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Semiautomatic 4D analysis of cardiac image sequences

机译:心脏图像序列的半自动4D分析

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Medical imaging scanners now exist that can generated 4D cardiac images (time sequences of 3D volumes). Since the heart is an organ that exhibits motion, examining its image characteristics with a 4D image can give useful information about its condition. For multi- dimensional image segmentation, semi-automatic methods have many advantages over manual segmentation. This paper describes a procedure for performing semi-automatic image segmentation and analysis upon a 4D cardiac image. This procedure involves the input of user- defined information (cues) at certain time points of the sequence. These cues are then automatically interpolated or extrapolated for the remaining time points. The analysis system interprets the completed sequence of cues to generate a list of image processing functions that can subsequently segment and analyze the 4D image. This paradigm has been implemented using INTERSEG, an existing 3D cue-based analysis system. This cue-based analysis procedure permits 4D cardiac image segmentation with a small amount of user interaction. Performance of the proposed 4D image analysis system compares favorably to results generated by defining cues on each individual volume, as well as manual techniques. Further, the 4D approach requires significantly less interaction time than a 3D-only approach.
机译:现在存在医学成像扫描仪,其可以产生4D心脏图像(3D卷的时间序列)。由于心脏是表现出运动的器官,因此使用4D图像检查其图像特性可以提供有关其条件的有用信息。对于多维图像分割,半自动方法具有对手动分段的许多优点。本文介绍了在4D心脏图像上执行半自动图像分割和分析的过程。该过程涉及在序列的特定时间点处输入用户定义的信息(提示)。然后将这些提示自动插入或外推以用于剩余时间点。分析系统解释所完成的提示序列,以生成可以随后段和分析4D图像的图像处理功能列表。该范例已经使用interseg实现了现有的基于3D Cue的分析系统。该基于提示的分析程序允许具有少量用户交互的4D心脏图像分割。所提出的4D图像分析系统的性能对通过定义每个体积的提示以及手动技术产生的结果进行比较。此外,4D方法需要比仅3D方法的相互作用时间更少。

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