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
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;
Conference_Titel :
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Print_ISBN :
0-7803-9048-2
DOI :
10.1109/IJCNN.2005.1556294