医学图像三维重建模型的剖切与立体视窗剪裁

基于医学图像三维重建是医学图像可视化和医疗放射治疗放射治疗规划的基础，在人体多组织器官的重建及可视化中，为地重建组织的截面形状进行分析，观察内部组织的结构及空间位置，需要对重建模型施以剖切及对外表模型进行立体剪裁，针对医学图像重建的表面几何模型，提出对模型进行剖切及开窗的一种方法，该方法用剖切面或剖切体对重建模型施以剖切，在剖切面上生成边序列及顶点序列，由此边序列和顶点序列生成封闭的边界轮廓，确定各轮廓的包含关系，对封闭轮廓包围面区域进行Delaunay三角部分，得到完整的剖切后的表面模型，模型被剖切或开窗，可以方便地看到内部的组织，便于观察和诊断。     

基于三维表面模型的任意切割算法*

通过对三维表面模型进行切割,人们可以方便地观察物体的内部结构。针对三维表面模型,提出了一种任意切割算法。任意切割过程首先是交互生成切割曲线,生成切割面;然后通过切割面对表面模型进行切割,在切割面上生成交线序列;再由交线序列与切割面边界生成封闭的边界轮廓,确定各边界轮廓间的包含关系;最后对边界轮廓包围的截面区域进行Delaunay三角剖分并着色,得到完整的剖面。实验结果证明了该算法的有效性和可行性。     

基于标志点的虚拟剖切面重建

针对现有医学图像技术中三维模型的虚拟剖切面重建算法功能单一、不能完成复杂路径剖切面展开的缺点,提出基于空间任意标志点的剖切面重建算法。该算法可以沿三维空间中的任意路径完成虚拟剖切面展开,包括确定标志点、拟合虚拟剖切路径、重建剖切面3个部分。实验证明该算法可以得到稳定优异的重建图像,精确度较高。     

医学图像三维表面模型切割算法

为了在计算机辅助虚拟手术中对重建的三维模型进行切割,提出一种医学图像三维表面模型切割算法,利用鼠标在模型上画任意形状的封闭曲线来模拟手术刀的切割轨迹,从而实现手术过程中的任意交互切割。仿真实验结果表明,该算法具有良好的交互性,能够获得较好的虚拟切割效果,具有一定应用价值。     

基于B-Rep实体模型的IGES转换为STL

提出一种将IGES文件格式转换成STL文件格式的算法.根据IGES文件内容重构几何实体信息及其拓扑关系;将几何实体的三维曲面贴合为二维平面,并将曲面上的轮廓边界转换到平面上,在二维空间中根据封闭轮廓边界裁剪曲面;根据曲面上保留的特征点及轮廓边界上的顶点信息对面进行符合STL模型一致性规则的三角剖分,生成合法的STL文件.该算法的核心是保证面与面接合处的三角化的正确性.最后介绍了该算法的转换实例.     

基于顶点重要度的保形网格简化方法研究

为解决许多网格简化方法不能很好地保持模型的重要几何特征问题,提出基于顶点重要度和三角剖分的边折叠简化算法.算法通过特征因子加权顶点重要度作为边的折叠代价,定义法向量夹角因子,控制边的折叠顺序;在折叠过程中对边界特征区域进行冻结处理,以保持模型总体轮廓特征;采用边中点折叠和边邻域网格重建方法完成折叠操作.实验结果表明,模型在大规模简化后,该方法能较好地保持模型的几何特征.     

三维重建表面任意切面图像提取及映射有效方法*

针对三维重建表面模型的任意切面纹理显示,分为3D纹理采样和切面纹理映射两阶段。前者通过模型包围盒及模型横断面轮廓定位纹理部位并去掉图像背景,经采样形成多精度3D纹理;后者先计算剖切平面和模型及纹理空间中包围盒交面,然后利用向量叠加原理及立方体线性插值方法快速提取纹理空间的交面图像,经Alpha测试后映射到模型空间相应切面上,形成具有切面纹理的剖切模型。实验表明,该方法克服了面绘制技术不能体现内部数据的缺点,有效地提高了大数据量模型任意剖切面纹理绘制速度。     

一种基于图像序列轮廓三维重建表面的任意切面图像提取及纹理映射有效方法

针对三维重建后的表面模型的任意剖切,首先通过对象的序列轮廓去掉图像背景,然后计算其模型及图像空间中包围盒和剖切平面的交面,利用向量叠加原理及立方体线性插值方法快速提取交面图像,经Alpha测试后映射到模型空间中相应切面上.实验表明,该方法在克服面绘制技术不能体现内部数据缺点的同时,有效地提高了模型任意剖切时剖面纹理绘制速度.     

基于VTK的三维医学图像虚拟切片提取

目前大多数医学影像设备,如CT、MRI、超声等所产生的图像序列往往必须沿着某一固定方向,但这通常不能满足临床上多方位、任意角度诊查的需要。针对该问题,提出了一种三维医学图像的任意角度虚拟切片提取方法。在Visual C++平台下,结合可视化工具包VTK,对DICOM格式的CT图像序列进行三维重建,通过设置虚拟切面的法向量和内点来对重建后的三维物体进行切割并获得虚拟切片信息,在切割的同时可以同步显示出虚拟切片图像。通过简单的鼠标操作可以生成任意角度、任意部位的虚拟切片图像,并能对切割平面及虚拟切片图像进行移     

基于退化多边形求交的多面体虚拟壳模型重构

三维模型的重建和表示是计算机图形和计算机视觉中一个重要的领域,其广泛应用于自动识别,工业自动化设计以及虚拟场景的重建。文中实现一个从照片序列重建三维物体多面体模型的系统,使用由轮廓恢复形体(SFS),通过经由轮廓光锥相交得到包围物体的虚拟壳。在系统中采用的共极线几何和增量运算把所有的三维的相交计算投射到二维平面的退化多边形求交来降低相交计算的复杂度。与传统多面体虚拟壳重构相比,算法有以下几点改进:在图像平面以退化多边形组织投影锥体和物体轮廓的交集,把任意锥面与物体轮廓的交集归一到一个退化多边形;基于退化多边形的二维平面上多边形快速相交算法。通过这些改进可以减少虚拟壳的生成时间并有助于实时绘制的实现。     

Piecewise-planar reconstruction using two views

The article describes a reconstruction pipeline that generates piecewise-planar models of man-made environments using two calibrated views. The 3D space is sampled by a set of virtual cut planes that intersect the baseline of the stereo rig and implicitly define possible pixel correspondences across views. The likelihood of these correspondences being true matches is measured using signal symmetry analysis [1], which enables to obtain profile contours of the 3D scene that become lines whenever the virtual cut planes intersect planar surfaces. The detection and estimation of these lines cuts is formulated as a global optimization problem over the symmetry matching cost, and pairs of reconstructed lines are used to generate plane hypotheses that serve as input to PEARL clustering [2]. The PEARL algorithm alternates between a discrete optimization step, which merges planar surface hypotheses and discards detections with poor support, and a continuous optimization step, which refines the plane poses taking into account surface slant. The pipeline outputs an accurate semi-dense Piecewise-Planar Reconstruction of the 3D scene. In addition, the input images can be segmented into piecewise-planar regions using a standard labeling formulation for assigning pixels to plane detections. Extensive experiments with both indoor and outdoor stereo pairs show significant improvements over state-of-the-art methods with respect to accuracy and robustness.     

Velocity-Guided Tracking of Deformable Contours in Three Dimensional Space

This paper presents a 3D active contour model for boundary detection and tracking of non-rigid objects, which applies stereo vision and motion analysis to the class of energy-minimizing deformable contour models, known as snakes. The proposed contour evolves in three-dimensional space in reaction to a 3D potential function, which is derived by projecting the contour onto the 2D stereo images. The potential function is augmented by a kinetic term, which is related to the velocity field along the contour. This term is used to guide the inter-image contour displacement. The incorporation of inter-frame velocity estimates in the tracking algorithm is especially important for contours which evolve in 3D space, where the added freedom of motion can easily result in loss of tracking. The proposed scheme incorporates local velocity information seamlessly in the snake model, with little computational overhead, and does not require exogenous computation of the optical flow or related quantities in each image. The resulting algorithm is shown to provide good tracking performance with only one iteration per frame, which provides a considerable advantage for real time operation.     

Acquiring a complete 3D model from specular motion under theillumination of circular-shaped light sources

We recover 3D models of objects with specular surfaces. An object is rotated and its continuous images are taken. Circular-shaped light sources that generate conic rays are used to illuminate the rotating object in such a way that highlighted stripes can be observed on most of the specular surfaces. Surface shapes can be computed from the motions of highlights in the continuous images; either specular motion stereo or single specular trace mode can be used. When the lights are properly set, each point on the object can be highlighted during the rotation. The shape for each rotation plane is measured independently using its corresponding epipolar plane image. A 3D shape model is subsequently reconstructed by combining shapes at different rotation planes. Computing a shape is simple and requires only the motion of highlight on each rotation plane. The novelty of this paper is the complete modeling of a general type of specular objects that has not been accomplished before     

基于倾斜摄影的三维模型单体化方法研究

利用三角面片的可分割性质,解决倾斜摄影数据的三维模型可分离单体化问题。该方法首先绘制切割多边形,确定单体化模型边界,然后使用包围盒方法进行求交检测,获得需要切割的三角面片。之后计算求交检测所得三角面片与切割多边形的交点,然后详细分析切割多边形与三角面片相交时的不同相交情形,并针对不同的相交情形采用不同的切割方法。最后,对相交区域三角面片进行裁切并重构,再纹理重构并实现多细节分层后得到分离的单体化模型。实验结果表明,该方法可有效实现倾斜摄影三维模型的分离单体化。     

3D model reconstruction with common hand-held cameras

A 3D model reconstruction workflow with hand-held cameras is developed. The exterior and interior orientation models combined with the state-of-the-art structure from motion and multi-view stereo techniques are applied to extract dense point cloud and reconstruct 3D model from digital images. An overview of the presented 3D model reconstruction methods is given. The whole procedure including tie point extraction, relative orientation, bundle block adjustment, dense point production and 3D model reconstruction is all reviewed in brief. Among them, we focus on bundle block adjustment procedure; the mathematical and technical details of bundle block adjustment are introduced and discussed. Finally, four scenes of images collected by hand-held cameras are tested in this paper. The preliminary results have shown that sub-pixel (<1 pixel) accuracy can be achieved with the proposed exterior–interior orientation models and satisfactory 3D models can be reconstructed using images collected by hand-held cameras. This work can be applied in indoor navigation, crime scene reconstruction, heritage reservation and other applications in geosciences.     

Anatomical structure modeling from medical images

Some clinical applications, such as surgical planning, require volumetric models of anatomical structures represented as a set of tetrahedra. A practical method of constructing anatomical models from medical images is presented. The method starts with a set of contours segmented from the medical images by a clinician and produces a model that has high fidelity with the contours. Unlike most modeling methods, the contours are not restricted to lie on parallel planes. The main steps are a 3D Delaunay tetrahedralization, culling of non-object tetrahedra, and refinement of the tetrahedral mesh. The result is a high-quality set of tetrahedra whose surface points are guaranteed to match the original contours. The key is to use the distance map and bit volume structures that were created along with the contours. The method is demonstrated on computed tomography, MRI and 3D ultrasound data. Models of 170,000 tetrahedra are constructed on a standard workstation in approximately 10s. A comparison with related methods is also provided.     

Omnidirectional texturing based on robust 3D registration through Euclidean reconstruction from two spherical images

We propose a semi-automatic omnidirectional texturing method that maps a spherical image onto a dense 3D model obtained by a range sensor. For accurate texturing, accurate estimation of the extrinsic parameters is inevitable. In order to estimate these parameters, we propose a robust 3D registration-based method between a dense range data set and a sparse spherical image stereo data set. For measuring the distances between the two data sets, we introduce generalized distances taking account of 3D error distributions of the stereo data. To reconstruct 3D models by images, we use two spherical images taken at arbitrary positions in arbitrary poses. Then, we propose a novel rectification method for spherical images that is derived from E matrix and facilitates the estimation of the disparities. The experimental results show that the proposed method can map the spherical image onto the dense 3D models effectively and accurately.