Case Study: Pixelabs achieves up to 95% recall with Ultralytics YOLO

Pixelabs achieves up to 95% recall with Ultralytics YOLO

Pixelabs, a visual AI platform company based in Madrid, faced challenges in scaling manual image review processes, particularly in the difficult and time-consuming analysis of retinal images for early Alzheimer's detection research. To automate these visual workflows and improve consistency, Pixelabs integrated Ultralytics YOLO models into its Pixelabs AI-Engine.

By implementing custom-trained Ultralytics YOLOv8 models within its analysis pipeline, Pixelabs achieved a recall rate of up to 95% for identifying retinal indicators like amyloid beta deposits. This Ultralytics-powered solution provided more accurate and consistent results, allowing researchers to reliably detect small features across large datasets and significantly improving the efficiency of the analysis workflow.

Pixelabs