3-D ultrasound texture classification using run difference matrix
Journal
Ultrasound in Medicine & Biology
Journal Volume
31
Journal Issue
6
Pages
763--770
Date Issued
2005-06
Author(s)
Wei-Ming Chen
Ruey-Feng Chang
Shou-Jen Kuo
Cheng-Shyong Chang
Woo Kyung Moon
Shou-Tung Chen
Dar-Ren Chen
Abstract
Ultrasonography is one of the most useful diagnostic tools for human soft tissue and it is in routine use in nearly all hospitals and many physicians' offices and clinics. However, the diagnosis mostly depends upon the personal experiences of the physicians. Moreover, the surface features and internal architecture of a tumor are not easy to be demonstrated simultaneously using the conventional two-dimensional (2-D) ultrasound. Recently, three-dimensional (3-D) ultrasound has been developed and allows the physician to view the 3-D anatomy. 3-D breast US can provide transverse, longitudinal planes as well as in addition simultaneously the coronal plane. This additional information has been proved to be helpful for clinical applications. In this paper, a new approach of texture classification of 3-D ultrasound breast diagnosis using run difference matrix with neural networks is developed. The test 3-D US image database includes 54 malignant and 161 benign tumors. In the experiments, the area index Az under the ROC curve of the proposal 3-D RDM method can achieve 0.9680. The accuracy, sensitivity, specificity, positive predictive value and negative predictive value of the proposed 3-D RDM method is 91.9%(148/161), 88.9%(48/54), 93.5%(100/107), 87.3%(48/55), and 94.3%(100/105), respectively. © 2005 World Federation for Ultrasound in Medicine & Biology.
SDGs
Type
journal article