Predicting the 3D bone structure of pork shoulders using X-ray imaging and statistical shape modeling

Abstract

In the meat industry, deboning and cutting are essential processing steps often performed by humans. To automate these processes it is essential to understand the complexity and variability of their three-dimensional (3D) shape as well as the relationship between their outer shape and inside bone structure. In this paper, we introduce a 3D statistical shape model (SSM) that describes the outer surface of a pork shoulder and its corresponding inner bone structure. X-ray computed tomography (CT) scans were acquired from 45 right-hand side and 45 left-hand side pork shoulders. The CT scans were segmented to obtain 3D models of the external shape and internal bone structure. Surface meshes were then created and used for establishing SSMs of the outer surface, the bone structure and the combined surfaces of the left and right pork shoulders based on principal component analysis. The first five of a total of 40 principal components were able to describe 63.6 % of the variability in the entire dataset. The mean absolute error (MAE) of the proposed fitting method in this paper was 5.15 mm for the test set. Besides being compact, the models could also generate realistic 3D shapes of pork shoulders that were not present in the dataset. These shapes can be used in the development of automated cutting and deboning procedures, and, thus, lead to improved precision in cutting, reduced waste, and further enhancements of automation within the meat industry.