https://scholars.lib.ntu.edu.tw/handle/123456789/489581
標題: | The adaptive computer-aided diagnosis system based on tumor sizes for the classification of breast tumors detected at screening ultrasound | 作者: | Moon, W.K. Chen, I.-L. Chang, J.M. Shin, S.U. Lo, C.-M. RUEY-FENG CHANG |
關鍵字: | Breast cancer; Computer-aided diagnosis; Screening ultrasound | 公開日期: | 2017 | 卷: | 76 | 起(迄)頁: | 70-77 | 來源出版物: | Ultrasonics | 摘要: | Screening ultrasound (US) is increasingly used as a supplement to mammography in women with dense breasts, and more than 80% of cancers detected by US alone are 1?cm or smaller. An adaptive computer-aided diagnosis (CAD) system based on tumor size was proposed to classify breast tumors detected at screening US images using quantitative morphological and textural features. In the present study, a database containing 156 tumors (78 benign and 78 malignant) was separated into two subsets of different tumor sizes (<1?cm and ?1?cm) to explore the improvement in the performance of the CAD system. After adaptation, the accuracies, sensitivities, specificities and Az values of the CAD for the entire database increased from 73.1% (114/156), 73.1% (57/78), 73.1% (57/78), and 0.790 to 81.4% (127/156), 83.3% (65/78), 79.5% (62/78), and 0.852, respectively. In the data subset of tumors larger than 1?cm, the performance improved from 66.2% (51/77), 68.3% (28/41), 63.9% (23/36), and 0.703 to 81.8% (63/77), 85.4% (35/41), 77.8% (28/36), and 0.855, respectively. The proposed CAD system can be helpful to classify breast tumors detected at screening US. ? 2016 Elsevier B.V. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/489581 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85008870606&doi=10.1016%2fj.ultras.2016.12.017&partnerID=40&md5=101afc363ab29a164a670b02f6fcc995 |
ISSN: | 0041624X | DOI: | 10.1016/j.ultras.2016.12.017 | SDG/關鍵字: | Diagnosis; Diseases; Medical imaging; Tumors; Ultrasonics; Breast Cancer; Breast tumor; CAD system; Computer aided diagnosis systems; Computer Aided Diagnosis(CAD); Data subsets; Textural feature; Tumor size; Computer aided diagnosis; adult; aged; breast density; breast tumor; computer assisted diagnosis; diagnostic imaging; echomammography; female; human; middle aged; needle biopsy; pathology; sensitivity and specificity; Adult; Aged; Biopsy, Needle; Breast Density; Breast Neoplasms; Diagnosis, Computer-Assisted; Female; Humans; Middle Aged; Sensitivity and Specificity; Ultrasonography, Mammary |
顯示於: | 資訊工程學系 |
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