Robust active shape models: a robust, generic and simple automatic segmentation tool.
This paper presents a new segmentation algorithm which combines active shape model and robust point matching techniques. It can use any simple feature detector to extract a large number of feature points in the image. Robust point matching is then used to search for the correspondences between feature and model points while the model is being deformed along the modes of variation of the active shape model. Although the algorithm is generic, it is particularly suited for medical imaging applications where prior knowledge is available. The value of the proposed method is examined with two different medical imaging modalities (Ultrasound, MRI) and in both 2D and 3D. The experiments have shown that the proposed algorithm is immune to missing feature points and noise. It has demonstrated significant improvements when compared to RPM-TPS and ASM alone.
Abi-Nahed
Julien
J
Imaging and Visualization Department, Siemens Corporate Research Princeton, New Jersey, USA. julien.abi.nahed@siemens.com
Jolly
Marie-Pierre
MP
Yang
Guang-Zhong
GZ
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D004452:Echocardiography / Q000379:methods*; D006352:Heart Ventricles / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; 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*; D008955:Models, Cardiovascular; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity