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Advancements in Dermatological Diagnosis: Harnessing Artificial Intelligence, Deep Learning, and 3D Reconstructions in Noninvasive Skin Imaging| title | Advancements in Dermatological Diagnosis: Harnessing Artificial Intelligence, Deep Learning, and 3D Reconstructions in Noninvasive Skin Imaging |
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| start_date | 2024/06/11 |
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| schedule | 10h |
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| online | no |
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| location_info | TPR2 salle de réunion 04.05 |
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| summary | Noninvasive skin imaging techniques, including reflectance confocal microscopy (RCM) and optical coherence tomography (OCT), are transforming the landscape of skin cancer diagnosis and management. However, the current reliance on human expert readers for diagnosis presents limitations. Artificial intelligence (AI), deep learning, and 3D reconstructions are revolutionizing healthcare by enhancing diagnostic and prognostic capabilities. In dermatology, their integration with noninvasive skin imaging holds significant promise for improving the accuracy and efficiency of disease diagnosis and monitoring. They can guide technicians during image acquisition, remove artifacts, and enhance image quality. Furthermore, they can assist dermatologists in identifying regions of interest, facilitating automated lesion detection, classification, and monitoring with heightened accuracy and efficiency. Automated detection would further enable widespread utilization of these techniques. |
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| responsibles | NC |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2024/06/06 09:36 UTC |
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