TY - GEN
T1 - Rough and Fuzzy-rough methods for mammographic data analysis
AU - Shen, Qiang
AU - MacParthaláin, Neil Seosamh
AU - Jensen, Richard
N1 - N. Mac Parthalain, R. Jensen and Q. Shen. Rough and fuzzy-rough methods for mammographic data analysis. Proceedings of the 8th Annual UK Workshop on Computational Intelligence (UKCI'08), 2008.
PY - 2008/9/10
Y1 - 2008/9/10
N2 - The accuracy of methods for the detection of
mammographic abnormaility is heavily related
to breast tissue characteristics. A breast with
high tissue density will have reduced sensitivity
in terms of detection. Also, breast tissue
density is an important indicator of the risk of
development of breast cancer. This paper investigates
the application of a number of rough
set and fuzzy-rough set techniques to mammographic
image data. The aim is to attempt to
automate the breast tissue classification procedure
based on the consensus data of experts.
The results of applying the various previously
mentioned techniques show that they perform
well, achieving high levels of classification accuracy.
AB - The accuracy of methods for the detection of
mammographic abnormaility is heavily related
to breast tissue characteristics. A breast with
high tissue density will have reduced sensitivity
in terms of detection. Also, breast tissue
density is an important indicator of the risk of
development of breast cancer. This paper investigates
the application of a number of rough
set and fuzzy-rough set techniques to mammographic
image data. The aim is to attempt to
automate the breast tissue classification procedure
based on the consensus data of experts.
The results of applying the various previously
mentioned techniques show that they perform
well, achieving high levels of classification accuracy.
M3 - Conference Proceeding (Non-Journal item)
BT - Proceedings of the 8th Annual UK Workshop on Computational Intelligence
ER -
