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Updated: Jun 27, 2025

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一个基于深度学习的散射校正与水相当的路径长度图,用于数字放射学

Masayuki Hattori1,2, Hisato Tsubakiya3, Sung-Hyun Lee4

  • 1Graduate School of Science and Engineering, Yamagata University, Yonezawa, 992-8510, Japan. m-hattori@med.id.yamagata-u.ac.jp.

Radiological physics and technology
|May 2, 2024
PubMed
概括

一个新的深度学习模型使用水等效路径长度图准确地纠正数字放射学中的散射. 这种方法可以提高图像质量和对比度,而不需要物理放射学系统来训练数据.

关键词:
深度学习是一种深度学习.数字辐射学数字辐射学蒙特卡洛模拟的蒙特卡洛模拟分散的纠正纠正分散的纠正这就是U-Net.水相当的路径长度和路径长度.

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To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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