Machine learning for accurate differentiation of benign and malignant breast tumors presenting as non-mass enhancement Conference Paper
| Authors: | Illan, I. A.; Tahmassebi, A.; Ramirez, J.; Gorriz, J. M.; Foo, S. Y.; Pinker-Domenig, K.; Meyer-Baese, A. |
| Editors: | Mahalanobis, A.; Ashok, A.; Tian, L.; Petruccelli, J. C. |
| Title: | Machine learning for accurate differentiation of benign and malignant breast tumors presenting as non-mass enhancement |
| Conference Title: | Computational Imaging III |
| Abstract: | Accurate methods for breast cancer diagnosis are of capital importance for selection and guidance of treatment and optimal patient outcomes. In dynamic contrast enhancing magnetic resonance imaging (DCE-MRI), the accurate differentiation of benign and malignant breast tumors that present as non-mass enhancing (NME) lesions is challenging, often resulting in unnecessary biopsies. Here we propose a new approach for the accurate diagnosis of such lesions with high resolution DCE-MRI by taking advantage of seven robust classification methods to discriminate between malignant and benign NME lesions using their dynamic curves at the voxel level, and test it in a manually delineated dataset. The tested approaches achieve a diagnostic accuracy up to 94% accuracy, sensitivity of 99 % and specificity of 90% respectively, with superiority of high temporal compared to high spatial resolution sequences. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. |
| Keywords: | magnetic resonance imaging; diagnostic accuracy; breast cancer; medical imaging; tumors; artificial intelligence; patient treatment; diseases; statistical tests; computer aided diagnosis; high spatial resolution; machine learning; classification (of information); learning systems; dynamic contrast enhanced magnetic resonance imaging; breast cancer diagnosis; computer aided instruction; computer aided diagnosis (cad); dynamic contrast enhanced magnetic resonance imaging (dce-mri); computer aided diagnosis(cad); mass enhancement; robust classification |
| Journal Title | Proceedings of SPIE |
| Volume: | 10669 |
| Conference Dates: | 2018 Apr 15-17 |
| Conference Location: | Orlando, FL |
| ISBN: | 0277-786X |
| Publisher: | SPIE |
| Date Published: | 2018-01-01 |
| Start Page: | 10669 0W |
| Language: | English |
| DOI: | 10.1117/12.2304588 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Conference Paper -- Export Date: 1 August 2018 -- Source: Scopus |
