https://scholars.lib.ntu.edu.tw/handle/123456789/379086
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Yi-Chen Lai | en_US |
dc.contributor.author | Yao-Sian Huang | en_US |
dc.contributor.author | Day-Woei Wang | en_US |
dc.contributor.author | Chui-Mei Tiu | en_US |
dc.contributor.author | Yi-Hong Chou | en_US |
dc.contributor.author | Ruey-Feng Chang | en_US |
dc.contributor.author | RUEY-FENG CHANG | zz |
dc.creator | Yi-Chen Lai;Yao-Sian Huang;Day-Woei Wang;Chui-Mei Tiu;Yi-Hong Chou;Ruey-Feng Chang | - |
dc.date.accessioned | 2018-09-10T09:46:11Z | - |
dc.date.available | 2018-09-10T09:46:11Z | - |
dc.date.issued | 2013-04 | - |
dc.identifier.uri | http://scholars.lib.ntu.edu.tw/handle/123456789/379086 | - |
dc.description.abstract | In recent studies, both tumor morphology and vascularity played an important role in differentiating breast tumors. In this article, a computer-aided diagnosis (CAD) system was proposed to quantify the tumor morphology of vascularity on three-dimensional (3-D) power Doppler breast ultrasound (PDUS) images. We segmented the tumor margin by the level set method and skeletonized vessels by the 3-D thinning algorithm from 3-D PDUS data to capture the B-mode and vascularity features. The B-mode features including texture, shape and ellipsoid fitting and the vascularity features containing volume, complexity, length, radius and tortuosity were used to differentiate breast tumors. In the experiment, 82 biopsy-verified lesions including 41 benign and 41 malignant lesions were used to test the performance of the proposed system. The proposed method performed well, achieving accuracy, sensitivity, specificity and Az values of 85.37% (70/82), 85.37% (35/41), 85.37% (35/41) and 0.9104, respectively. ? 2013 World Federation for Ultrasound in Medicine & Biology. | - |
dc.language | en | en |
dc.relation.ispartof | Ultrasound in Medicine & Biology | en_US |
dc.source | AH | - |
dc.subject | Breast tumor; Computer-aided diagnosis; Power Doppler ultrasonography; Ultrasound; Vascularity | - |
dc.subject.classification | [SDGs]SDG3 | - |
dc.subject.other | Algorithms; Computer aided diagnosis; Medical imaging; Morphology; Tumors; Ultrasonic imaging; Ultrasonics; Breast tumor; Breast ultrasound; Ellipsoid-fitting; Power doppler ultrasonographies; Thinning algorithm; Threedimensional (3-d); Tumor morphology; Vascularity; Three dimensional; adult; aged; algorithm; article; B scan; breast biopsy; breast cancer; breast tumor; computer assisted diagnosis; computer system; controlled study; diagnostic accuracy; diagnostic test accuracy study; diagnostic value; Doppler echography; female; human; image processing; major clinical study; priority journal; sensitivity and specificity; three dimensional power Doppler ultrasound; tumor classification; tumor vascularization; ultrasound scanner; ultrasound transducer | - |
dc.title | Computer-Aided Diagnosis for 3-D Power Doppler Breast Ultrasound | - |
dc.type | journal article | en |
dc.identifier.doi | 10.1016/j.ultrasmedbio.2012.09.020 | - |
dc.relation.pages | 555--567 | - |
dc.relation.journalvolume | 39 | - |
dc.relation.journalissue | 4 | - |
item.fulltext | no fulltext | - |
item.openairetype | journal article | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.grantfulltext | none | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | Biomedical Electronics and Bioinformatics | - |
crisitem.author.dept | Networking and Multimedia | - |
crisitem.author.dept | Computer Science and Information Engineering | - |
crisitem.author.dept | Center for Artificial Intelligence and Advanced Robotics | - |
crisitem.author.orcid | 0000-0002-2086-0097 | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | Others: University-Level Research Centers | - |
顯示於: | 資訊工程學系 |
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