Enhancing Surgical Predictions with Computer Vision
At Accelvision, we had the privilege of collaborating with an innovative spinout from a prominent research institution to improve predictive analytics for spinal surgery complications. The company’s proprietary regression model relied on geometric measurements of spinal discs to assess the probability of surgical complications, but manual measurement processes introduced significant variability, impacting prediction accuracy.
Our contributions included:
- Training Advanced Computer Vision Models: We developed a segmentation model to accurately and consistently identify spinal discs in MRI scans.
- Implementing Complex Geometric Calculations: Leveraging logic from research MATLAB code, we implemented precise geometric computations in Python to automate the extraction of key features from the segmented discs.
This solution not only improved prediction accuracy but also saved valuable time for experts, who now only needed to make minor corrections to the disk masks rather than creating them manually. The standardized and efficient pipeline exemplifies our ability to combine cutting-edge AI with domain-specific expertise to deliver impactful and time-saving solutions.