TY  - CONF
ID  - GFS2014
T1  - 2D-Based 3D Volume Retrieval Using Singular Value Decomposition of Detected Regions
A1  - García Seco de Herrera, Alba
A1  - Foncubierta-Rodríguez, Antonio
A1  - Schiavi, Emanuele
A1  - Müller, Henning
TI  - Medical Computer Vision. Large Data in Medical Imaging
T3  - Lecture Notes in Computer Science
Y1  - 2014
SP  - 185
EP  - 195
PB  - Springer International Publishing
T2  - MICCAI
CY  - Nagoya, Japan
KW  - 2D-based 3D retrieval
KW  - image retrieval
KW  - region detector
KW  - singular value decompasition
N2  - 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.
M1  - MICCAI post-conference workshop: 26 Sept 2013
ER  -