Graph-based registration for biomedical images

Abstract : The context of this thesis is the image registration for endomicroscopic images. Multiphoton microendoscope provides different scanning trajectories which are considered in this work. First we propose a nonrigid registration method whose motion estimation is cast into a feature matching problem under the Log-Demons framework using Graph Wavelets. We investigate the Spectral Graph Wavelets (SGWs) to capture the shape feature of the images. The data representation on graphs is more adapted to data with complex structures. Our experiments on endomicroscopic images show that this method outperforms the existing nonrigid image registration techniques. We then propose a novel image registration strategy for endomicroscopic images acquired on irregular grids. The Graph Wavelet transform is flexible to apply on different types of data regardless of the data point densities and how complex the data structure is. We also show how the Log-Demons framework can be adapted to the optimization of the objective function defined for images with an irregular sampling.
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Submitted on : Thursday, June 6, 2019 - 4:27:53 PM
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  • HAL Id : tel-02149797, version 1



Hong Nhung Pham. Graph-based registration for biomedical images. Signal and Image Processing. Université de Poitiers, 2019. English. ⟨NNT : 2019POIT2258⟩. ⟨tel-02149797⟩



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