DocumentCode
3591354
Title
Feasibility of multi-layered perceptron network in discriminating breast magnetic resonance imaging lesions
Author
Muthyala, Sreenivas ; Gibbs, Peter ; Turnbull, Lindsay
Author_Institution
Centre for MR Investigations, Hull Univ., UK
Volume
4
fYear
2005
Firstpage
2493
Abstract
The feasibility of IMLP networks in reliably discriminating between benign and malignant lesions is demonstrated in this pilot study. MLP networks can be trained on similar information that a radiologist would use to interpret lesions on DCE-MRI study of breast and perform as well as a trained radiologist. In the future this work will be extended to a larger data set, and the feasibility of other neural networks such as radial basis function will be tested.
Keywords
diseases; magnetic resonance imaging; medical computing; medical image processing; multilayer perceptrons; breast magnetic resonance imaging lesions; multi-layered perceptron network; neural networks; radial basis function; Breast cancer; Intelligent networks; Lesions; Magnetic resonance imaging; Mammography; Multilayer perceptrons; Neural networks; Tellurium; Testing; X-ray imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Print_ISBN
0-7803-9048-2
Type
conf
DOI
10.1109/IJCNN.2005.1556294
Filename
1556294
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