title: Optimal feature point selection and automatic initialization in active shape model search.
abstract: This paper presents a novel approach for robust and fully automatic segmentation with active shape model search. The proposed method incorporates global geometric constraints during feature point search by using interlandmark conditional probabilities. The A* graph search algorithm is adapted to identify in the image the optimal set of valid feature points. The technique is extended to enable reliable and fast automatic initialization of the ASM search. Validation with 2-D and 3-D MR segmentation of the left ventricular epicardial border demonstrates significant improvement in robustness and overall accuracy, while eliminating the need for manual initialization.
authors.affiliation: Visual Information Processing, Department of Computing Imperial College London, United Kingdom. lekadir@doc.ic.ac.uk
authors.forename: Karim
authors.initials: K
authors.lastname: Lekadir
authors.forename: Guang-Zhong
authors.initials: GZ
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D006352:Heart Ventricles / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity