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相关概念视频

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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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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Autoimmune Disorders01:29

Autoimmune Disorders

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Autoimmune diseases are a group of disorders in which the body's immune system mistakenly attacks its own cells, tissues, and organs. This results from an overactive immune response against substances and tissues normally present in the body. Let's delve into the concept and mechanism of autoimmune diseases from an immune system point of view, explore different causes and examples of such diseases, and discuss potential solutions.
Concept and Mechanism of Autoimmune Diseases
The immune...
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相关实验视频

Updated: Jan 14, 2026

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
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MCFL:为哈西莫托的甲状腺炎识别多模式协作融合学习.

Wenchao Jiang, Guanjie Zhou, Honghua Bai

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |January 12, 2026
    PubMed
    概括

    一种新的多模式协作融合学习 (MCFL) 方法增强了超声波成像和生物化学数据,用于诊断哈西莫托甲状腺炎 (HT). 这种方法通过重新校准指标以获得更好的意义和特异性来提高诊断准确性.

    科学领域:

    • 医疗成像医学成像
    • 生物化学 生物化学
    • 人工智能在医学中的应用

    背景情况:

    • 哈西莫托的甲状腺炎 (HT) 诊断依赖于超声波成像和生物化学测试,但单独是不够的.
    • 现有的多式联运模型在图像和文本数据之间的特征维度不平衡中扎.
    • 准确的HT诊断需要有效地整合各种数据模式.

    研究的目的:

    • 提出一种新的多模式协作融合学习 (MCFL) 方法,以加强HT诊断.
    • 用超声波图像数据提高生物化学指标的意义和特异性.
    • 为了克服现有的多式联运模式在处理方面的局限性,特征是维度不平衡.

    主要方法:

    • 开发了一种新的INNet,将超声波图像特征转换为局部突出炎症 (Lpi) 和全球扩散病变 (Gdl) 指标.
    • 采用基于决策树的优化策略,使用Lpi和Gdl重新校准生物化学指标.
    • 利用了深度Q学习框架与经验重复和e-greedy战略用于诊断指导和模型稳定性.

    主要成果:

    • 通过超声波图像数据,MCFL有效地增强和重新校准生物化学指标.
    • 该方法将图像和文本数据统一到一个单一的表示空间中.
    • 在来自多个医疗中心的多式联络数据集上实现了最先进的性能.

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    结论:

    • 在HT诊断的多式联络学习中,MCFL提供了显著的进步.
    • 拟议的方法为诊断哈西莫托甲状腺炎的准确性和稳定性设定了新的基准.
    • 通过协作融合学习整合成像和生物化学数据对于复杂疾病诊断至关重要.