Accurate reconstruction of deformable structures in image sequences is a fundamental task in many applications ranging from forecasting by remote sensing to sophisticated medical imaging applications. In this paper we report a novel automatic two-stage method for deformable structure reconstruction from $3$D image sequences. The first stage of the proposed method is focused on the automatic identification and localization of the deformable structures of interest, by means of fuzzy clustering and temporal regions tracking. The final segmentation is accomplished by a second processing stage, devoted to identify finer details using a Multilevel Artificial Neural Network. Application to the segmentation of heart left ventricle from MRI sequences are discussed.
Deformable structures localization and reconstruction in 3D images
Moroni D;Colantonio S;Salvetti O;
2007
Abstract
Accurate reconstruction of deformable structures in image sequences is a fundamental task in many applications ranging from forecasting by remote sensing to sophisticated medical imaging applications. In this paper we report a novel automatic two-stage method for deformable structure reconstruction from $3$D image sequences. The first stage of the proposed method is focused on the automatic identification and localization of the deformable structures of interest, by means of fuzzy clustering and temporal regions tracking. The final segmentation is accomplished by a second processing stage, devoted to identify finer details using a Multilevel Artificial Neural Network. Application to the segmentation of heart left ventricle from MRI sequences are discussed.| File | Dimensione | Formato | |
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