Abstract
The University of Central Florida invention is an efficient and accurate system for automatically detecting the presence of any abnormality from information available in one-dimensional or multidimensional signals such as images. One example application is detecting brain tumors from brain scans. Following are some benefits of the technique:
- Detects one or more types of abnormalities that are not identifiable visually or auditorily
- Detects an abnormality’s size, shape and physical location (spatial information)
- Searches for abnormalities or particular characteristics in any biometric signals known today
With the ability to project the data on any appropriate domain, the invention lends itself to computationally efficient implementation. It allows for enhanced accuracy and considerable reduction in the data representing the abnormality. It also reduces storage requirements, simplifies computation, and offers results in real time. The UCF technique can also be used with other transform domains and to search for particular characteristics in biometric signals.
Partnering Opportunity
The research team is seeking partners for licensing, research collaboration, or both.
Stage of Development
Prototype available.
Benefit
Fast, low cost and accurateUseful for detecting the presence of at least one abnormal biometric signalCan be used for automated data analysis in many fieldsMarket Application
Machine learning applications in the biomedical field
Brochure
