A Systematic Benchmark of Intraoperative Ultrasound-to-MR Synthesis for Brain Tumour Surgery
Researchers have conducted a comprehensive benchmark of AI models designed to synthesize MRI-like images from intraoperative ultrasound data for brain tumor surgery. The study evaluated six different generator architectures, including GANs, transformers, and diffusion models, across four inference regimes and two target modalities. Critically, the findings indicate that perceptual quality metrics, such as LPIPS, correlate more closely with downstream surgical utility, like tumor segmentation, than traditional image fidelity metrics like SSIM. AI
IMPACT Highlights the importance of perceptual and downstream task metrics over traditional image fidelity for AI in surgical planning.