Hybrid Topological Data Analysis and Deep Learning for Basal Cell Carcinoma Diagnosis.

ABSTRACT: A critical clinical indicator for basal cell carcinoma (BCC) is the presence of telangiectasia (narrow, arborizing blood vessels) within the skin lesions. Many skin cancer imaging processes today exploit deep learning (DL) models for diagnosis, segmentation of features, and feature analysis. To extend automated diagnosis, recent computational intelligence research has also explored the field of Topological Data Analysis (TDA), a branch of mathematics that uses topology to extract meaningful information from highly complex data. This study combines TDA and DL with ensemble learning to create a hybrid TDA-DL BCC diagnostic model. Persistence homology (a TDA technique) is implemented to extract topological features from automatically segmented telangiectasia as well as skin lesions, and DL fe

SUBMITTER: Maurya A 

PROVIDER: S-EPMC10976904 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature