Mivora Neuro Hospital, a renowned neurosurgical institute in Switzerland, faced growing challenges in accurately segmenting brain tumors during pre-surgical planning. Manual segmentation performed by radiologists required extensive time—often several hours per case—and carried the risk of variability in identifying tumor boundaries. These inconsistencies could impact surgical precision and overall patient outcomes.
To address this, the hospital integrated our AI-powered Brain Tumor Segmentation Platform, which leverages deep learning models trained on thousands of MRI datasets. The system automatically identifies and highlights tumor regions in high-resolution scans.
The AI solution streamlined the pre-surgical process by reducing planning time by 40%, enabling clinicians to focus on critical surgical decisions rather than manual data interpretation. With real-time visualization and integration into existing PACS systems, the hospital achieved improved accuracy, reduced workload, and enhanced patient safety in neurosurgical planning.
With complex MRI data and rising surgical demands, Mivora Neuro Hospital faced:
The AI-powered system was developed to assist neurosurgeons by delivering precise, automated brain tumor segmentation from MRI scans.
Delivered precise, data-driven insights that improved surgical accuracy, reduced planning time, and enhanced patient outcomes.
AI gives us an extra set of expert eyes. It spots subtle indicators in scans that even trained specialists might miss.
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