Research Keyword: image analysis

Assessing the Validity and Impact of Remote Digital Image Reading in Fungal Diagnostics

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This study tested whether trained mycologists could accurately identify fungal infections from digital images viewed remotely, similar to how radiologists review X-rays. Five experienced laboratory professionals analyzed 474 images of different fungi with accuracy rates between 78-93%. The results suggest that remote digital diagnosis could help hospitals in developing countries where expert mycologists are scarce, enabling faster and more accurate diagnosis of serious fungal infections.

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Monitoring the impact of confinement on hyphal penetration and fungal behavior

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Scientists created tiny glass channels that mimic soil conditions to study how fungi grow when squeezed into tight spaces. They observed seven different fungal species growing through these channels and measured how fast their thread-like hyphae could push through. Most fungi slowed down in tighter spaces, but each species had unique behaviors, like branching patterns or the ability to push so hard they broke the glass containers.

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Micro-CT and deep learning: Modern techniques and applications in insect morphology and neuroscience

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Modern scanning technology called micro-CT can create detailed 3D pictures of tiny insects and their brains without damaging them. Artificial intelligence using deep learning can automatically analyze these massive image files much faster than humans could. Scientists are combining these two technologies to map insect brains and sensory systems in unprecedented detail, potentially revealing how insects sense and process information from their environment.

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Characterization of spatio-temporal dynamics of the constrained network of the filamentous fungus Podospora anserina using a geomatics-based approach

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Researchers studied how a fungus called Podospora anserina adapts its growth pattern when exposed to challenging conditions like nutrient scarcity, temperature changes, and bright light. Using a novel computer mapping technique borrowed from geography, they discovered that fungi don’t just grow slower under stress—they reorganize how densely they pack their filaments. This geomatics approach revealed that different stresses cause different patterns of network densification, providing new insights into fungal survival strategies.

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