Extending and applying active appearance models for automated, high precision segmentation in different image modalities |
| | Abstract | In this paper, we present a set of extensions to the deformable template model: Active Appearance Model (AAM)
proposed by Cootes et al. AAMs distinguish themselves by
learning a priori knowledge through observation of shape
and texture variation in a training set. This is used to obtain a compact object class description, which can be employed to rapidly search images for new object instances. The proposed extensions concern enhanced shape representation, handling of homogeneous and heterogeneous textures, refinement optimization using Simulated Annealing and robust statistics. Finally, an initialization scheme is designed thus making the usage of AAMs fully automated. Using these extensions it is demonstrated that AAMs can segment bone structures in radiographs, pork chops in perspective images and the left ventricle in cardiovascular magnetic resonance images in a robust, fast and accurate manner. Subpixel landmark accuracy was obtained in two of the three cases. | | Type | Conference paper [With referee] | | Conference | Proc. 12th Scandinavian Conference on Image Analysis - SCIA 2001, Bergen, Norway | | Editors | Ivar Austvoll | | Year | 2001 Month June pp. 90-97 | | Publisher | NOBIM | | Address | Stavanger, Norway | | Electronic version(s) | [pdf] | | BibTeX data | [bibtex] | | IMM Group(s) | Image Analysis & Computer Graphics |
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