Academic Journal
Surface-Based Ultrasound Scans for the Screening of Prostate Cancer
| العنوان: | Surface-Based Ultrasound Scans for the Screening of Prostate Cancer |
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| المؤلفون: | Rory Bennett, Tristan Barrett, Vincent J. Gnanapragasam, Zion Tse |
| المصدر: | IEEE Open Journal of Engineering in Medicine and Biology, Vol 6, Pp 212-218 (2025) |
| بيانات النشر: | IEEE, 2025. |
| سنة النشر: | 2025 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Medical technology |
| مصطلحات موضوعية: | Abdominal ultrasound, machine learning, prostate cancer, PSA-density, surface-based ultrasound, Computer applications to medicine. Medical informatics, R858-859.7, Medical technology, R855-855.5 |
| الوصف: | Surface-based ultrasound (SUS) systems have undergone substantial improvement over the years in image quality, ease-of-use, and reduction in size. Their ability to image organs non-invasively makes them a prime technology for the diagnosis and monitoring of various diseases and conditions. An example is the screening/risk- stratification of prostate cancer (PCa) using prostate-specific antigen density (PSAD). Current literature predominantly focuses on prostate volume (PV) estimation techniques that make use of magnetic resonance imaging (MRI) or transrectal ultrasound (TRUS) imaging, while SUS techniques are largely overlooked. If a reliable SUS PCa screening method can be introduced, patients may be able to forgo unnecessary MRI or TRUS scans. Such a screening procedure could be introduced into standard primary care settings with point-of-care ultrasound systems available at a fraction of the cost of their larger hospital counterparts. This review analyses whether literature suggests it is possible to use SUS-derived PV in the calculation of PSAD. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2644-1276 |
| Relation: | https://ieeexplore.ieee.org/document/10758798/; https://doaj.org/toc/2644-1276 |
| DOI: | 10.1109/OJEMB.2024.3503494 |
| URL الوصول: | https://doaj.org/article/3e642d1d39474ee188f66c77ea7822e8 |
| رقم الانضمام: | edsdoj.3e642d1d39474ee188f66c77ea7822e8 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 26441276 |
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| DOI: | 10.1109/OJEMB.2024.3503494 |