Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A Review
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 accur...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Journal of Imaging |
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| Online Access: | https://www.mdpi.com/2313-433X/6/10/105 |
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| author | Kehinde Aruleba George Obaido Blessing Ogbuokiri Adewale Oluwaseun Fadaka Ashwil Klein Tayo Alex Adekiya Raphael Taiwo Aruleba |
| author_facet | Kehinde Aruleba George Obaido Blessing Ogbuokiri Adewale Oluwaseun Fadaka Ashwil Klein Tayo Alex Adekiya Raphael Taiwo Aruleba |
| author_sort | Kehinde Aruleba |
| collection | DOAJ |
| description | 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. Hence, the use of state of the art computational approaches has been proposed as a potential alternative approach for the design and development of novel diagnostic imaging methods for breast cancer. Thus, this review provides a concise overview of past and present conventional diagnostics approaches in breast cancer detection. Further, we gave an account of several computational models (machine learning, deep learning, and robotics), which have been developed and can serve as alternative techniques for breast cancer diagnostics imaging. This review will be helpful to academia, medical practitioners, and others for further study in this area to improve the biomedical breast cancer imaging diagnosis. |
| first_indexed | 2024-03-10T15:48:00Z |
| format | Article |
| id | doaj.art-98acfcafc6f3472bb50520f157be95b2 |
| institution | Directory Open Access Journal |
| issn | 2313-433X |
| language | English |
| last_indexed | 2024-03-10T15:48:00Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Imaging |
| spelling | doaj.art-98acfcafc6f3472bb50520f157be95b22023-11-20T16:20:09ZengMDPI AGJournal of Imaging2313-433X2020-10-0161010510.3390/jimaging6100105Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A ReviewKehinde Aruleba0George Obaido1Blessing Ogbuokiri2Adewale Oluwaseun Fadaka3Ashwil Klein4Tayo Alex Adekiya5Raphael Taiwo Aruleba6School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg 2001, South AfricaSchool of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg 2001, South AfricaSchool of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg 2001, South AfricaDepartment of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Private Bag X17, Bellville, Cape Town 7535, South AfricaDepartment of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Private Bag X17, Bellville, Cape Town 7535, South AfricaDepartment of Pharmacy and Pharmacology, School of Therapeutic Science, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, 7 York Road, Parktown 2193, South AfricaDepartment of Molecular and Cell Biology, Faculty of Science, University of Cape Town, Cape Town 7701, South AfricaWith 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. Hence, the use of state of the art computational approaches has been proposed as a potential alternative approach for the design and development of novel diagnostic imaging methods for breast cancer. Thus, this review provides a concise overview of past and present conventional diagnostics approaches in breast cancer detection. Further, we gave an account of several computational models (machine learning, deep learning, and robotics), which have been developed and can serve as alternative techniques for breast cancer diagnostics imaging. This review will be helpful to academia, medical practitioners, and others for further study in this area to improve the biomedical breast cancer imaging diagnosis.https://www.mdpi.com/2313-433X/6/10/105cancerbreast cancerdiagnosticsimagingcomputationartificial intelligence |
| spellingShingle | Kehinde Aruleba George Obaido Blessing Ogbuokiri Adewale Oluwaseun Fadaka Ashwil Klein Tayo Alex Adekiya Raphael Taiwo Aruleba Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A Review Journal of Imaging cancer breast cancer diagnostics imaging computation artificial intelligence |
| title | Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A Review |
| title_full | Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A Review |
| title_fullStr | Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A Review |
| title_full_unstemmed | Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A Review |
| title_short | Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A Review |
| title_sort | applications of computational methods in biomedical breast cancer imaging diagnostics a review |
| topic | cancer breast cancer diagnostics imaging computation artificial intelligence |
| url | https://www.mdpi.com/2313-433X/6/10/105 |
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