在干预圆束CT中进行可变形运动补偿,并使用上下文感知学习自动对焦度量
Heyuan Huang1, Yixuan Liu1, Jeffrey H Siewerdsen1,2
1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Medical physics
|May 11, 2024
概括
一种新的深度学习方法,视觉信息忠实度-深度学习 (VIF-DL),准确地量化了圆束CT (CBCT) 成像中的运动工件. 这种进步提高了图像质量,并有助于指导干预程序.
科学领域:
- 医疗成像医学成像
- 放射学中的人工智能
- 干预性放射学 干预性放射学
背景情况:
- 干预圆束CT (CBCT) 为腹部干预提供3D可视化,但由于采集时间长,受到运动工件的限制.
- 现有的自动对焦方法使用手工制作的指标,缺乏解剖学上下文和潜在运动的意识.
- 需要一种新的数据驱动方法来准确量化CBCT中的运动诱导退化.
研究的目的:
- 引入一个学习,上下文意识,可变形的度量,视觉信息忠实度-深度学习 (VIF-DL),用于CBCT中的运动量化.
- 开发一种深度卷积神经网络 (CNN),能够评估图像质量退化和解剖现实性.
- 改进运动补偿策略,以加强干预程序的指导.
主要方法:
- 设计了一个深度的CNN架构,用于voxel-wise和上下文特征提取的多分支处理.
- 美国有线电视新闻网 (CNN) 接受了训练,以模拟运动损坏的CBCT数据来模拟基于参考的结构相似度指标 (VIF).
- 使用相关性指标,不同参数的模拟研究和实验幻影数据验证了性能,随后将其集成到自动对焦框架中.
主要成果:
- VIF-DL显示了与地面真实VIF的高相关性 (0.95在模拟中,0.88在真实数据中),以及与运动场的良好相关性 (0.90).
- 该指标准确地反映了不同的运动幅度和频率,区分轻微的运动和严重的运动.
- 使用VIF-DL的自动对焦补偿显著减少了运动工件,提高了高达9.20%的空间分辨率和9.64%的容器度.
结论:
- 拟议的VIF-DL指标有效量化运动诱导的图像质量下降和解剖学可信性以无参考的方式.
- 它的情境感知架构确保了在各种运动模式,成像技术和解剖学变异中提供强大的性能.
- 与传统指标相比,VIF-DL是一个显著的进步,为改善临床干预中的深度自动对焦运动补偿铺平了道路.
相关概念视频
01:10Computed Tomography
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
01:25Relative Motion Analysis using Rotating Axes
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it instrumental in...
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it instrumental in...