title: Collaborative multi organ segmentation by integrating deformable and graphical models.
abstract: Organ segmentation is a challenging problem on which significant progress has been made. Deformable models (DM) and graphical models (GM) are two important categories of optimization based image segmentation methods. Efforts have been made on integrating two types of models into one framework. However, previous methods are not designed for segmenting multiple organs simultaneously and accurately. In this paper, we propose a hybrid multi organ segmentation approach by integrating DM and GM in a coupled optimization framework. Specifically, we show that region-based deformable models can be integrated with Markov Random Fields (MRF), such that multiple models' evolutions are driven by a maximum a posteriori (MAP) inference. It brings global and local deformation constraints into a unified framework for simultaneous segmentation of multiple objects in an image. We validate this proposed method on two challenging problems of multi organ segmentation, and the results are promising.
authors.affiliation: CBIM, Rutgers University, Piscataway, NJ, USA.
authors.forename: Mustafa Gökhan
authors.initials: MG
authors.lastname: Uzunbaş
authors.affiliation: CBIM, Rutgers University, Piscataway, NJ, USA.
authors.forename: Chao
authors.initials: C
authors.lastname: Chen
authors.affiliation: CBIM, Rutgers University, Piscataway, NJ, USA.
authors.forename: Shaoting
authors.initials: S
authors.lastname: Zhang
authors.affiliation: University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Kilian M
authors.initials: KM
authors.lastname: Poh
authors.affiliation: Dept. of Industrial and Systems Engineering, Rutgers University, Piscataway, NJ, USA.
authors.forename: Kang
authors.initials: K
authors.lastname: Li
authors.affiliation: CBIM, Rutgers University, Piscataway, NJ, USA.
authors.forename: Dimitris
authors.initials: D
authors.lastname: Metaxas
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique