DocumentCode :
1553449
Title :
Information fusion, application to data and model fusion for ultrasound image segmentation
Author :
Solaiman, B. ; Debon, R. ; Pipelier, F. ; Cauvin, J.M. ; Roux, C.
Author_Institution :
ENST de Bretagne, Brest, France
Volume :
46
Issue :
10
fYear :
1999
Firstpage :
1171
Lastpage :
1175
Abstract :
Nowadays, information fusion constitutes a challenging research topic. The authors´ study proposes to achieve the fusion of several knowledge sources. This, in order to detect the esophagus inner wall from ultrasound medical images. After a brief description of information fusion concepts, the authors propose a system architecture including both model and data fusion. The data fusion is accomplished using fuzzy modeling, which can be seen as a monosensor/multiple sources data fusion system. The model fusion is performed using a full-adapted snake theory, which projects the fuzzy decision into the binary decision space.
Keywords :
biological organs; biomedical ultrasonics; edge detection; fuzzy set theory; image segmentation; medical image processing; modelling; sensor fusion; binary decision space; esophagus inner wall detection; full-adapted snake theory; fuzzy decision; knowledge sources; medical diagnostic imaging; system architecture; ultrasound medical images; Biomedical imaging; Decision making; Esophagus; Fuzzy logic; Fuzzy systems; Humans; Image segmentation; Sensor fusion; Sensor systems; Ultrasonic imaging; Computer Simulation; Endoscopes; Endosonography; Equipment Design; Esophageal Neoplasms; Esophagus; Fuzzy Logic; Humans; Image Enhancement; Transducers;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.790491
Filename :
790491
Link To Document :
بازگشت