Information fusion, application to data and model fusion for ultrasound image segmentation

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...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 1999-10, Vol.46 (10), p.1171-1175
Main Authors: Solaiman, B., Debon, R., Pipelier, F., Cauvin, J.-M., Roux, C.
Format: Article
Language:English
Subjects:
Algorithms
Biomedical imaging
Computer Simulation
Decision making
Endoscopes
Endosonography - instrumentation
Endosonography - methods
Engineering Sciences
Equipment Design
Esophageal Neoplasms - diagnostic imaging
Esophagus
Esophagus - diagnostic imaging
Fuzzy Logic
Fuzzy sets
Fuzzy systems
Humans
Image Enhancement - methods
Image segmentation
Mathematical models
Medical imaging
Sensor data fusion
Sensor fusion
Sensor systems
Signal and Image processing
Tissue
Transducers
Ultrasonic imaging
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Summary: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.
ISSN:0018-9294
1558-2531
DOI:10.1109/10.790491