Abstract No. 192 AI-Assisted Prostate Segmentation Module for MRI-Guided Transurethral Ultrasound (TULSA) Treatment Planning: Multi-reader Multi-case Study and Initial Real-World Experience
During MRI-guided Transurethral Ultrasound Ablation (TULSA) of the prostate, the physician manually outlines the intended treatment zone on intra-procedural axial T2w images before starting ablation. This contouring task is repetitive, time-consuming, and subject to intra- and inter-reader variability. We present the validation of a deep learning model for artificial intelligence (AI)–assisted whole prostate segmentation compared to manual segmentation with two goals: 1) non-inferior accuracy and 2) time savings.
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During MRI-guided Transurethral Ultrasound Ablation (TULSA) of the prostate, the physician manually outlines the intended treatment zone on intra-procedural axial T2w images before starting ablation. This contouring task is repetitive, time-consuming, and subject to intra- and inter-reader variability. We present the validation of a deep learning model for artificial intelligence (AI)–assisted whole prostate segmentation compared to manual segmentation with two goals: 1) non-inferior accuracy and 2) time savings.
