title: Virtual dissection of pig carcasses.
abstract: This paper proposes the use of computed tomography (CT) as a reference method for estimating the lean meat percentage (LMP) of pig carcasses. The current reference is manual dissection which has a limited accuracy due to variability between butchers. A contextual Bayesian classification scheme is applied to classify volume elements of full body CT-scans of pig carcasses into three tissue types. A linear model describes the relation between voxels and the full weight of the half carcass, which can be determined more accurately than that of the lean meat content. Two hundred and ninety-nine half pig carcasses were weighed and CT-scanned. The explained variance of the model was R(2)=0.9994 with a root-mean-squared error of prediction of 83.6g. Applying this method as a reference will ensure a more robust calibration of sensors for measuring the LMP, which is less prone to variation induced by manual intervention.
authors.affiliation: DTU Informatics, Technical University of Denmark, Richard Petersens Plads, Bld. 321, DK-2800 Kgs. Lyngby, Denmark.
authors.forename: Martin
authors.initials: M
authors.lastname: Vester-Christensen
authors.forename: Søren G H
authors.initials: SG
authors.lastname: Erbou
authors.forename: Mads F
authors.initials: MF
authors.lastname: Hansen
authors.forename: Eli V
authors.initials: EV
authors.lastname: Olsen
authors.forename: Lars B
authors.initials: LB
authors.lastname: Christensen
authors.forename: Marchen
authors.initials: M
authors.lastname: Hviid
authors.forename: Bjarne K
authors.initials: BK
authors.lastname: Ersbøll
authors.forename: Rasmus
authors.initials: R
authors.lastname: Larsen