一种基于人脑三维模型分割断面图像上脑沟、回的方法与实现

目的 借助人脑三维模型实现二维断面图像上大脑沟、回的分割。方法 首先在三维脑模型上以勾勒轮廓的方式界定不同脑沟、脑回区域,然后映射到断面相应区域上,进行区域内颜色填充,达到分割目的;并采用Visual C++ 6.0结合可视化类库工具包搭建脑沟、回分割平台,予以实现。结果 准确有效地分割出了序列断面图像上的右脑中央前回和中央后回。结论 此方法为获取完整、连续的脑沟、脑回断面解剖图谱提供了一种简单可行的实现手段,对于丰富数字化脑图谱及促进脑部功能与疾病诊断定位相关研究有重要意义。     

基于医学图像的三维模拟手术

目的 对实现三维模拟手术的关键技术进行研究,构建基于医学图像的三维模拟手术平台. 方法在VC++平台下,使用三维分割算法对体数据进行分割,结合VTK对读入的体数据进行交互式三维重建和虚拟切割,并对各种虚拟切割方式的性能进行分析. 结果实现了医学CT/MR图像的交互式三维重建、虚拟手术刀切割以及虚拟手术规划. 结论该系统可以辅助医生对手术过程进行模拟,为医生观察三维人体组织器官结构及病灶部位,实施辅助手术提供有力的帮助.     

基于磁共振图像的脑皮层厚度测量方法

基于磁共振图像的脑皮层厚度测量方法,是在图像处理的基础上对脑灰质组织结构进行活体定量估计的一种新的技术.本文介绍了脑皮层厚度测量与分析方法的基本流程,并将现有几种流行的测量方法进行总结和归纳,最后比较分析了这些算法的测量精度和运行速度.     

Quantification and visualization of alveolar bone resorption from 3D dental CT images

Purpose A computer aided diagnosis (CAD) system for quantifying and visualizing alveolar bone resorption caused by periodontitis was developed based on three-dimensional (3D) image processing of dental CT images. Methods The proposed system enables visualization and quantification of resorption of alveolar bone surrounding and between the roots of teeth. It has the following functions: (1) vertical measurement of the depth of resorption surrounding the tooth in 3D images, avoiding physical obstruction; (2) quantification of the amount of resorption in the furcation area; and (3) visualization of quantification results by pseudo-color maps, graphs, and motion pictures. The resorption measurement accuracy in the area surrounding teeth was evaluated by comparing with dentist’s recognition on five real patient CT images, giving average absolute difference of 0.87 mm. An artificial image with mathematical truth was also used for measurement evaluation. Results The average absolute difference was 0.36 and 0.10 mm for surrounding and furcation areas, respectively. The system provides an intuitive presentation of the measurement results. Conclusion Computer aided diagnosis of 3D dental CT scans is feasible and the technique is a promising new tool for the quantitative evaluation of periodontal bone loss.     

Virtual endoscopic colonography based on 3D MRI

Background: To evaluate the potential of magnetic resonance colonography (MRC) in detecting colorectal mass lesions. Methods: Twenty patients underwent MR imaging (MRI) before colonoscopy. The colon was filled with a gadolinium (0.5 mol):water mixture (1:100) under MRI control, and patients were imaged while breath-holding imaged with a three-dimensional spoiled gradient echo sequence in the prone and supine positions. Images were interactively analyzed based on the combination of multiplanar reconstruction and virtual colonoscopy by a radiologist blinded to colonoscopic findings and the patient's history. MRC interpretations were correlated with colonoscopic results. Results: Polyps smaller than 5 mm could not be identified with MRC. The sensitivity for detecting polyps of 5–10 mm was 70%, whereas mass lesions larger than 10 mm were all detected (sensitivity = 100). The sensitivity, specificity, and accuracy for identifying polyp-positive patients including the three patients with small (<5 mm) polyps were 64%, 89%, and 75%, respectively. Conclusion: Virtual colonoscopy based on MRI data is feasible and should be evaluated in a larger sample of patients.     

Segmentation of multiple organs in non-contrast 3D abdominal CT images

Objective We propose a simultaneous extraction method for 12 organs from non-contrast three-dimensional abdominal CT images. Materials and methods The proposed method uses an abdominal cavity standardization process and atlas guided segmentation incorporating parameter estimation with the EM algorithm to deal with the large fluctuations in the feature distribution parameters between subjects. Segmentation is then performed using multiple level sets, which minimize the energy function that considers the hierarchy and exclusiveness between organs as well as uniformity of grey values in organs. To assess the performance of the proposed method, ten non-contrast 3D CT volumes were used. Results The accuracy of the feature distribution parameter estimation was slightly improved using the proposed EM method, resulting in better performance of the segmentation process. Nine organs out of twelve were statistically improved compared with the results without the proposed parameter estimation process. The proposed multiple level sets also boosted the performance of the segmentation by 7.2 points on average compared with the atlas guided segmentation. Nine out of twelve organs were confirmed to be statistically improved compared with the atlas guided method. Conclusion The proposed method was statistically proved to have better performance in the segmentation of 3D CT volumes. This study was originally presented at CARS 2006 and supported by a Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology, Japan.     

Algorithm for haptic rendering of reconstructed 3D solid organs

Purpose  The use of haptic (the sensing of touch) technology as an interactive tool for new diagnostic procedures is an important and interesting goal because of the potential benefits. Materials and methods  We developed an algorithm for integration of haptic sensing in a medical 3D visualization environment. 3D reconstructions were generated from a stack of medical preoperative images. The innovation of the presented work is the improvement on the behavior of the haptic rendering over previous algorithms. First, the tool we developed for 3D reconstruction is presented. The classical pipeline for surface 3D reconstruction is reviewed from a parametric point of view. These parameters play an important role in the analysis of the haptic behavior. In addition, all the parameters of the reconstruction are accessible and can be modified on-line during the reconstruction procedure. Next, the software architecture used for the integration of the haptic devices is described. The haptic rendering algorithm is detailed, including the collision detection algorithm (a simple ray-tracing scheme programmed using VTK) that is used with the medical images. Results  The results obtained by evaluation of the haptic algorithm’s behavior are presented, demonstrating acceptance of the interactive tool by medical professionals. Conclusion  An improved method for haptic sensing and interaction in a 3D medical visualization environment is feasible and promises to improve image-guided interventions and minimally invasive surgery.     

Fast extraction of minimal paths in 3D images and applications to virtual endoscopy

The aim of this article is to build trajectories for virtual endoscopy inside 3D medical images, using the most automatic way. Usually the construction of this trajectory is left to the clinician who must define some points on the path manually using three orthogonal views. But for a complex structure such as the colon, those views give little information on the shape of the object of interest. The path construction in 3D images becomes a very tedious task and precise a priori knowledge of the structure is needed to determine a suitable trajectory. We propose a more automatic path tracking method to overcome those drawbacks: we are able to build a path, given only one or two end points and the 3D image as inputs. This work is based on previous work by Cohen and Kimmel [Int. J. Comp. Vis. 24 (1) (1997) 57] for extracting paths in 2D images using Fast Marching algorithm.Our original contribution is twofold. On the first hand, we present a general technical contribution which extends minimal paths to 3D images and gives new improvements of the approach that are relevant in 2D as well as in 3D to extract linear structures in images. It includes techniques to make the path extraction scheme faster and easier, by reducing the user interaction.We also develop a new method to extract a centered path in tubular structures. Synthetic and real medical images are used to illustrate each contribution.On the other hand, we show that our method can be efficiently applied to the problem of finding a centered path in tubular anatomical structures with minimum interactivity, and that this path can be used for virtual endoscopy. Results are shown in various anatomical regions (colon, brain vessels, arteries) with different 3D imaging protocols (CT, MR).     

基于虚拟现实的女性盆腔可视化及手术仿真

目的 实现基于虚拟现实的女性盆腔可视化及手术仿真.方法 选取中国可视人体数据集的盆腔部分作为数据源,对盆腔中的重要器官进行分割处理,并在此基础上进行基于VRML的盆腔可视化以及基于Dextrobeam系统的虚拟手术仿真研究.结果 成功构建了基于虚拟现实的女性盆腔网络化模型和手术模型,可清晰显示各盆腔器官结构,并进行手术仿真操作.结论 虚拟现实技术的运用可有效地推动解剖教学与手术设计,为医学教育与培训提供逼真的模拟实践平台.     

数字人体的虚拟与仿真技术

本文首先介绍了数字人体虚拟与仿真技术的基本概念;然后讨论了数字人体虚拟现实系统的基本类型、技术系统的结构、虚拟VR-(IS技术特点与应用、数字人体虚拟系统的关键理论、虚拟系统模型;最后阐述了虚拟现实技术的发展、虚拟现实系统的类型和构成.