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Microfilaria Analyser
Powered by Computer Vision

Precision microfilaria detection and segmentation for clinical research. Automate diagnosis with more than ~90% accuracy using our YOLO and UNet-based computer vision architecture.

Microfilaria analyser app — UNet segmentation and diagnostic output

Developed and Engineered by

PolarythmUniversiti Kebangsaan MalaysiaUKM Medical Molecular Biology Institute

Precision Analysis Infrastructure

Our platform combines high-resolution microscopy with deep learning to deliver instant, actionable data for parasitology.

Multi-Scale Support
Seamlessly switch between 10x for broad screening and 40x for detailed species differentiation and segmentation.
High-Confidence Stats
Adjustable confidence thresholds allow researchers to fine-tune sensitivity versus specificity for specific studies.

~90%

Accuracy

150ms

Latency

Ready to accelerate your research?

Start analyzing your microscopy samples today with our AI-powered workbench.

Available
10x Detection
Used for detecting presence of microfilaria in 10x microscopy images
Available
40x Classification
Used for classifying microfilaria species in 40x microscopy images
Microfilaria analyser

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