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基于机器学习的自动扫描处方腰椎MRI收购

Eugene Ozhinsky¹, Felix Liu¹, Valentina Pedoia¹

¹Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4(th) St, San Francisco, CA 94143, United States.

Magnetic resonance imaging

|April 4, 2024

概括

这项研究引入了一种机器学习管道,用于自动磁共振成像 (MRI) 扫描处方,提高腰椎成像的准确性. 该系统显示了临床使用的可行性,减少了患者扫描中的手动调整.

科学领域:

放射学放射学是一门学科.
医疗成像医学成像
机器学习机器学习

背景情况:

准确的扫描处方对于无错误的放射学解释至关重要.
最佳覆盖和对准解剖结构是MRI质量的关键.

研究的目的:

开发一条机器学习管道,用于自动化斜扫描处方.
使用先前MRI检查的定位器图像和元数据来训练管道.

主要方法:

开发了一种新的基于多片旋转区域的卷积神经网络 (MS-R2CNN) 架构.
模型被训练为自动的斜腰腰脊柱.
该管道集成到扫描仪控制台软件中,并对志愿者和患者进行了测试.

主要成果:

自动化处方在健康志愿者中表现出高准确度.
在手动和自动化处方之间观察到良好的一致性,以实现对齐和覆盖.
在患者中,90%的产生的处方被应用到最小的调整中.

结论:

定向物体检测模型可以在没有手动注释的情况下开出斜腰脊椎MRI.
机器学习管道可用于扫描仪上的自动化MRI采集处方.

关键词:

自动化处方的自动化处方自动扫描计划自动化扫描计划腰椎脊柱的腰椎脊柱是指腰椎脊柱的部分.机器学习是机器学习.磁共振成像技术磁共振成像技术肌肉骨的MRI是指肌肉骨的MRI.

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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...