Tumor Diagnosis of Shear Wave Breast Elastography
Date Issued
2012
Date
2012
Author(s)
Lin, Yi-Ting
Abstract
The breast cancer is always one of the ten leading death causes for women around the world. The strain of the tumor has been confirmed to be the main feature of distinguishing benign and malignant tumors. In the past years, the physician has used the sonoelastography with manual compression to obtain the tumor strain. Different from the conventional sonoelastography, this study adopts the new shear wave elastography which uses the acoustic radiation to generate the tumor strain. In the conventional sonoelastography, the tumor diagnosis is based on the elasticity information inside the tumor. However, in the new shear wave elastography, the important diagnostic information is outside the tumor rather than inside the tumor. The purposes of this paper are automatically segmenting the tumor contour for the image and extracting the features to diagnose benign and malignant tumors. First, we use the level set segmentation method to automatically cut out the tumor contour. Comparing with the manually circled tumor, our scheme can maintain the consistency of the segmentation results. Then, the tumor contour and image information are applied to extract the B-mode and elastographic features. Finally, in addition to use either B-mode or elastographic features to diagnose benign and malignant tumors, a combination of both feature set is also utilized for diagnosis. In this study, we use 112 biopsy-proved breast tumors composed of 58 benign and 54 malignant cases. The experimental results illustrate that the accuracy in distinguishing tumors using B-mode features is 84.82%, whereas 91.07% using elastography features, and 94.64% combining B-mode and elastographic features. Based on statistical analyses of experimental results, the accuracy of classifying tumors using the combined feature set is significantly improved.
Subjects
elastography
shear wave
breast
tumor
tumor segmentation
SDGs
Type
thesis
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