An Intelligent Diagnostic Model for Melasma Based on Deep Learning and Multimode Image Input.

ABSTRACT:

Introduction

The diagnosis of melasma is often based on the naked-eye judgment of physicians. However, this is a challenge for inexperienced physicians and non-professionals, and incorrect treatment might have serious consequences. Therefore, it is important to develop an accurate method for melasma diagnosis. The objective of this study is to develop and validate an intelligent diagnostic system based on deep learning for melasma images.

Methods

A total of 8010 images in the VISIA system, comprising 4005 images of patients with melasma and 4005 images of patients without melasma, were collected for training and testing. Inspired by four high-performance structures (i.e., DenseNet, ResNet, Swin Transformer, and MobileNet), the performances of deep learning models in melasma

SUBMITTER: Liu L 

PROVIDER: S-EPMC9884721 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature