DocumentCode
2976562
Title
MVN_CNN and FCNN for endocardial edge detection
Author
Ketout, Hussin ; Gu, Jason ; Horne, Gabrielle
Author_Institution
Electr. & Comput. Eng., Dalhousie Univ., Halifax, NS, Canada
fYear
2011
fDate
21-24 Feb. 2011
Firstpage
208
Lastpage
212
Abstract
In this paper, Fuzzy Cellular Neural Networks (FCNN) endocardial edge detection is proposed. The echocardiographic image is preprocessed to enhance the contrast and smoothness by utilizing MVN_CNN filtering. FCNN is applied to the smoothed image to extract the heart boundaries. Fuzzy min and max functions are employed. The comparison was made between Fuzzy, CNN and FCNN edge detectors. The FCNN approach showed better results for extracting the LV endocardial edges. Some experimental results are given for different echocardiographic images.
Keywords
echocardiography; edge detection; fuzzy neural nets; medical image processing; FCNN filtering; Fuzzy Cellular Neural Network; MVN_CNN filtering; echocardiographic image; endocardial edge detection; heart boundary; Cellular neural networks; Equations; Image edge detection; Mathematical model; Maximum likelihood detection; Nonlinear filters; CNN; Echocardiography; Endocardial; FCNN; Fuzzy; MVN_CNN; edge detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering (MECBME), 2011 1st Middle East Conference on
Conference_Location
Sharjah
Print_ISBN
978-1-4244-6998-7
Type
conf
DOI
10.1109/MECBME.2011.5752102
Filename
5752102
Link To Document