利用欧氏距离变换Snake模型分割脊椎CT图像

在计算机虚拟脊椎矫正系统中,为模拟钢钉打入椎骨后相关脊椎骨产生位移和旋转,需要建立患者脊柱的三维模型。由于脊椎结构复杂,空间位置相互交错,造成了在靠近上下椎骨连接区域的CT图像中既有当前椎骨的图像,还有相邻其它椎骨的部分骨组织图像的状态,用传统的分割方法很难从脊柱的CT序列图像中分割出单个的椎骨。在传统Snake模型算法基础上,通过引进一种新的能量表达方法,改善了传统算法对具有复杂凹形轮廓物体分割效果差的缺点,在脊椎CT图像分割中取得了良好的效果。     

一种基于极大特征点的三维椎骨分割方法

椎骨的精确分割对于椎骨形态学研究和脊柱疾病的诊断和治疗有重要意义。通过 对正常人脊柱 CT 图序列的变化规律进行研究,提出了一种基于 CT 图像序列并利用椎骨面积 变化规律进行分割的椎骨分割算法。该方法通过对预先处理后的 CT 图像序列进行椎骨区域面 积统计,找出用于分割的显著极大特征点,并利用连续图像相似性筛选出椎骨实际分割点,最 后从序列中提取图像并进行三维重建。实验表明,该算法对正常人体腰椎和胸椎下部的椎骨 CT 图像序列有良好地分割效果,自动化程度较高。对脊柱形态学研究和矫正手术模拟有重要意义。       

基于MIMICS软件的脊柱三维重建算法研究

探讨基于MIMICS图像处理软件的脊柱三维重建算法。采集真实患者脊柱部位的CT影像数据,应用比利时医学交互式影像控制系统软件(Materialise's Interative Medical Image Control System, MIMICS)对影像数据进行图像处理、三维重建。采用基于灰度值的阈值分割、蒙版编辑、区域增长等算法编辑图像,最后计算三维蒙版获得脊柱的三维模型。结果:获得可编辑的stl格式的脊柱三维模型。应用MIMICS软件可基于脊柱CT影像数据高精度、准确的、快速建立三维模型,以用于临床的测量、手术规划、3D打印和数字骨科的有限元仿真。     

融合多注意力机制的脊椎图像分割方法

针对脊椎CT、MR图像分割模型分割性能不高的问题,基于U型网络提出了脊椎分割网络MAU-Net。首先引入坐标注意力模块,使网络准确捕获到空间位置信息,并嵌入到通道注意力中;然后提出基于Transformer的双支路通道交叉融合模块代替跳跃连接,进行多尺度特征融合;最后提出特征融合注意力模块,更好地融合Transformer与卷积解码器的语义差异。在脊柱侧凸CT数据集上,Dice达到0.929 6,IoU达到0.859 7。在公开MR数据集SpineSagT2Wdataset3上,与FCN相比,Dice提高14.46%。实验结果表明,MAU-Net能够有效减少椎骨误分割区域。     

深度学习在脊柱图像分割中的应用综述

深度学习算法在脊柱图像分割中具有学习和自适应能力强、对图像有非线性映射能力等优点,相较于传统分割方法,能更好地提取脊柱图像中的关键信息,并且抑制不相关信息,辅助医生准确定位病灶区域,实现精准、高效分割。从深度学习算法、脊柱疾病类型、图像类型、实验分割结果、性能评估指标等方面,对深度学习在脊柱图像分割中的应用现状进行归纳、总结并加以分析。介绍深度学习模型和脊柱图像分割的背景,从而引出深度学习在脊柱图像分割中的应用;介绍常见的几种脊柱疾病类型,阐述其在图像分割中的难点,并介绍脊柱图像分割中常用的公开数据集、图像分割的方法流程以及图像分割评价指标等要素;结合具体实验总结分析基于卷积神经网络模型、U型网络模型及其改进的模型在椎骨、椎间盘以及脊柱肿瘤图像分割中的应用进展;结合以往的实验结果和当前深度学习模型的研究进展,总结目前临床研究的局限性以及分割效果不足的原因,针对所存在的问题提出相应的解决方法,并对未来的研究和发展进行展望。     

基于Top-hat变换和角点检测的MRI脊椎分割算法

脊椎骨骼提取的精度直接影响到脊椎三维重建的效果。针对MR(Magnetic Resonance)脊椎图像成像不均匀的特点,提出一种利用Top-hat变换和角点检测结合的脊椎骨骼提取算法。首先利用Top-hat变换增强脊椎块与周围组织间的对比度,进而用大津法(OTSU)分割图像,获得脊柱的粗分割结果;然后使用改进的CSS(Curvature Scale Space)角点检测算法作用于粗分割图像,获取图像的有效角点;最后通过拟合角点,得到脊柱两侧的曲线,从而分割出脊柱区域。实验表明,该方法可以精确分割出脊椎部分,而且分割的结果可以应用于同一病人同序列的其他图像中,缩短了分割时间,具有较好的应用前景。     

一种用于三维重建的多视图前景目标自动分割算法

基于序列图像的三维物体重建之前,从图像中分割前景目标可节约大量时间。但传统的分割算法需要通过用户输入来确定前、后景,而基于图像的三维重建需要大量的图像,造成极大的人工浪费。为此提出一种用于三维重建的多视图前景目标自动分割算法。对每个图像进行颜色一致性和几何一致性分析,确定前景和后景大致区域,得到初始输入,并以此构建能量方程。使用Graph Cut算法求解方程得到粗略分割结果;使用Matting细化分割边界,得到高质量的分割结果;使用分割后图片重建出物体三维模型。实验结果表明,该算法可自动分割出多视图图像的前景目标,且具有极高的准确率和良好的边缘。将该算法用于三维重建的前期图像处理,可大大提高三维重建的速度。     

基于多尺度特征融合与注意力机制的脊柱CT图像分割

本文针对医学脊柱CT图像因骨密度不均匀、骨骼结构复杂或图像成像分辨率低等因素造成的分割精度较低的问题,提出一种基于卷积-反卷积神经网络的CT图像脊柱分割方法.通过引入多尺度残差模块及注意力机制改进U-Net网络,训练特征模型并进行测试.在真实数据集上的实验结果表明,该方法能有效提高CT图像中脊柱的分割精度及分割效率,Dice系数评估值为0.97,IOU系数评估值为0.94.     

结合改进分水岭和GVF的三维肝脏分割方法

三维肝脏分割是当前医学图像处理的热点问题,如何准确快速地从腹部CT序列中分割出肝脏是肝部病变诊断的基础。针对传统活动轮廓模型对轮廓线敏感、运算量大的问题,改进了传统轮廓线设置方法,并把算法扩展到三维。首先,在一幅腹部CT图片中采用改进的分水岭算法,按照灰度和纹理的相似性原则从一个种子块开始生长出整个肝脏,再用其边缘作为相邻CT序列的起始轮廓,用GVF算法从序列图片中分割出肝脏,重复该过程,直至分割出整个腹部序列图像的切片,进行三维重建。     

利用ITK和VTK集成实现三维医学图像的分割

ITK是一个对图像进行分割配准处理的开源的、基于对象的软件系统.它提供几乎所有的主流医学图像分割算法,能够解决虚拟手术中三维图像分割问题.讨论了ITK中区域生长和Level set分割算法,对CT序列图像进行分割,最后通过VTK对分割数据进行三维重建.利用ITK和VTK的功能集成,对医学图像三维组织体分割,并实现分割结果的可视化.实验证明这种方法能够满足医生对局部病变区域观测的要求,实时性良好.     

计算全息图的球面重现

该文研究重现于球面的计算全息图(CGH)的生成和重现。当用平面波照射傅里叶全息图时,所重现的图像一般显示在平面上。该文利用坐标变换方法实现显示于球面的二维图像的计算全息图的生成,并由所生成全息图得到原始图像,从而实现整个全息记录和重现过程的计算机模拟。二维图像重现于球面实际上产生了三维显示,因此该文所提到的方法在从计算全息图重现三维图像方面起到了重要的作用。     

基于3维提升可分离小波变换的图像水印方案

鲁棒水印技术通常被用于版权保护和所有权声明等目的。许多提出的水印方案通常把水印嵌入在变换域内,如2维的DFT域、DCT域和DWT域以及3维的DCT域、WT域。前3个域主要被用于2维的图像载体,而后2个域主要被用于3维的视频载体和3维的图像载体。在本文中,一种基于3维提升可分离小波(3-D SWT)的灰度图像水印方案被提出。首先,通过之字扫描把灰度图像分解为3维的图像序列,然后使用3-D SWT变换这些图像序列。同时通过相对熵理论证明了3-D SWT变换系数符合广义高斯分布。为了平衡鲁棒性和不可感知性,新的适用于3维的人类视觉模型被重构并用于调整水印的嵌入强度。在水印的检测方面,最优检测器实现水印的盲检测。实验表明本方案对各种攻击是强鲁棒的。     

Real-time advanced spinal surgery via visible patient model and augmented reality system

This paper presents an advanced augmented reality system for spinal surgery assistance, and develops entry-point guidance prior to vertebroplasty spinal surgery. Based on image-based marker detection and tracking, the proposed camera-projector system superimposes pre-operative 3-D images onto patients. The patients’ preoperative 3-D image model is registered by projecting it onto the patient such that the synthetic 3-D model merges with the real patient image, enabling the surgeon to see through the patients’ anatomy. The proposed method is much simpler than heavy and computationally challenging navigation systems, and also reduces radiation exposure. The system is experimentally tested on a preoperative 3D model, dummy patient model and animal cadaver model. The feasibility and accuracy of the proposed system is verified on three patients undergoing spinal surgery in the operating theater. The results of these clinical trials are extremely promising, with surgeons reporting favorably on the reduced time of finding a suitable entry point and reduced radiation dose to patients.     

Construction of wavelet decompositions for tomographic images

In tomography an image is reconstructed from its projections from different directions. In this paper we study the reconstruction of a tomographic image from the wavelet transform of its projections with a 1-D analyzing wavelet. We then show that it allows us to reconstruct a 2-D wavelet decomposition of the image. The properties of the generated 2-D analyzing wavelet are studied. When the 1-D analyzing wavelet is even, the 2-D analyzing wavelet is isotropic. The extension of this idea to directional wavelets is also presented. The wavelet transform obtained in this case is defined with respect to a scale parameter and a rotation angle. For illustration, results on simulated and x-ray computerized tomography medical images are presented.     

直接三维重建研究

本文提出了一个基于多结点插值样条和有限级数展开法的直接三维图像重建方法。该重建算法可以充分利用被重建物体的先验三维信息。对于减少稀疏系数矩阵的维数问题，本文也作了研究，实验结果证明了本方法是可行的。     

Wavelet-Based De-noising of Positron Emission Tomography Scans

A method to improve the signal-to-noise-ratio (SNR)of positron emission tomography (PET) scans is presented. A wavelet-based image decomposition technique decomposes an image into two parts, one which primarily contains the desired restored image and the other primarily the remaining unwanted portion of the image. Because the method is based on a texture extraction model that identifies the desired image in the space of bounded variation, these restorations are approximations of piecewise constant images, and are referred to as the cartoon part of the image. Here an approximation using a wavelet decomposition is used which allows solutions to be computed very efficiently. To process 3-D volume data a slice by slice approach in all three directions is adopted. Using a redundant discrete wavelet transform, 3-D restorations can be efficiently computed on standard desktop computers. The method is illustrated for PET images which have been reconstructed from simulated data using the expectation maximization algorithm. When post-processed by the presented wavelet decomposition they show a significant increase in SNR. It is concluded that the new wavelet based method can be used as an alternative to the well established de-noising of PET scans by smoothing with a Gaussian point spread function. In particular, if the volume data are reconstructed using the EM algorithm with a larger number of iterations than the number of iterations that would be used without post-processing, the 3-D images are sharper and show more detail. A MATLAB^® based graphical user interface is provided that allows easy exploration of the impact of parameter choices.     

基于改进二维图像重建算法的工业CT系统

基于对工业CT图像二维重建算法的研究，结合傅立叶切片理论和迭代算法，提出了修正的二维投影重建算法，大大减少了计算量，提高了抗噪性，得到了清晰、准确的断层图像，通过VC++设计开发了工业CT图像处理软件系统，使重建图像的质量得以提高，为试验数据提供了更方便和系统的管理，实现了工业CT图像缺陷判断的计算机自动化检测。     

A novel feature-based tracking approach to the detection, localization, and 3-D reconstruction of internal defects in hardwood logs using computer tomography

A novel feature-based tracking approach based on the Kalman filter is proposed for the detection, localization, and 3-D reconstruction of internal defects in hardwood logs from cross-sectional computer tomography (CT) images. The defects are simultaneously detected, classified, localized, and reconstructed in 3-D space, making the proposed scheme computationally much more efficient than existing methods where the defects are detected and localized independently in individual CT image slices and the 3-D reconstruction of the defects accomplished via correspondence analysis across the various CT image slices. Robust techniques for defect detection and classification are proposed. Defect class-specific tracking schemes based on the Kalman filter, B-spline contour approximation, and Snakes contour fitting are designed which use the geometric parameters of the defect contours as the tracking variables. Experimental results on cross-sectional CT images of hardwood logs from select species such as white ash, hard maple, and red oak are presented.     

基于三维图像处理的心肌细胞中Ca2+浓度研究

心肌细胞中Ca2+浓度的空间和时间分布,对于建立心肌细胞节律运动电路模型提供离子特性参数有很大帮助。提出了一种幼鼠心肌细胞中Ca2+浓度分布分析的新方法。对激光共聚焦显微镜（LSCM）采集的幼鼠心肌细胞序列图像进行图像处理、三维重建、细胞分割、距离变换,从细胞膜向内进行分层剥离,得到心肌细胞中Ca2+浓度的空间和时间分布。该方法极大地方便生物研究和医学诊断,基于三维距离变换研究Ca2+浓度时间空间分布的方法也可运用于类似的生物医学研究。     

3-D recovery of human motion by mobile stereo cameras

A method is described which recovers the 3-D shape of deformable objects, particularly human motions, from mobile stereo images. In the proposed technique, camera calibration is not required when taking images. Existing optical 3-D modeling systems must employ calibrated cameras that are set at fixed positions. This inevitably puts constraints on the range of the movement of an object. In the proposed method, multiple mobile cameras take images of a deformable object moving freely, and its 3-D model is reconstructed from the video image streams obtained. The advantages of the proposed method include the fact that the cameras employed are calibration-free, and that the image-taking cameras can move freely. The theory is described, and the performance is shown by an experiment on 3-D human motion modeling in an outdoor environment. The accuracy of the 3-D model obtained is evaluated and a discussion is given. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005