Poster preview

Details

Dermatology, as a pivotal clinical-surgical field, requires precise scrutiny of suspicious lesions to improve diagnostic accuracy and minimize unnecessary biopsies. Complementary technologies like reflectance confocal microscopy (RCM) provide detailed skin layer visualization, reducing invasive biopsies by up to 60%. Despite its benefits, mastering RCM diagnosis requires extensive training and experience, highlighting a current limitation in its widespread adoption. To address this gap, exploring the integration of deep learning algorithms in RCM analysis emerges as a promising avenue. Leverag...