Title
Optimizing feature selection across a multimodality database in computerized classification of breast lesions
Abstract
Linear step-wise feature selection is performed for computerized analysis methods on a set of mammography features using a database of mammography cases, a set of ultrasound features using a database of ultrasound cases, and a set of mammography and sonography features using a multi-modality database of lesions with both mammograms and sonograms. The large mammography and sonography databases were randomly split 20 times into three subdatabases for feature selection, classifier training and independent validation. The average validation. A(z) value over the 20 random splits for the mammography database was 0.82 +/- 0.04 and for the sonography database was 0.85 +/- 0.03. The average consistency feature selection. value for the mammography and sonography databases were 0.87 +/- 0.02 and 0.88 +/- 0.02, respectively. For the mulit-modality database, the consistency feature selection. A(z) value was 0.93.
Year
DOI
Venue
2002
10.1117/12.467053
Proceedings of SPIE
Keywords
Field
DocType
feature selection,computer-aided diagnosis,mammography,ultrasound
Mammography,Ultrasonography,Multimodality,Feature selection,Computer-aided diagnosis,Radiology,Classifier (linguistics),Medicine,Database,Ultrasound
Conference
Volume
ISSN
Citations 
4684
0277-786X
1
PageRank 
References 
Authors
0.40
0
8
Name
Order
Citations
PageRank
Karla Horsch1173.53
a ceballos210.40
Maryellen L. Giger339385.89
ioana r bonta4162.85
Z Huo5388.69
C J Vyborny6438.64
edward hendrick721.22
Li Lan86918.36