Active Shape and Appearance Models

Statistical models of shape and appearance are powerful tools for medical image analysis. The shape models can capture the mean and variation in shape of a structure or set of structures across a population. They can be used to help interpret new images by finding the parameters which best match an instance of the model to the image. Two widely used methods for matching are the Active Shape Model and the Active Appearance Model. We describe the models and the matching algorithms, and give examples of their use.

[1]  Rasmus Larsen,et al.  Multi-band modelling of appearance , 2003, Image Vis. Comput..

[2]  Timothy F. Cootes,et al.  Additive Update Predictors in Active Appearance Models , 2010, BMVC.

[3]  Milan Sonka,et al.  3-D active appearance models: segmentation of cardiac MR and ultrasound images , 2002, IEEE Transactions on Medical Imaging.

[4]  Timothy F. Cootes,et al.  On representing edge structure for model matching , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[5]  Timothy F. Cootes,et al.  Combining point distribution models with shape models based on finite element analysis , 1994, Image Vis. Comput..

[6]  Aziz Umit Batur,et al.  Adaptive active appearance models , 2005, IEEE Transactions on Image Processing.

[7]  Timothy F. Cootes,et al.  Combining Elastic and Statistical Models of Appearance Variation , 2000, ECCV.

[8]  Xiaoming Liu,et al.  Generic Face Alignment using Boosted Appearance Model , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Roland Göcke,et al.  A Nonlinear Discriminative Approach to AAM Fitting , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[10]  Stephan Tschechne,et al.  Learning Robust Objective Functions for Model Fitting in Image Understanding Applications , 2006, BMVC.

[11]  Timothy F. Cootes,et al.  A Comparative Evaluation of Active Appearance Model Algorithms , 1998, BMVC.

[12]  Timothy F. Cootes,et al.  Active Appearance Models , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  C. Taylor,et al.  Accurate Regression Procedures for Active Appearance Models , 2011, BMVC 2011.

[14]  C. Goodall.  Procrustes methods in the statistical analysis of shape , 1991 .

[15]  Martin Roberts,et al.  Vertebral Morphometry: Semiautomatic Determination of Detailed Shape From Dual-Energy X-ray Absorptiometry Images Using Active Appearance Models , 2006, Investigative radiology.

[16]  Timothy F. Cootes,et al.  Active Shape Models and the shape approximation problem , 1996, Image Vis. Comput..

[17]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[18]  Bjarne K. Ersbøll,et al.  FAME-a flexible appearance modeling environment , 2003, IEEE Transactions on Medical Imaging.

[19]  Ralph Gross,et al.  Constructing and Fitting Active Appearance Models With Occlusion , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[20]  Timothy F. Cootes,et al.  Advances in active appearance models , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[21]  Alejandro F. Frangi,et al.  Active shape model segmentation with optimal features , 2002, IEEE Transactions on Medical Imaging.

[22]  Yi Zhou,et al.  Bayesian tangent shape model: estimating shape and pose parameters via Bayesian inference , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[23]  Josien P. W. Pluim,et al.  Non-rigid registration based active appearance models for 3D medical image segmentation , 2004 .

[24]  Timothy F. Cootes,et al.  Robust Active Appearance Models with Iteratively Rescaled Kernels , 2007, BMVC.

[25]  Dinggang Shen,et al.  Hierarchical active shape models, using the wavelet transform , 2003, IEEE Transactions on Medical Imaging.

[26]  Timothy F. Cootes,et al.  Fully Automatic Segmentation of the Proximal Femur Using Random Forest Regression Voting , 2013, IEEE Transactions on Medical Imaging.

[27]  Timothy F. Cootes,et al.  Improving Appearance Model Matching Using Local Image Structure , 2003, IPMI.

[28]  Jim Graham,et al.  Robust Active Shape Model Search , 2002, ECCV.

[29]  Simon Baker,et al.  Active Appearance Models Revisited , 2004, International Journal of Computer Vision.

[30]  Timothy F. Cootes,et al.  Linking Sequences of Active Appearance Sub-Models via Constraints: An Application in Automated Vertebral Morphometry , 2003, BMVC.

[31]  Timothy F. Cootes,et al.  Computing Accurate Correspondences across Groups of Images , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[32]  William H. Press,et al.  Numerical Recipes in C, 2nd Edition , 1992 .

[33]  Alejandro F. Frangi,et al.  Automatic construction of multiple-object three-dimensional statistical shape models: application to cardiac modeling , 2002, IEEE Transactions on Medical Imaging.

[34]  Timothy F. Cootes,et al.  An Algorithm for Tuning an Active Appearance Model to New Data , 2006, BMVC.

[35]  Timothy F. Cootes,et al.  3D Statistical Shape Models Using Direct Optimisation of Description Length , 2002, ECCV.