2D-Based 3D Volume Retrieval Using Singular Value Decomposition of Detected Regions
| Publicatietype: | In proceedings |
| Citatie: | GFS2014 |
| Boektitel: | Medical Computer Vision. Large Data in Medical Imaging |
| Serie: | Lecture Notes in Computer Science |
| Jaar: | 2014 |
| Pagina's: | 185-195 |
| Uitgever: | Springer International Publishing |
| Locatie: | Nagoya, Japan |
| Organisatie: | MICCAI |
| Samenvatting: | In this paper, a novel 3D retrieval model to retrieve medical volumes using 2D images as input is proposed. The main idea consists of applying a multi{scale detection of saliency of image regions. Then, the 3D volumes with the regions for each of the scales are associated with a set of projections onto the three canonical planes.The 3D shape is indirectly represented by a 2D{shape descriptor so that the 3D{shape matching is transformed into measuring similarity between 2D{shapes. The shape descriptor is de ned by the set of the k largest singular values of the 2D images and Euclidean distance between the vector descriptors is used as a similarity measure. The preliminary results obtained on a simple database show promising performance with a mean average precision (MAP) of 0.82 and could allow using the approach as part of a retrieval system in clinical routine. |
| Gebruikersvelden: | MICCAI post-conference workshop: 26 Sept 2013 |
| Trefwoorden: | 2D-based 3D retrieval, image retrieval, region detector, singular value decompasition |
| Auteurs | |
| Toegevoegd door: | [] |
| Totaalscore: | 0 |
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