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Gastric motility is the coordinated contraction and relaxation of stomach muscles that convert ingested food into chyme, a semi-liquid substance ready for further digestion in the intestines. The process begins with the vagus nerve inducing the relaxation of the smooth muscles in the fundus and body of the stomach, allowing these regions to expand and accommodate up to approximately 1.5 liters of food and liquid.
Peristaltic Waves and Chyme Formation
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Gastric emptying occurs when the stomach gradually releases chyme into the duodenum. When the stomach is distended, it triggers the release of gastrin, a hormone that promotes gastric acid secretion to aid in digestion. Additionally, stomach distension contributes to peristaltic waves that propel gastric contents toward the pyloric region. The gastroenteric reflex, on the other hand, primarily stimulates peristalsis in the intestines, facilitating the movement of contents further along the...
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In situ Quantification of Pancreatic Beta-cell Mass in Mice
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优化空间变压器用于细分胰腺异常.

Banavathu Sridevi1, B John Jaidhan2

  • 1GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, 530045, India. sbanavat@gitam.edu.

Journal of imaging informatics in medicine
|September 4, 2024
PubMed
概括
此摘要是机器生成的。

一种新的空间角注意力方法 (SHLAM) 在MRI扫描中改善了胰腺细分. 这种人工智能方法达到99.6%的准确性,克服了医疗图像分析中的挑战,以更好地进行手术规划.

关键词:
功能提取 功能提取磁共振成像技术 磁共振成像技术胰腺是什么? 胰腺是什么?预处理 预处理分段化 分段化 分段化 分段化

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科学领域:

  • 医学图像分析 医学图像分析
  • 人工智能在医学中的应用
  • 手术规划 手术规划

背景情况:

  • 从临床图像中精确划分胰腺是医疗分析和手术的挑战.
  • 图像分析和临床实践中的复杂性阻碍了准确的胰腺成像.

研究的目的:

  • 引入一种新的空间角注意力方法 (SHLAM),以改善胰腺细分.
  • 解决临床图像分析和与胰腺有关的外科手术过程中的障碍.

主要方法:

  • 开发了一种预处理功能,以消除MRI数据中的噪声.
  • 实施了属性评估,并确定了受影响地区预测的关键要素.
  • 在确定受影响区域后执行图像细分,使用80%的数据用于培训,20%用于测试.
  • 使用精度,准确性,回忆,F测量,错误率, Dice 和 Jaccard 评估最佳参数.

主要成果:

  • 在胰腺细分方面,SHLAM方法实现了99.6%的准确率.
  • 通过将SHLAM与各种现有模型进行比较,验证了性能改进.
  • 与替代方法相比,表现出优越的性能.

结论:

  • 空间角注意力方法 (SHLAM) 显著提高了胰腺细分的准确性.
  • SHLAM为医疗图像分析挑战提供了强大的解决方案,帮助手术程序.
  • 该方法显示了提高诊断准确性和患者治疗结果的潜力.