Multimodal registration across 3D point clouds and CT-volumes
نویسندگان
چکیده
Multimodal registration is a challenging problem in visual computing, commonly faced during medical image-guided interventions, data fusion and 3D object retrieval. The main challenge of multimodal finding accurate correspondence between modalities, since different modalities do not exhibit the same characteristics. This paper explores how coherence can be utilized for task registration. A novel deep learning framework proposed by introducing siamese architecture, especially designed aligning fusing structural physical principles. cross-modal attention blocks lead network to establish correspondences features modalities. focuses on alignment point clouds micro-CT volumes object. dataset consisting real scans their synthetically generated models (point clouds) presented evaluating our methodology.
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ژورنال
عنوان ژورنال: Computers & Graphics
سال: 2022
ISSN: ['0097-8493', '1873-7684']
DOI: https://doi.org/10.1016/j.cag.2022.06.012