Acknowledgement
Supported by : Korea Health Industry Development Institute (KHIDI)
References
- Wang X, Guo Y, Wang Y. Automatic detection of regions of interest in breast ultrasound images based on local phase information. Biomed Mater Eng 2015;26 Suppl 1:S1265-S1273
- Jung KW, Won YJ, Oh CM, Kong HJ, Lee DH, Lee KH. Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2014. Cancer Res Treat 2017;49:292-305 https://doi.org/10.4143/crt.2017.118
- Chabi ML, Borget I, Ardiles R, Aboud G, Boussouar S, Vilar V, et al. Evaluation of the accuracy of a computer-aided diagnosis (CAD) system in breast ultrasound according to the radiologist's experience. Acad Radiol 2012;19:311-319 https://doi.org/10.1016/j.acra.2011.10.023
- Kim K, Song MK, Kim EK, Yoon JH. Clinical application of SDetect to breast masses on ultrasonography: a study evaluating the diagnostic performance and agreement with a dedicated breast radiologist. Ultrasonography 2017;36:3-9 https://doi.org/10.14366/usg.16012
- Chen DR, Chien CL, Kuo YF. Computer-aided assessment of tumor grade for breast cancer in ultrasound images. Comput Math Methods Med 2015;2015:914091
- Moon WK, Huang YS, Lo CM, Huang CS, Bae MS, Kim WH, et al. Computer-aided diagnosis for distinguishing between triple-negative breast cancer and fibroadenomas based on ultrasound texture features. Med Phys 2015;42:3024-3035 https://doi.org/10.1118/1.4921123
- Song SE, Seo BK, Cho KR, Woo OH, Son GS, Kim C, et al. Computer-aided detection (CAD) system for breast MRI in assessment of local tumor extent, nodal status, and multifocality of invasive breast cancers: preliminary study. Cancer Imaging 2015;15:1 https://doi.org/10.1186/s40644-015-0036-2
- Shan J, Alam SK, Garra B, Zhang Y, Ahmed T. Computer-aided diagnosis for breast ultrasound using computerized BIRADS features and machine learning methods. Ultrasound Med Biol 2016;42:980-988 https://doi.org/10.1016/j.ultrasmedbio.2015.11.016
- Cho E, Kim EK, Song MK, Yoon JH. Application of computeraided diagnosis on breast ultrasonography: evaluation of diagnostic performances and agreement of radiologists according to different levels of experience. J Ultrasound Med 2018;37:209-216 https://doi.org/10.1002/jum.14332
- Choi JH, Kang BJ, Baek JE, Lee HS, Kim SH. Application of computer-aided diagnosis in breast ultrasound interpretation: improvements in diagnostic performance according to reader experience. Ultrasonography 2017;37:217-225
- Lee SE, Moon JE, Rho YH, Kim EK, Yoon JH. Which supplementary imaging modality should be used for breast ultrasonography? Comparison of the diagnostic performance of elastography and computer-aided diagnosis. Ultrasonography 2017;36:153-159 https://doi.org/10.14366/usg.16033
- Wang Y, Jiang S, Wang H, Guo YH, Liu B, Hou Y, et al. CAD algorithms for solid breast masses discrimination: evaluation of the accuracy and interobserver variability. Ultrasound Med Biol 2010;36:1273-1281 https://doi.org/10.1016/j.ultrasmedbio.2010.05.010
- Dromain C, Boyer B, Ferre R, Canale S, Delaloge S, Balleyguier C. Computed-aided diagnosis (CAD) in the detection of breast cancer. Eur J Radiol 2013;82:417-423 https://doi.org/10.1016/j.ejrad.2012.03.005
- Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977:33;159-174 https://doi.org/10.2307/2529310
- Tan T, Platel B, Twellmann T, van Schie G, Mus R, Grivegnee A, et al. Evaluation of the effect of computer-aided classification of benign and malignant lesions on reader performance in automated three-dimensional breast ultrasound. Acad Radiol 2013;20:1381-1388 https://doi.org/10.1016/j.acra.2013.07.013
- Lehman CD, Wellman RD, Buist DS, Kerlikowske K, Tosteson AN, Miglioretti DL. Diagnostic accuracy of digital screening mammography with and without computer-aided detection. JAMA Intern Med 2015;175:1828-1837 https://doi.org/10.1001/jamainternmed.2015.5231
- Sahiner B, Chan HP, Roubidoux MA, Hadjiiski LM, Helvie MA, Paramagul C, et al. Malignant and benign breast masses on 3D US volumetric images: effect of computer-aided diagnosis on radiologist accuracy. Radiology 2007;242:716-724 https://doi.org/10.1148/radiol.2423051464
- Yoo JL, Woo OH, Kim YK, Cho KR, Yong HS, Seo BK, et al. Can MR imaging contribute in characterizing well-circumscribed breast carcinomas? Radiographics 2010;30:1689-1702 https://doi.org/10.1148/rg.306105511