https://scholars.lib.ntu.edu.tw/handle/123456789/477768
標題: | Multi-dimensional tumor detection in automated whole breast ultrasound using topographic watershed | 作者: | Lo C.-M. Chen R.-T. YEUN-CHUNG CHANG YA-WEN YANG Hung M.-J. CHIUN-SHENG HUANG Chang R.-F. |
公開日期: | 2014 | 出版社: | Institute of Electrical and Electronics Engineers Inc. | 卷: | 33 | 期: | 7 | 起(迄)頁: | 1503-1511 | 來源出版物: | IEEE Transactions on Medical Imaging | 摘要: | 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. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903782536&doi=10.1109%2fTMI.2014.2315206&partnerID=40&md5=14cbd0806296f1c6a02d010242a71a84 https://scholars.lib.ntu.edu.tw/handle/123456789/477768 |
ISSN: | 0278-0062 | DOI: | 10.1109/TMI.2014.2315206 | SDG/關鍵字: | 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 |
顯示於: | 醫學系 |
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