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  1. Home
  3. Fully-automatic Detection And Diagnosis System For Thyroid Nodules Based On Ultrasound Video Sequences By Artificial Intelligence.
  1. Home
  3. Fully-automatic Detection And Diagnosis System For Thyroid Nodules Based On Ultrasound Video Sequences By Artificial Intelligence.

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Fully-Automatic Detection and Diagnosis System for Thyroid Nodules Based on Ultrasound Video Sequences by Artificial

Dan Liu1, Ke Yang2, Chunquan Zhang1

  • 1Department of Ultrasound, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, People's Republic of China.

Journal of Multidisciplinary Healthcare
|April 22, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

This study developed an artificial intelligence (AI) system for automatic thyroid nodule detection and diagnosis from ultrasound videos. The AI system demonstrated high accuracy, outperforming junior radiologists and matching senior ones.

Keywords:
Artificial intelligenceDeep learningRadiomicsThyroid noduleUltrasonography

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Oncology

Background:

  • Thyroid nodule diagnosis via ultrasound is subjective and time-consuming.
  • Artificial intelligence (AI) offers objective and efficient analysis.
  • Developing automated AI systems for thyroid nodule assessment is crucial.

Purpose of the Study:

  • To create a fully automatic AI system for thyroid nodule detection and diagnosis using ultrasound video sequences.
  • To evaluate the performance of the AI system in comparison to human radiologists.

Main Methods:

  • A prospective cohort of 1067 thyroid nodules was analyzed using dynamic ultrasound videos.
  • Two deep learning models were developed for automatic nodule detection and diagnosis.
  • Performance was measured using Average Precision (AP) for detection and Area Under the Curve (AUC) for diagnosis.

Main Results:

  • The AI detection model achieved an AP of 0.914.
  • The AI diagnostic model yielded an AUC of 0.953.
  • The AI system's diagnostic performance surpassed junior radiologists and was comparable to senior radiologists.

Conclusions:

  • A fully automatic AI system for thyroid nodule detection and diagnosis from ultrasound video was successfully established.
  • This AI approach can optimize the management of patients with thyroid nodules.
  • The system provides an objective and efficient tool for thyroid nodule analysis.