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2D-Based 3D Volume Retrieval Using Singular Value Decomposition of Detected Regions

Garcia Seco De Herrera, Alba and Foncubierta-Rodríguez, Antonio and Schiavi, Emanuele and Müller, Henning (2014) 2D-Based 3D Volume Retrieval Using Singular Value Decomposition of Detected Regions. In: Third International MICCAI Workshop, MCV 2013, 2013-09-26 - ?, Nagoya, Japan.

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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 defined 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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Medical Computer Vision. Large Data in Medical Imaging Third International MICCAI Workshop, MCV 2013, Nagoya, Japan, September 26, 2013, Revised Selected Papers. Part of the Lecture Notes in Computer Science book series (LNCS, volume 8331)
Uncontrolled Keywords: 2D-based 3D retrieval, image retrieval, region detector, singular value decompasition
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 22 Jan 2020 14:37
Last Modified: 22 Jan 2020 15:15

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