Artefact-Aware Fungal Detection in Dermatophytosis: A Real-Time Transformer-Based Approach for KOH Microscopy

Researchers have developed a transformer-based model using RT-DETR architecture to accurately detect fungal hyphae in KOH microscopy images for diagnosing dermatophytosis, achieving high precision and recall rates while distinguishing between fungal elements and artefacts. This AI system can serve as an automated screening tool, enhancing the reliability of image-level analysis and aiding clinical decision-making for content creators focusing on medical diagnostics.

Read the full article at arXiv cs.CV (Vision)

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