Lorenzo Patane'
Automatic Segmentation of 3D Large Field of View OCTA Skin Volumes using Deep Learning-based Methods.
Rel. Kristen Mariko Meiburger, Mengyang Liu, Giulia Rotunno. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2023
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Abstract
The skin comprises an intricate microvasculature vital for its function and health. With the ability to image capillary blood flow and internal structure of the skin in vivo, Optical Coherence Tomography-Angiography (OCTA) can offer new perspectives on the underlying causes and dynamic changes of skin conditions. OCTA can be used for non-invasive monitoring of disease progression and treatment, making it useful for diagnoses and treatment evaluation. To make OCTA suitable for basic and clinical research in dermatology, such as the assessment of wound healing, diagnosis and treatment of Chronic Venous Insufficiency (CVI), basal cell carcinoma, psoriasis, it is necessary to reliably analyze many images.
Therefore, accurate vessel segmentation is needed
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