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

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

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.

Bibliographic Details
Main Authors: Minciună Dorina Adelina, Socolov Demetra Gabriela, Szőcs Attila, Ivanov Doina, Gîscă Tudor, Nechifor Valentin, Budai Sándor, Gál Attila, Bálint Ákos, Socolov Răzvan, Iclanzan David
Format: Article
Language:English
Published: Scientia Publishing House 2023-12-01
Series:Acta Universitatis Sapientiae: Informatica
Subjects:
colposcopy imaging
cervical cancer diagnosis
lesion segmentation
automated image analysis
Online Access:https://doi.org/10.2478/ausi-2023-0019

Internet

https://doi.org/10.2478/ausi-2023-0019

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