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Deformable Medical Image Registration using advanced Ai Techniques

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dc.contributor.author HACHICHI, Aimene Nedjemeddine
dc.date.accessioned 2023-12-10T10:17:01Z
dc.date.available 2023-12-10T10:17:01Z
dc.date.issued 2023-06-08
dc.identifier.uri http//localhost:8080/jspui/handle/123456789/10957
dc.description.abstract Image medical registration is one of the most active areas in image processing, and has attracted particular interest in many areas such as medical image analysis, remote sensing, and mapping. The main idea of these techniques is to identify the spatial shift between two images which makes it possible to match the equivalent properties. Registration can be local or international. Several deep-learning-based registration techniques have been developed that have shown impressive performance in terms of matching, which can be grouped into two main classes: Flexible and Diffeomorphic feature registration based on extraction between two images. In the graduation project, we established an accurate learning model based on convolutional neural networks that were trained to record images. Where the model proved acceptable accuracy and speed en_US
dc.language.iso en en_US
dc.publisher Université Echahid Chikh Larbi Tébessi -Tébessa en_US
dc.subject Digital Watermarking, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) en_US
dc.title Deformable Medical Image Registration using advanced Ai Techniques en_US
dc.type Thesis en_US


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