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Simulating Contrast-Enhanced MRI for Prostate Cancer by aladino50 is a document available to read on EtoBox.

This study evaluates the feasibility of generating simulated contrast-enhanced MRI for suspected prostate cancer using deep learning techniques, specifically the pix2pix algorithm. Results show high similarity between simulated and actual contrast-enhanced images, with excellent agreement in PI-RADS scoring among radiologists. The findings suggest that simulated imaging could potentially reduce the need for gadolinium-based contrast agents while maintaining diagnostic accuracy.

Author
aladino50
Language
EN