors and Organs at Risk (OAR) in medical images.
- Automatically detect and segment tumors and OARs.
- Can detect multiple organs and generate their contour maps.
The National Cancer Institute estimates that in 2019 there were 53,000 new head and neck (HN) cancer cases, making up 3% of all new cancer cases. The proposed invention will contribute to the head and neck MRI market, valued at $565.2 million in 2019 and is expected to reach $755.4 million by 2025 at a CAGR of 4.8% 2019-2025. HN MRI accounts for 10% of the MRI application market (BCC Research HLC078E). This invention will also contribute to the automated imaging and image analysis market, which was expected to reach $26.5 billion by 2020 with a CAGR of 5.1% from 2014-to 2020 (BCC Research HLC066C).
Researchers have developed a method for automatically detecting and segmentation of tumors and OARs (organs at risk) of cancer patients found in medical images (CT/CBCT, MRI, PET/CT, and PET/MRI). The method consists of a training stage and a segmentation stage. For each pair of medical images and corresponding manual multi-organ contours, the contours are to be used as the learning-based target of the medical image. This novelty approach was able to produce contour images from medical images that matched those produced with the existing current manual method.
TTO Home Page: https://emoryott.technologypublisher.com
Name: Sat Balachander
Title: Licensing Associate
Phone: (404) 727-4968