title: Segmentation of the pectoral muscle in breast MRI using atlas-based approaches.
abstract: Pectoral muscle segmentation is an important step in automatic breast image analysis methods and crucial for multi-modal image registration. In breast MRI, accurate delineation of the pectoral is important for volumetric breast density estimation and for pharmacokinetic analysis of dynamic contrast enhancement. In this paper we propose and study the performance of atlas-based segmentation methods evaluating two fully automatic breast MRI dedicated strategies on a set of 27 manually segmented MR volumes. One uses a probabilistic model and the other is a multi-atlas registration based approach. The multi-atlas approach performed slightly better, with an average Dice coefficient (DSC) of 0.74, while with the much faster probabilistic method a DSC of 0.72 was obtained.
authors.affiliation: University of Girona, Spain. agubern@eia.udg.edu
authors.forename: Albert
authors.initials: A
authors.lastname: Gubern-Mérida
authors.forename: Michiel
authors.initials: M
authors.lastname: Kallenberg
authors.forename: Robert
authors.initials: R
authors.lastname: Martí
authors.forename: Nico
authors.initials: N
authors.lastname: Karssemeijer
mesh_terms: D000465:Algorithms; D059925:Anatomic Landmarks / Q000033:anatomy & histology*; D001185:Artificial Intelligence; D001940:Breast / Q000033:anatomy & histology*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010369:Pectoralis Muscles / Q000033:anatomy & histology*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique