Keratinocytic Skin Cancer Detection on the Face Using Region-Based Convolutional Neural Network.

ABSTRACT:

Importance

Detection of cutaneous cancer on the face using deep-learning algorithms has been challenging because various anatomic structures create curves and shades that confuse the algorithm and can potentially lead to false-positive results.

Objective

To evaluate whether an algorithm can automatically locate suspected areas and predict the probability of a lesion being malignant.

Design, setting, and participants

Region-based convolutional neural network technology was used to create 924 538 possible lesions by extracting nodular benign lesions from 182 348 clinical photographs. After manually or automatically annotating these possible lesions based on image findings, convolutional neural networks were trained with 1 106 886 image crops to locate and diagnose cance

SUBMITTER: Han SS 

PROVIDER: S-EPMC6902187 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature