MRI histopathology effectively detects prostate cancer using deep learning techniques, enhancing diagnosis.
The study identified optimal imaging parameters for accurate prostate cancer detection, backing clinical practices.
In silico analysis employed deep learning methods to classify prostate cancer based on MRI histopathologic data.
These findings may support advancements in prostate cancer diagnostics, emphasizing the role of imaging data.
Abstract
This in silico study demonstrates the feasibility of MRI histopathology for prostate cancer detection and identifies optimal imaging parameters to guide clinical acquisition.