This technology integrates FDG-PET and high-resolution MRI to perform automated quantitative analysis and lateralization of epileptogenic foci in medial temporal lobe epilepsy. By calculating standardized uptake values (SUVs) and using machine learning algorithms, it improves pre-surgical evaluation accuracy compared to traditional visual assessment. The system reduces the need for invasive procedures and has been clinically validated with patent protection.

This technology represents a scientific breakthrough by integrating high-resolution MRI and FDG-PET with machine learning to automate the lateralization of epileptogenic foci in medial temporal lobe epilepsy (MTLE). It overcomes the limitations of traditional visual interpretation by using individualized standardized uptake values (SUVs) and lateralization indices (LIs) to guide classification. Validated in surgical cases, it achieved 100% accuracy in external testing.

This technology enables automated and quantitative analysis of FDG-PET for pre-surgical evaluation in epilepsy, reducing manual workload and invasive procedures. It is well-suited for integration into hospital systems, cloud-based diagnostic platforms, and SaMD products. With strong applicability in both advanced and emerging healthcare markets, it offers commercialization potential through clinical deployment and international collaborations.