Emerging trends in breast imaging and cancer detection: Systematic review

• Autores: Mohamed El Gazzar, Majed Salem Juaifer Bajuaifer, Amal Abdullah Ali Masmali, Amina Mohammed ali Almomen, Norah Eid Hareer AlAnazi, Khulood Khalid Rashed Alrabyee, Israa Ahmed Salem Alhaffaf, Noor Abdullah Abdulrahim Altarooti, Ghadi Said Alahmadi, Talal Mohammed Abu Jazilah, Fouz Mohammed Alshamrani, Nissren Tamam, Mahmoud Gharib
• Localización: Revista iberoamericana de psicología del ejercicio y el deporte, ISSN 1886-8576, Vol. 20, Nº. 6, 2025, págs. 651-655
• Idioma: inglés
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• Referencias bibliográficas
  • 1. Abdul Halim, A. A., Andrew, A. M., & Mohd Yasin, M. N. (2021). Existing and emerging breast cancer detection technologies and its challenges:...
  • 2. Abhisheka, B., Biswas, S. K., & others. (2023). A comprehensive review on breast cancer detection, classification and segmentation...
  • 3. Abhisheka, B., Biswas, S. K., Purkayastha, B., & Das, D. (2024). Recent trend in medical imaging modalities and their applications...
  • 4. Ahmed, R. O. A. G., Darwish, M. A. E. H., Chalabi, N. A. E., & Tantawy, S. H. (2023). Role of tomosynthesis and ultrasound in the assessment...
  • 5. AlSawaftah, N., El-Abed, S., Dhou, S., & Zakaria, A. (2022). Microwave imaging for early breast cancer detection: Current state, challenges,...
  • 6. Balkenende, L., Teuwen, J., & Mann, R. M. (2022). Application of deep learning in breast cancer imaging. Seminars in Nuclear Medicine,...
  • 7. Ben Ammar, M., Ayachi, F. L., & others. (2024). Harnessing deep learning for early breast cancer diagnosis: A review of datasets, methods,...
  • 8. Bhushan, A., Gonsalves, A., & Menon, J. U. (2021). Current state of breast cancer diagnosis, treatment, and theranostics. Pharmaceutics,...
  • 9. Borowiec, T., Matkowski, R., Cybulska-Stopa, B., Kuniej, T., Kołodziejczyk, A., Dupla, D., & Maciejczyk, A. (2025). Baseline cross-sectional...
  • 10. Felipe, V. C., Graziano, L., Barbosa, P. N., Calsavara, V. F., & Bitencourt, A. G. (2020). Multidetector computed tomography with...
  • 11. Formaz, E., Schmidt, C., Berger, N., Schönenberger, A. L., Wieler, J., Frauenfelder, T., & Marcon, M. (2023). Dedicated breast computedtomography...
  • 12. Gouda, W., Yasin, R., Yasin, M. I., & Omar, S. (2024). Automated breast ultrasound in breast cancer screening of mammographically...
  • 13. He, N., Wu, Y. P., Kong, Y., Lv, N., Huang, Z. M., Li, S., & Wei, W. D. (2016). The utility of breast cone-beam computed tomography,...
  • 14. Lauritzen, A. D., von Euler-Chelpin, M. C., Lynge, E., Vejborg, I., Nielsen, M., Karssemeijer, N., & Lillholm, M. (2023). Assessing...
  • 15. Lång, K., Andersson, I., Rosso, A., Tingberg, A., Timberg, P., & Zackrisson, S. (2016). Performance of one-view breast tomosynthesis...
  • 16. Lee, Y., Ni, J., Beretov, J., Wasinger, V. C., Graham, P., & Li, Y. (2023). Recent advances of small extracellular vesicle biomarkers...
  • 17. Luo, L., Wang, X., Lin, Y., Ma, X., & Tan, A. (2024). Deep learning in breast cancer imaging: A decade of progress and future directions....
  • 18. Meenalochini, G., & Ramkumar, S. (2021). Survey of machine learning algorithms for breast cancer detection using mammogram images....
  • 19. Monticciolo, D. L., Malak, S. F., Friedewald, S. M., & others. (2021). Breast cancer screening recommendations inclusive of all women...
  • 20. Nasser, M., & Yusof, U. K. (2023). Deep learning based methods for breast cancer diagnosis: A systematic review and future direction....
  • 21. Niu, L., Bao, L., Zhu, L., Tan, Y., Xu, X., Shan, Y., & Shen, Y. (2019). Diagnostic performance of automated breast ultrasound in...
  • 22. Raza, A., Ullah, N., Khan, J. A., Assam, M., & Guzzo, A. (2023). DeepBreastCancerNet: A novel deep learning model for breast cancer...
  • 23. Rezaei, Z. (2021). A review on image-based approaches for breast cancer detection, segmentation, and classification. Expert Systems with...
  • 24. Shah, S. M., Khan, R. A., Arif, S., & Sajid, U. (2021). Artificial intelligence for breast cancer detection: Trends & directions....
  • 25. Tufail, A. B., Ma, Y. K., Kaabar, M. K. A., & others. (2021). Deep learning in cancer diagnosis and prognosis prediction: A minireview...
  • 26. Umadevi, K., Sundeep, D., Vighnesh, A. R., & Misra, A. (2025). Current trends and advances in nanoplatforms-based imaging for cancer...
  • 27. Urano, M., Shiraki, N., Kawai, T., Goto, T., Endo, Y., Yoshimoto, N., & Shibamoto, Y. (2016). Digital mammography versus digital breast...
  • 28. Wang, L. (2023). Microwave imaging and sensing techniques for breast cancer detection. Micromachines, 14(6): 1183.
  • 29. Wang, X., Ahmad, I., Javeed, D., Zaidi, S. A., & Alotaibi, F. M. (2022). Intelligent hybrid deep learning model for breast cancer...
  • 30. Zebari, D. A., Ibrahim, D. A., Zeebaree, D. Q., & others. (2021). Systematic review of computing approaches for breast cancer detection...