Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review

作者: Essam H Houssein , Marwa M Emam , Abdelmgeid A Ali , Ponnuthurai Nagaratnam Suganthan , None

DOI: 10.1016/J.ESWA.2020.114161

关键词:

摘要: … a review that shows the new applications of machine learning … This review reflects on the classification of breast cancer … the different approaches to machine learning, then an overview …

参考文章(225)
D. Kopans, K. Bowyer, R. Moore, M. Heath, THE DIGITAL DATABASE FOR SCREENING MAMMOGRAPHY ,(2007)
Inês C. Moreira, Igor Amaral, Inês Domingues, António Cardoso, Maria João Cardoso, Jaime S. Cardoso, INbreast: toward a full-field digital mammographic database. Academic Radiology. ,vol. 19, pp. 236- 248 ,(2012) , 10.1016/J.ACRA.2011.09.014
Mohamed Abdel-Nasser, Hatem A. Rashwan, Domenec Puig, Antonio Moreno, Analysis of tissue abnormality and breast density in mammographic images using a uniform local directional pattern Expert Systems With Applications. ,vol. 42, pp. 9499- 9511 ,(2015) , 10.1016/J.ESWA.2015.07.072
Mellisa Pratiwi, Alexander, Jeklin Harefa, Sakka Nanda, Mammograms Classification Using Gray-level Co-occurrence Matrix and Radial Basis Function Neural Network Procedia Computer Science. ,vol. 59, pp. 83- 91 ,(2015) , 10.1016/J.PROCS.2015.07.340
Aya F. Khalaf, Inas A. Yassine, Spectral correlation analysis for microcalcification detection in digital mammogram images international symposium on biomedical imaging. pp. 88- 91 ,(2015) , 10.1109/ISBI.2015.7163823
I. Isikli Esener, S. Ergin, T. Yuksel, A new ensemble of features for breast cancer diagnosis international convention on information and communication technology electronics and microelectronics. pp. 1168- 1173 ,(2015) , 10.1109/MIPRO.2015.7160452
Luqman Mahmood Mina, Nor Ashidi Mat Isa, Breast abnormality detection in mammograms using Artificial Neural Network international conference on computer communications. pp. 258- 263 ,(2015) , 10.1109/I4CT.2015.7219577
Gisbert Schneider, Evgeny Byvatov, Support vector machine applications in bioinformatics. Applied Bioinformatics. ,vol. 2, pp. 67- 77 ,(2003)
Woo Kyung Moon, Yao-Sian Huang, Chung-Ming Lo, Chiun-Sheng Huang, Min Sun Bae, Won Hwa Kim, Jeon-Hor Chen, Ruey-Feng Chang, Computer-aided diagnosis for distinguishing between triple-negative breast cancer and fibroadenomas based on ultrasound texture features. Medical Physics. ,vol. 42, pp. 3024- 3035 ,(2015) , 10.1118/1.4921123