Title :
Self-organizing maps for analyzing mammographic findings
Author :
Lo, Joseph Y. ; Floyd, Carey E., Jr.
Author_Institution :
Dept. of Radiol., Duke Univ. Med. Center, Durham, NC, USA
Abstract :
The purpose of this study is to analyze mammographic findings using self-organizing map artificial neural networks. Using two findings of patient age and mass margin extracted by radiologists, self-organizing maps were developed to analyze both the distribution and topology of the input findings. These results can help to explain the underlying nature of mammographic findings data, which may in turn help radiologists to improve breast cancer diagnosis and assist in the development of other neural networks
Keywords :
diagnostic radiography; medical diagnostic computing; patient diagnosis; pattern classification; self-organising feature maps; topology; breast cancer diagnosis; mammographic finding data analysis; mass margin; neural networks; patient age; radiology; self-organizing map; topology; Biomedical imaging; Breast cancer; Data mining; Lesions; Medical diagnostic imaging; Network topology; Neural networks; Neurons; Radiology; Self organizing feature maps;
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
DOI :
10.1109/ICNN.1997.614546
