2024
DOI: 10.1002/ima.23043
|View full text |Cite
|
Sign up to set email alerts
|

CerviFormer: A pap smear‐based cervical cancer classification method using cross‐attention and latent transformer

Bhaswati Singha Deo,
Mayukha Pal,
Prasanta K. Panigrahi
et al.

Abstract: Cervical cancer is one of the primary causes of death in women. It should be diagnosed early and treated according to the best medical advice, similar to other diseases, to ensure that its effects are as minimal as possible. Pap smear images are one of the most constructive ways for identifying this type of cancer. This study proposes a cross‐attention‐based Transfomer approach for the reliable classification of cervical cancer in pap smear images. In this study, we propose the CerviFormer‐a model that depends… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
4
1

Relationship

1
4

Authors

Journals

citations
Cited by 12 publications
references
References 67 publications
0
0
0
Order By: Relevance