Intelligent Suite

Intelligent Suite automates malaria pathogen detection in thick smear microscopy images using a custom YOLO-mp-3l model optimized and deployed with OpenVINO.

Key Features:

• OpenVINO Integration: The suite utilizes OpenVINO's inference engine for model optimization and deployment across several inference devices.
• Custom Detection Model: The suite employs a custom YOLO-mp-3l model trained on the Darknet framework for malaria pathogen detection.
• Inference Device Selection: The suite supports inference device and mode selection, including deployment on a Neural Compute Stick 2 (NCS2).
• Model Parameter Adjustment: The suite allows users to alter model parameters for detection tasks.
• Detection Reporting: The suite generates detection reports along with model performance metrics.

Scientific Applications:

• Malaria Pathogen Detection: The suite automates detection of malaria pathogens in thick smear microscope images of blood samples.
• Diagnostic Support in Endemic Regions: The suite addresses the scarcity of expert microscopists in remote areas where malaria is endemic.

Methodology:

The custom YOLO-mp-3l model is trained on the Darknet framework and optimized using OpenVINO for inference deployment.