A General Technique for the Estimation of Farm Animal Body Part Weights from CT Scans and Its Applications in a Rabbit Breeding Program

Various applications of farm animal imaging are based on estimating the weight of specific body parts and cuts from CT images of animals. In many cases, the complexity of the problem is increased by the enormous variability in body postures in the CT images due to scanning unsedated live animals. In this work, we propose a general and robust approach to estimate the weights of sections and body parts from CT images of (possibly) live animals. We adapt the segmentation by elastic registration and joint feature and model selection for the regression component to cope with the large number of features and small number of samples. The proposed technique is evaluated and illustrated by real applications in rabbit breeding programs. The r2 values are 12% higher than those of previous techniques and methods used in the breeding selection programs. The proposed technique is easily transferable to similar problems and is therefore made available in an open source software package for the benefit of the community.