Thyroid Nodule Cell Classification in Cytology Images Using Transfer Learning Approach

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

5 Scopus citations

Abstract

Analysis of fine needle aspiration cytology FNAC slides of thyroid nodules is a very crucial test before the preoperative diagnosis of thyroid malignancy. Cytology slides may be composed of different types of cells. Differentiating between cancerous cells and healthy cells plays an important role in the treatment. However, the conventional visual inspection is very time consuming and the process might endure inaccuracies because of the subject-level assessment. To the best of our knowledge, no work has been done for the multi-class cell level classification of thyroid nodules. In this paper, we propose a method for classification of cytology images at the cell level by using fine-tuned VGG-19 and AlexNet models, exploiting the transfer learning approach to better fit the model for classification of our dataset. Model evaluations are done by calculating the precision, recall, F1-score, and accuracy. Although the data is highly imbalanced, but both model have shown very good performance by achieving an accuracy of 93.05% and 92.88% by VGG-19 and AlexNet respectively.

Original languageBritish English
Title of host publicationProceedings of the 12th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2020
EditorsAjith Abraham, Yukio Ohsawa, Niketa Gandhi, M. A. Jabbar, Abdelkrim Haqiq, Seán McLoone, Biju Issac
PublisherSpringer Science and Business Media Deutschland GmbH
Pages539-549
Number of pages11
ISBN (Print)9783030736880
DOIs
StatePublished - 2021
Event12th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2020 and 16th International Conference on Information Assurance and Security, IAS 2020 - Virtual, Online
Duration: 15 Dec 202018 Dec 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1383 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference12th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2020 and 16th International Conference on Information Assurance and Security, IAS 2020
CityVirtual, Online
Period15/12/2018/12/20

Keywords

  • Deep learning
  • FNAC
  • Thyroid cancer detection

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