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.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.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.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 |