Title
Classifying breast masses in volumetric whole breast ultrasound data: a 2.5-dimensional approach
Abstract
The aim of this paper is to investigate a 2.5-dimensional approach in classifying masses as benign or malignant in volumetric anisotropic voxel whole breast ultrasound data In this paper, the term 2.5-dimensional refers to the use of a series of 2-dimensional images While mammography is very effective in breast cancer screening in general, it is less sensitivity in detecting breast cancer in younger women or women with dense breasts Breast ultrasonography does not have the same limitation and is a valuable adjunct in breast cancer detection We have previously reported on the clinical value of volumetric data collected from a prototype whole breast ultrasound scanner The current study focuses on a new 2.5-dimensional approach in analyzing the volumetric whole breast ultrasound data for mass classification Sixty-three mass lesions were studied Of them 33 were malignant and 30 benign Features based on compactness, orientation, shape, depth-to-width ratio, homogeneity and posterior echo were measured Linear discriminant analysis and receiver operating characteristic (ROC) analysis were employed for classification and performance evaluation The area under the ROC curve (AUC) was 0.91 using all breast masses for training and testing and 0.87 using the leave-one-mass-out cross-validation method Clinically significance of the results will be evaluated using a larger dataset from multi-clinics.
Year
DOI
Venue
2010
10.1007/978-3-642-13666-5_86
Digital Mammography / IWDM
Keywords
Field
DocType
dense breast,breast cancer,anisotropic voxel whole breast,volumetric data,ultrasound data,breast masse,prototype whole breast ultrasound,classifying breast masse,breast cancer screening,volumetric whole breast ultrasound,breast cancer detection,roc analysis,data collection,2 dimensional,cross validation,roc curve,receiver operator characteristic,ultrasonography,ultrasound
Voxel,Mammography,Receiver operating characteristic,Breast cancer,Breast cancer screening,Linear discriminant analysis,Whole breast,Radiology,Medicine,Ultrasound
Conference
Volume
ISSN
ISBN
6136
0302-9743
3-642-13665-6
Citations 
PageRank 
References 
1
0.36
2
Authors
9
Name
Order
Citations
PageRank
Gobert N. Lee1367.29
Toshiaki Okada210.36
Daisuke Fukuoka3417.37
Chisako Muramatsu431735.56
Takeshi Hara563979.10
Takako Morita6177.08
Etsuo Takada7164.31
Tokiko Endo8568.59
Hiroshi Fujita911824.65