A deep learning-based hybrid artificial intelligence model for the detection and severity assessment of vitiligo lesions.

ABSTRACT:

Background

We aimed to establish and validate a deep learning-based hybrid artificial intelligence (AI) model for the objective morphometric and colorimetric assessment of vitiligo lesions.

Methods

Two main datasets containing curated images of vitiligo lesions from Chinese patients (Fitzpatrick skin types III or IV) were established, including one with 2,720 images for lesion localization study and the other with 1,262 images for lesion segmentation study. Besides, an additional test set containing 145 images of vitiligo lesions from other Fitzpatrick skin types (I, II, or V) was also generated. A 3-stage hybrid model was constructed. YOLO v3 (You Only Look Once, v3) architecture was trained and validated to classify and localize vitiligo lesions, with sensitivity and error

SUBMITTER: Guo L 

PROVIDER: S-EPMC9201159 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature