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Hyphae structures are detected and visualized; whole-slide images are classified into positive (with hyphae) and negative.
Whole-slide images are preprocessed by Mindpeak Onychomycosis AI and the cases are triaged correspondingly.
Upon opening a case, suspicious regions with detected hyphae are identified. These regions of interest are highlighted and presented appropriately. Users review the case and provide a final decisive assessment.
Proprietary AI model for fungus detection based on convolutional neural networks.
Standard personal working machine. Minimum requirements: 32 bit Processor Intel Core i5 or better; 4 GB RAM.
All major whole slide image formats: (tif, mrxs, etc.), png, jpg/jpeg.
Nail, Fungus detection, Onychomycosis, Fungus Hyphae, PAS, Deep learning, Artificial Intelligence, Image analysis.
The first commercial dermatopathology AI solution to detect nail fungus hypha
Mindpeak Onychomycosis AI reliability is on par with human experts.