Deep Feature Extraction of Pap Smear Images Based on Convolutional Neural Network and Vision Transformer for Cervical Cancer Classification

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Cervical cancer is a malignant disease that women commonly experience. This cancer can be prevented if screening is carried out early using the pap smear method. The pap smear technique yields a subjective diagnosis. An appropriate decision-making method is needed to overcome this obstacle, such as using a computer-based diagnosis method and applying machine learning. We apply a combination of deep feature extraction using transfer learning from convolutional neural network models and vision transformers to obtain local and global features. Local and global features can represent an image's more comprehensive variety of features. The combined features are then reduced using two steps, principal component analysis and linear discriminant analysis, to obtain a representation of the essential features of the data. The reduced features are then analyzed using several classifiers, including SVM, K-NN, MLP, and LR. The proposed framework was evaluated on three publicly accessible datasets, namely Herlev, Mendeley LBC, and SIPaKMeD, achieving classification accuracies of 97.83% (SVM, K-NN, MLP, and LR), 100% (SVM, K- NN, MLP, and LR), and 98.52% (SVM, K-NN, and LR) respectively.

Original languageEnglish
Title of host publicationProceedings of the 2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages290-296
Number of pages7
ISBN (Electronic)9798350353464
DOIs
Publication statusPublished - 2024
Event2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024 - Hybrid, Bali, Indonesia
Duration: 4 Jul 20246 Jul 2024

Publication series

NameProceedings of the 2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024

Conference

Conference2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024
Country/TerritoryIndonesia
CityHybrid, Bali
Period4/07/246/07/24

Keywords

  • Cervical Cancer
  • Classification
  • Deep Feature Extraction
  • Feature Reduction

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