Multi-dimensional tumor detection in automated whole breast ultrasound using topographic watershed
Journal
IEEE Transactions on Medical Imaging
Journal Volume
33
Journal Issue
7
Pages
1503-1511
Date Issued
2014
Author(s)
Abstract
Automated whole breast ultrasound (ABUS) is becoming a popular screening modality for whole breast examination. Compared to conventional handheld ultrasound, ABUS achieves operator-independent and is feasible for mass screening. However, reviewing hundreds of slices in an ABUS image volume is time-consuming. A computer-aided detection (CADe) system based on watershed transform was proposed in this study to accelerate the reviewing. The watershed transform was applied to gather similar tissues around local minima to be homogeneous regions. The likelihoods of being tumors of the regions were estimated using the quantitative morphology, intensity, and texture features in the 2-D/3-D false positive reduction (FPR). The collected database comprised 68 benign and 65 malignant tumors. As a result, the proposed system achieved sensitivities of 100% (133/133), 90% (121/133), and 80% (107/133) with FPs/pass of 9.44, 5.42, and 3.33, respectively. The figure of merit of the combination of three feature sets is 0.46 which is significantly better than that of other feature sets (p-value < 0.05). In summary, the proposed CADe system based on the multi-dimensional FPR using the integrated feature set is promising in detecting tumors in ABUS images. ? 1982-2012 IEEE.
SDGs
Other Subjects
Automation; Image segmentation; Tumors; Ultrasonic applications; Breast Cancer; Breast ultrasound; Computer-aided detection; False-positive reduction; Watershed segmentation; Diagnosis; adult; aged; article; automated whole breast ultrasound; benign tumor; cancer diagnosis; computer aided design; computer aided detection system; echomammography; female; human; human tissue; intraductal carcinoma; major clinical study; malignant neoplastic disease; pattern recognition; quantitative analysis; real time ultrasound scanner; retrospective study; sensitivity analysis; ultrasound transducer; algorithm; breast tumor; computer assisted diagnosis; echography; echomammography; middle aged; procedures; receiver operating characteristic; very elderly; young adult; Adult; Aged; Aged, 80 and over; Algorithms; Breast Neoplasms; Female; Humans; Image Interpretation, Computer-Assisted; Middle Aged; ROC Curve; Ultrasonography, Mammary; Young Adult
Publisher
Institute of Electrical and Electronics Engineers Inc.
Type
journal article