DocumentCode
3240947
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
Volume
4
fYear
1997
fDate
9-12 Jun 1997
Firstpage
2472
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks,1997., International Conference on
Conference_Location
Houston, TX
Print_ISBN
0-7803-4122-8
Type
conf
DOI
10.1109/ICNN.1997.614546
Filename
614546
Link To Document