Detection and Diagnosis of Tumor Regions in Thyroid Images using CANFIS Classifier

Authors

  • Malathi MOHAN Pondicherry University
  • Srinivasan SABANAYAGAM Annamalai University

Keywords:

Thyroid images, Tumor regions, Diagnosis, Segmentation, Co-active Adaptive Neuro-Fuzzy Inference System classifier

Abstract

Thyroid tumor is an uncommon type of cancer. This cancer can be cured if it is detected promptly and treated correctly. This paper presents a tool for the detection and diagnosis of thyroid malignant areas using Co-active Adaptive Neuro-Fuzzy Inference System (CANFIS) classifier. The proposed methodology considers the image enhancement stage, feature extraction along with classification stage. The Gaussian filter is applied to enhance the thyroid image in terms of smoothening the edge regions and features are extracted from the enhanced thyroid image. These extracted features are classified using the proposed algorithm to classify the thyroid image into either benign or malignant nodule. The tumor region of interest is segmented by morphological segmentation. The performance of the planned thyroid tumor detection system is analyzed using performance parameters.

Author Biographies

Malathi MOHAN, Pondicherry University

Electronics and Communication Engineering

Srinivasan SABANAYAGAM, Annamalai University

Electronics & Instrumentation Engineering

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Published

01.12.2017

How to Cite

1.
MOHAN M, SABANAYAGAM S. Detection and Diagnosis of Tumor Regions in Thyroid Images using CANFIS Classifier. Appl Med Inform [Internet]. 2017 Dec. 1 [cited 2024 Feb. 22];39(3-4):41-8. Available from: https://ami.info.umfcluj.ro/index.php/AMI/article/view/615

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Section

Articles