Author:
Jørgen Kongsro
Affiliation:
Animalia – Norwegian Meat Research Centre, Norway
Keyword(s):
Lamb carcass, Tissue, PARAFAC, Multi-Way Analysis, Computer Tomography, Classification, Image, Stacks.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Applications and Services
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Biometrics
;
Biometrics and Pattern Recognition
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Methodologies and Methods
;
Multimedia
;
Multimedia Signal Processing
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
;
Telecommunications
Abstract:
Computer Tomography is shown to be an efficient and cost-effective tool for classification and segmentation of soft tissues in animal carcasses. By using 15 fixed anatomical sites based on vertebra columns, 120 lamb carcasses were CT scanned in Norway during autumn of 2005. Frequency distributions of CT values (HU [-200,200]) of soft tissues from each image were obtained. This yielded a 3-way data set (120 samples * 400 CT values * 15 anatomical sites). The classification of the soft tissues was done by multi way Parallel Factor Analysis (PARAFAC), which resulted in 3 components or soft tissues classified from the images; fat, marbled and lean muscle tissue.