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相关概念视频

The Thyroid Gland01:23

The Thyroid Gland

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The thyroid gland is a small, butterfly-shaped gland located in the neck and covers the anterior surface of the trachea. The gland has two lateral lobes connected by a thin tissue mass called the isthmus. Internally, each lobe comprises many small spherical structures known as thyroid follicles, surrounded by a network of blood vessels.
The follicles have a central cavity lined by simple cuboidal to squamous epithelial cells called follicular cells. These cells produce the glycoprotein...
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Synthesis and Regulation of Thyroid Hormones01:20

Synthesis and Regulation of Thyroid Hormones

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Low blood levels of the thyroid hormones — triiodothyronine (T3) and thyroxine (T4) — signal the hypothalamus to release the thyrotropin-releasing hormone (TRH). TRH then reaches the pituitary gland and stimulates the release of thyroid-stimulating hormone(TSH) into the bloodstream.
Upon reaching the thyroid gland, TSH stimulates the follicular cells' active uptake of iodide ions from the blood. The ions diffuse to the apical surface of the cells and are oxidized to iodine. The...
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Classification of Illness01:17

Classification of Illness

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The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
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相关实验视频

Updated: Jul 13, 2025

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
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深度学习以协助组合分类和甲状腺固体结节诊断:一个多中心诊断研究.

Chen Chen1,2,3, Yitao Jiang4, Jincao Yao1,5,6

  • 1Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, China.

European radiology
|October 11, 2023
PubMed
概括

深度学习模型准确地识别了甲状腺结节的组成和恶性瘤风险,表现优于高级医生. 这种框架可以减少对甲状腺结节的不必要的细针吸入程序.

关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.甲状腺结节 甲状腺结节超声波学 超声波学 超声波学

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相关实验视频

Last Updated: Jul 13, 2025

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科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 在瘤学瘤学.

背景情况:

  • 高分辨率超声波增加了甲状腺结节的检测,导致不必要的细针吸收 (FNA) 和患者焦虑.
  • 区分良性和恶性甲状腺结节对于适当的患者管理至关重要.

研究的目的:

  • 开发一个深度学习 (DL) 框架来分类甲状腺结节的组成和评估恶性瘤风险.
  • 评估卷积神经网络 (CNN) 模型在区分良性和恶性固体甲状腺结节方面的性能.

主要方法:

  • 一项回顾性多中心研究,利用6784个结节 (11,201张图像) 的超声波图像.
  • 包括Inception-ResNet在内的CNN模型被训练并验证用于结节分类.
  • 接收器运行特征曲线 (AUC) 下的面积是主要评估指标.

主要成果:

  • 对于固体甲状腺结节分级,CNN模型实现了AUC>0.91,Inception-ResNet达到0.94.
  • 最好的DL算法在测试组中显示了0.88的灵敏度和0.86的特异性.
  • 在区分良性与恶性结节方面,DL模型的表现优于高级医生 (p < 0.001).

结论:

  • 基于CNN的DL框架可以有效地协助甲状腺结节的诊断.
  • 这项技术有可能大大减少不必要的细针吸入程序.
  • DL模型为提高甲状腺癌风险评估的准确性和效率提供了一个有希望的工具.