Investigation of Cervical Cancer Detection from Whole Slide Imaging

Title

Investigation of Cervical Cancer Detection from Whole Slide Imaging

Creator

Uma N.; Inbanila K.

Description

Early cancer detection is critical in enhancing a patient's clinical results. Cervical cancer detection from a large number of whole slide images generated regularly in a clinical setting is a complex and time-consuming task. As a result, we require an efficient and accurate model for early cancer diagnosis, especially cervical cancer as it can be fully prevented if detected in an early stage. This study focuses on in-depth writing on current methodologies for cervical cancer segmentation and characterization from the whole cervical slide. It combines the state of their specialty's performance measurement with the quantitative evaluation of cutting-edge techniques. Numerous publications over the last eleven years (2011-2022) clearly outline various cervical imaging methods over multiple blocks. And this review shows different types of algorithms used in each processing stage of detection. The study clearly indicates the advancements in the automation field and the necessity of the same. Published under licence by IOP Publishing Ltd.

Source

Journal of Physics: Conference Series, Vol-2571, No. 1

Date

2023-01-01

Publisher

Institute of Physics

Subject

Cervical cancer; Classification; Deep Learning; Neural Network; Segmentation

Coverage

Uma N., Department of Electronics & Communication, Christ University, Bangalore, India; Inbanila K., Department of Electronics & Communication, Christ University, Bangalore, India

Rights

All Open Access; Gold Open Access

Relation

ISSN: 17426588

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1088/1742-6596/2571/1/012002

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176237904&doi=10.1088%2f1742-6596%2f2571%2f1%2f012002&partnerID=40&md5=bb4a184023e4d9564e5d14c0e182e065