COMPUTER METHOD FOR 3-D IMAGES CLASSIFICATION
Computer vision | Healthcare | Optimization | Monitoring | Digital Image ProcessingINTRODUCTION
Extracting salient and robust features from images may often be affected by scaling, normalization, and orientation problems; generality and performance are often compromised. Our analysis method for automatic characterization and classification on any n-D images is able to capture global properties by computing features from image isosurfaces offering suitable alternative to standard methods.![](/TechTransfer/images/Brevetti_panoramica/Chincarini_scheda_en.png)
TECHNICAL FEATURES
Extracting salient and robust features from images may often be affected by scaling, normalization, and orientation problems; generality and performance are often compromised. These problems are particularly relevant for low resolution and low contrast digital 3-D images. Although this analysis has been developed and optimized for PET images of the brain, it is a general geometrical method for automatic characterization, ranking and classification, similar to human visual analysis. It can be applied to any set of homogeneous data that represents a population of objects described by n-D scalar matrices. ELBA, its lightweight and fast algorithm, is able to capture global relevant properties of each image by computing features from image isosurfaces offering suitable alternative to comparing intensity-based methods. Features provided are sufficiently general to be applied to any kind of image summarizing its content.POSSIBLE APPLICATIONS
- Clinical brain amyloid PET evaluation targeted to drug trial monitoring;
- Supernovae detection in astronomical images ;
- Background filtering and object recognition;
- Characterization of images time series;
- Data mining;
- Night vision enhancement;
- Flaws classification and monitoring;
ADVANTAGES
- Provides features, stable and easy to obtain, computable on any n-D matrix ;
- Perceptual approach closer to visual assessment ;
- Provides complementary info combinable with existing methods ;
- Avoid intensity normalization;
- Extremely generalizable and flexible ;
- Not strictly requires image registration
PATENT INFORMATION
PATENT OWNER
Istituto Nazionale di Fisica NuclearePATENT STATUS
GrantedPRIORITY NUMBER
MI2014A001418PRIORITY DATE
01/08/2014LICENSE
ItalyCOMMERCIAL RIGHTS
ExclusiveAVAILABILITY
AvailableFIND OUT MORE
Contact usDownload the patent card