OralNet: Fused Optimal Deep Features Framework for Oral Squamous Cell Carcinoma Detection.

ABSTRACT: Humankind is witnessing a gradual increase in cancer incidence, emphasizing the importance of early diagnosis and treatment, and follow-up clinical protocols. Oral or mouth cancer, categorized under head and neck cancers, requires effective screening for timely detection. This study proposes a framework, OralNet, for oral cancer detection using histopathology images. The research encompasses four stages: (i) Image collection and preprocessing, gathering and preparing histopathology images for analysis; (ii) feature extraction using deep and handcrafted scheme, extracting relevant features from images using deep learning techniques and traditional methods; (iii) feature reduction artificial hummingbird algorithm (AHA) and concatenation: Reducing feature dimensionality using AHA and concaten

SUBMITTER: Mohan R 

PROVIDER: S-EPMC10377094 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature