DocumentCode :
2580788
Title :
Medical image modality classification and retrieval
Author :
Csurka, Gabriela ; Clinchant, Stephane ; Jacquet, Guillaume
Author_Institution :
Xerox Res. Centre Eur., Meylan, France
fYear :
2011
fDate :
13-15 June 2011
Firstpage :
193
Lastpage :
198
Abstract :
The aim of this paper is to explore different medical image modality and retrieval strategies. First, we analyze how current state-of-the art image representations (bags of visual words and Fisher Vectors) perform when we use them for medical modality classification. Then we integrated these representations in a content based image retrieval system and tested on a medical image retrieval task. Finally, in both cases, we explored how the performance can be improved if we combine visual with textual information. To show the performance of different systems we compared our approaches to the systems participated at the Medical Task of the latest ImageClef Challenge [16].
Keywords :
content-based retrieval; image classification; image representation; image retrieval; medical image processing; Fisher vector; bags-of-visual word; content based image retrieval system; image representation; medical image modality classification; medical image retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Content-Based Multimedia Indexing (CBMI), 2011 9th International Workshop on
Conference_Location :
Madrid
ISSN :
1949-3983
Print_ISBN :
978-1-61284-432-9
Electronic_ISBN :
1949-3983
Type :
conf
DOI :
10.1109/CBMI.2011.5972544
Filename :
5972544
Link To Document :
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