Prostate cancer has long confounded even the most experienced eyes, hiding in the subtle gradients of imaging scans where disagreement among readers is common and missed diagnoses carry real consequence. Into this uncertainty, researchers have introduced MUSegNet, an artificial intelligence system trained to detect clinically significant prostate cancer on micro-ultrasound with greater accuracy than expert radiologists. Developed to work within the practical constraints of scarce labeled data and an emerging imaging technology, the system achieved 85% detection accuracy — surpassing six specia