High-resolution AI image dataset for diagnosing oral submucous fibrosis and squamous cell carcinoma.

ABSTRACT: Oral cancer is a global health challenge with a difficult histopathological diagnosis. The accurate histopathological interpretation of oral cancer tissue samples remains difficult. However, early diagnosis is very challenging due to a lack of experienced pathologists and inter- observer variability in diagnosis. The application of artificial intelligence (deep learning algorithms) for oral cancer histology images is very promising for rapid diagnosis. However, it requires a quality annotated dataset to build AI models. We present ORCHID (ORal Cancer Histology Image Database), a specialized database generated to advance research in AI-based histology image analytics of oral cancer and precancer. The ORCHID database is an extensive multicenter collection of high-resolution images captured a

SUBMITTER: Chaudhary N 

PROVIDER: S-EPMC11436638 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature