A Semi-automated Approach to Improve the Efficiency of Medical Imaging Segmentation for Haptic Rendering.
A Semi-automated Approach to Improve the Efficiency of Medical Imaging Segmentation for Haptic Rendering.
复制标题
提高触觉渲染医学成像分割效率的半自动化方法。
DOI：
10.1007/s10278-017-9985-2
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发表时间：
2017
影响因子：
4.4
通讯作者：
Krishnaswamy,Srinivasan
中科院分区：
文献类型：
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作者：
Banerjee,Pat;Hu,Mengqi;Kannan,Rahul;Krishnaswamy,Srinivasan
Sensimmer平台代表了我们正在进行的关于3D模型的同时触觉和图形渲染的研究。为了使用Sensimmer模拟医疗和外科手术，必须从医学成像数据（如磁共振成像（MRI）或计算机断层扫描（CT））中获取3D模型。图像分割技术用于从图像确定感兴趣的解剖结构。三维模型是通过分割得到的，其三角形约简是图形和触觉渲染所必需的。本文重点介绍了通过基于像素对比度的CT图像自动分割来创建3D模型，以集成Sensimmer和医疗成像设备之间的接口，使用体积方法，Hough变换方法和手动居中方法。因此，自动化过程将分割时间缩短了56.35%，同时在±2个体素处保持相同的输出精度。
The Sensimmer platform represents our ongoing research on simultaneous haptics and graphics rendering of 3D models. For simulation of medical and surgical procedures using Sensimmer, 3D models must be obtained from medical imaging data, such as magnetic resonance imaging (MRI) or computed tomography (CT). Image segmentation techniques are used to determine the anatomies of interest from the images. 3D models are obtained from segmentation and their triangle reduction is required for graphics and haptics rendering. This paper focuses on creating 3D models by automating the segmentation of CT images based on the pixel contrast for integrating the interface between Sensimmer and medical imaging devices, using the volumetric approach, Hough transform method, and manual centering method. Hence, automating the process has reduced the segmentation time by 56.35% while maintaining the same accuracy of the output at ±2 voxels.