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arXiv · 1911.08303

Lightweight Residual Network for The Classification of Thyroid Nodules

Ponugoti Nikhila·Sabari Nathan·Elmer Jeto Gomes Ataide·Alfredo Illanes·Michael Friebe·Srichandana Abbineni
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Abstract

Ultrasound is a useful technique for diagnosing thyroid nodules. Benign and malignant nodules that automatically discriminate in the ultrasound pictures can provide diagnostic recommendations or, improve diagnostic accuracy in the absence of specialists. The main issue here is how to collect suitable features for this particular task. We suggest here a technique for extracting features from ultrasound pictures based on the Residual U-net. We attempt to introduce significant semantic characteristics to the classification. Our model gained 95% classification accuracy.

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Ponugoti Nikhila, Sabari Nathan, Elmer Jeto Gomes Ataide, Alfredo Illanes, Michael Friebe, Srichandana Abbineni. 2019-11-16. Lightweight Residual Network for The Classification of Thyroid Nodules. https://arxiv.org/abs/1911.08303

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