Texture Analysis on Thyroid Ultrasound Images for the Classification of Hashimoto Thyroiditis

Kohila, S. and Sankara Malliga, G. (2019) Texture Analysis on Thyroid Ultrasound Images for the Classification of Hashimoto Thyroiditis. In: Computer Aided Intervention and Diagnostics in Clinical and Medical Images. Springer Link, pp. 271-279.

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Abstract

The biopsy using Fine Needle Aspiration (FNA) is a major procedure/testing method which has been regularly recommended, at a time, exactly when
a thyroid nodule is suspected or else identified. The FNA will usually reveal if a
nodule is benign or malignant. Histopathology is also sometimes recommended.
Another regular test is the ultrasound. Yet, the ultrasound cannot recognize or distinguish the thyroid disorders. Hashimoto thyroiditis is the most widely recognized
kind of inflammation of the thyroid gland. The motto of this work is to identify the
Hashimoto’s thyroiditis disorder using only ultrasonogram images without going
for any painful examination. In this paper, features are studied using the Neighborhood Gray Tone Difference Matrix (NGTDM), Statistical Feature Matrix (SFM), and
Laws’ texture energy measures methods. The salient features from the above procedures are helpful to identify and in separating the two types of ultrasonic thyroid
images as normal and Hashimoto’s thyroiditis. The student two-tailed unpaired T-test
method is employed to classify the two groups. A major difference between the two
groups (p < 0.001) was observed. The results are correlated with the histopathology
results. The results prove that the Hashimoto thyroiditis can be identified using the
ultrasound images.

Item Type: Book Section
Subjects: Electronics and Communication Engineering > Digital Signal Processing
Divisions: Electronics and Communication Engineering
Depositing User: Mr IR Admin
Date Deposited: 02 Oct 2024 09:22
Last Modified: 02 Oct 2024 09:22
URI: https://ir.vistas.ac.in/id/eprint/8054

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