Automating prostate volume acquisition using abdominal ultrasound scans for prostate-specific antigen density calculations.

ABSTRACT: Proposed methods for prostate cancer screening are currently prohibitively expensive (due to the high costs of imaging equipment such as magnetic resonance imaging and traditional ultrasound systems), inadequate in their detection rates, require highly trained specialists, and/or are invasive, resulting in patient discomfort. These limitations make population-wide screening for prostate cancer challenging. Machine learning techniques applied to abdominal ultrasound scanning may help alleviate some of these disadvantages. Abdominal ultrasound scans are comparatively low cost and exhibit minimal patient discomfort, and machine learning can be applied to mitigate against the high operator-dependent variability of ultrasound scanning. In this study, a state-of-the-art machine learning model wa

SUBMITTER: Bennett RD 

PROVIDER: S-EPMC12484655 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature