Lesion segmentation using 3D scan and deep learning for the evaluation of facial portwine stain birthmarks

Ke, Cheng; Huang, Yuanbo; Yang, Jun; Zhang, Yunjie; Zhan, Huiqi; Wu, Chunfa; Bi, Mingye; Huang, Zheng

doi:10.1016/j.pdpdt.2024.104030

Cited by 1 publication

(1 citation statement)

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“…This network was built around the foundational architecture of the original DeepLabV3+ model [ 13 ]. The deep learning-based semantic segmentation technique can intelligently divide PWS lesions of varying color and shape in the texture mapping of three-dimensional (3D) pictures [ 14 ]. Semantic segmentation can be employed in conjunction with 3D scanning to assess the size of face PWS lesions [ 14 ].…”

Section: Discussionmentioning

confidence: 99%

Port-Wine Stains and Intraoral Hemangiomas: A Case Series

Arumugam Venkatachalam Sargurunathan,

Gowda Venkatesha

et al. 2024

Cureus

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Port-wine stains (PWSs), also called port-wine birthmarks or nevus flammeus, are hamartomatous vascular capillary malformations that clinically appear as erythematous areas on the buccal mucosa, vermilion border of the lip, gingiva, or pink to port-wine-colored patches on skin since birth and persist throughout life. On the face, they occur in the area supplied by the trigeminal nerve. PWSs have structural abnormalities of the intradermal capillaries. PWSs on the skin and oral mucosa contain ectatic capillaries in the dermis and submucosa, respectively. PWSs occur anywhere, and the oral mucosa is no exception. PWSs on the facial skin lead to cosmetic disfigurement and create social stigma. Clinically, PWSs start as flat, pink, or red patches and may darken, thicken, and develop nodules over time. The diagnosis of PWSs is primarily clinical. PWSs are complex vascular malformations with significant clinical, psychosocial, and therapeutic challenges. This article enlightens a series of cases of PWSs on the facial skin and capillary hemangioma on the gingiva, buccal mucosa, and lip diagnosed by a diascopy test, etiopathogenesis, differential diagnosis, and management of PWSs.

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Section: Discussionmentioning

confidence: 99%