Applications of computational methods in biomedical breast cancer imaging diagnostics: A review
| dc.contributor.author | Aruleba, Kehinde | |
| dc.contributor.author | Obaido, George | |
| dc.contributor.author | Aruleba, Raphael Taiwo | |
| dc.date.accessioned | 2020-11-23T10:18:43Z | |
| dc.date.available | 2020-11-23T10:18:43Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | With the exponential increase in new cases coupled with an increased mortality rate, cancer has ranked as the second most prevalent cause of death in the world. Early detection is paramount for suitable diagnosis and effective treatment of different kinds of cancers, but this is limited to the accuracy and sensitivity of available diagnostic imaging methods. Breast cancer is the most widely diagnosed cancer among women across the globe with a high percentage of total cancer deaths requiring an intensive, accurate, and sensitive imaging approach. Indeed, it is treatable when detected at an early stage. | en_US |
| dc.identifier.citation | Aruleba, K. et al. (2020). Applications of computational methods in biomedical breast cancer imaging diagnostics: A review. Journal of Imaging ,6(10),105 | en_US |
| dc.identifier.issn | 2313-433X | |
| dc.identifier.uri | https://doi.org/10.3390/jimaging6100105 | |
| dc.identifier.uri | http://hdl.handle.net/10566/5460 | |
| dc.language.iso | en | en_US |
| dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | en_US |
| dc.subject | Cancer | en_US |
| dc.subject | Breast cancer | en_US |
| dc.subject | Diagnostics | en_US |
| dc.subject | Imaging | en_US |
| dc.subject | Computation | en_US |
| dc.title | Applications of computational methods in biomedical breast cancer imaging diagnostics: A review | en_US |
| dc.type | Article | en_US |