Computer-Aided tumor diagnosis in 3-D breast elastography
Journal
Computer Methods and Programs in Biomedicine
Journal Volume
153
Pages
201-209
Date Issued
2018
Author(s)
Abstract
Background and objective Breast cancer is the major cause of cancer-related mortality in women. However, the death rate can be effectively decreased if the breast cancer can be detected early and treated appropriately. In recent years, many studies have indicated that the elastography has the better diagnosis performance than conventional ultrasound (US). Method In this study, the 3-D tumor contour is obtained by using the proposed segmentation methods and then the features containing texture information, shape information, ellipsoid fitting information are extracted respectively by using the segmented 3-D tumor contour and B-mode images, and the features containing elasticity information are calculated using the same contour and elastographic images. Results In this experiment, totally 40 biopsy-proved lesions containing 20 benign tumors and 20 malignant tumors are used to evaluate the proposed computer-aided diagnosis (CAD) system. From the experimental results, the combination of shape, ellipsoid fitting and elastographic features has the best performance with accuracy 90.50% (36/40), sensitivity 85.00% (17/20), specificity 95.00% (19/20), and the area under the ROC curve Az 0.987. Conclusion The result shows that tumors can be diagnosed more precisely by using the elastography images. ? 2017 Elsevier B.V.
SDGs
Other Subjects
Curve fitting; Diagnosis; Diseases; Image segmentation; Information use; Medical imaging; Tumors; Area under the ROC curve; Breast; Computer Aided Diagnosis(CAD); Diagnosis performance; Elastography; Ellipsoid; Segmentation methods; Shape; Computer aided diagnosis; adult; aged; Article; B scan; benign breast tumor; breast biopsy; breast carcinoma; breast elastography; breast fibroadenoma; breast papilloma; breast tumor; clinical article; computer assisted diagnosis; diagnostic accuracy; echomammography; elastography; entropy; female; fibrocystic breast disease; human; image segmentation; intraductal carcinoma; invasive carcinoma; malignant neoplasm; papillary carcinoma; predictive value; sensitivity and specificity; three dimensional imaging; tumor classification; tumor diagnosis; breast tumor; diagnostic imaging; elastography; procedures; Breast Neoplasms; Diagnosis, Computer-Assisted; Elasticity Imaging Techniques; Female; Humans
Publisher
Elsevier Ireland Ltd
Type
journal article