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数字参考对象用于评估MR图像形成中的算法性能

Christian Wülker¹, Nils T Gessert¹, Mariya Doneva¹

¹Philips Research, Hamburg, Germany.

Magnetic resonance imaging

|November 4, 2023

概括

数字参考对象 (DRO) 能够客观地评估MRI图像质量 (IQ). 这项研究证明了DROs.

科学领域:

医疗成像医学成像
磁共振成像 (MRI) 是一种磁共振成像技术.
计算成像技术的成像

背景情况:

对MRI图像质量 (IQ) 的客观评估对于算法开发至关重要.
对于可重复的智商评估,需要标准化指标.
数字参考对象 (DRO) 为客观的智商评估提供了一个潜在的解决方案.

研究的目的:

介绍和展示数字参考对象 (DRO) 对评估MRI图像质量的实用性.
在MRI图像形成中建立自动化和可重复的智商指标的基础.
为了方便不同MR图像重建算法的比较.

主要方法:

数字参考对象 (DRO) 直接在k空间中采样,使用分析里埃转换公式.
基于卷积神经网络 (CNN) 的无声化算法应用于杂的ACR幻影图像.
从测量和模拟的k空间数据中重建图像以进行比较.

主要成果:

基于CNN的除算法在测量和模拟的ACR幻影数据上产生了几乎相同的结果.
视觉和定量比较证实了消光性能的一致性.
这表明了DRO在表示现实世界幻影数据方面的忠实性.

结论:

数字参考对象 (DRO) 可以指导技术选择在开发新的MR图像形成算法,包括深度学习方法.
使用DROs是实现可重复的MR图像形成的重要一步.
这种方法支持MRI智商评估的标准化.

关键词:

深度学习是一种深度学习.拒绝这种行为,就是拒绝.图像质量指标图像质量指标机器学习机器学习数学幻象在线阅读客观的图像质量评估对象.可复制性可复制性模拟模拟是为了模拟.

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相关概念视频

Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...