AnnoCerv: A new dataset for feature-driven and image-based automated colposcopy analysis

Abstract

Colposcopy imaging is pivotal in cervical cancer diagnosis, a major health concern for women. The computational challenge lies in accurate lesion recognition. A significant hindrance for many existing machine learning solutions is the scarcity of comprehensive training datasets.

Keywords

• colposcopy imaging
• cervical cancer diagnosis
• lesion segmentation
• automated image analysis