B样条小波在提取脑电癫痫棘波中的应用

脑电癫痫特征波自动提取对于患者的诊断，以及减轻医生的繁重劳动力都具有重要意义。采用B样条小波对信号突变点灵敏检测的优良特性来进行癫痫棘波提取，取得了比较好的效果。     

带形状参数的指数均匀B样条模型

本文给出了k(k≥2)阶带形状参数指数多项式的均匀B样条模型.该类模型具有很多与B样条模型相同的性质,并且具有一个可调节的形状参数.由该模型构造的曲线,通过改变形状参数的取值,可以调整曲线接近其控制多边形的程度.该模型可以应用于CAD/CAM领域,作为几何造型一种新的有效模型.     

应用B-样条技术重建颅颌骨的三维形态

目的:本研究试图找到最能表达颅颌骨特征的特征点,并尝试运用计算机图形学的技术拟合生成颅颌骨的 曲线和曲面图。方法:头颅骨标本经CT断层扫描后获得三维数据,经过筛选提取出76个特征点,应用B-样条技 术拟合生成颅颌骨的曲线和曲面图。结果:生成的图像可视性强,定性地描述了颅颌骨三维形态。结论:根据特 征点重构颅颌骨的三维可视图是可行的,为下一步直接从X线定位片获得颅颌骨的特征点并重建颅颌骨的三维形 态提供了依据。     

Bidirectional elastic image registration using B-spline affine transformation

A registration scheme termed as B-spline affine transformation (BSAT) is presented in this study to elastically align two images. We define an affine transformation instead of the traditional translation at each control point. Mathematically, BSAT is a generalized form of the affine transformation and the traditional B-spline transformation (BST). In order to improve the performance of the iterative closest point (ICP) method in registering two homologous shapes but with large deformation, a bidirectional instead of the traditional unidirectional objective/cost function is proposed. In implementation, the objective function is formulated as a sparse linear equation problem, and a sub-division strategy is used to achieve a reasonable efficiency in registration. The performance of the developed scheme was assessed using both two-dimensional (2D) synthesized dataset and three-dimensional (3D) volumetric computed tomography (CT) data. Our experiments showed that the proposed B-spline affine model could obtain reasonable registration accuracy.     

基于三次B样条小波的结肠镜图像暗区中心点估计的研究

提出用三次B样条小波的多尺度边缘检测算子对结肠镜图像的亮度分量Ⅰ进行边缘提取,找出所有类似圆弧状边缘线的圆心经加权求和后得到内窥镜图像暗区真正的中心点,弥补了传统方法中因暗区不明显而无法确定中心点的不足,并用所求的中心点来引导肠镜前端导管,起到导航的作用。     

Real-time 3D interactive segmentation of echocardiographic data through user-based deformation of B-spline explicit active surfaces

Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate morphological or functional properties of given anatomical targets. While automatic processing is highly desirable, image segmentation remains to date a supervised process in daily clinical practice. Indeed, challenging data often requires user interaction to capture the required level of anatomical detail. To optimize the analysis of 3D images, the user should be able to efficiently interact with the result of any segmentation algorithm to correct any possible disagreement. Building on a previously developed real-time 3D segmentation algorithm, we propose in the present work an extension towards an interactive application where user information can be used online to steer the segmentation result. This enables a synergistic collaboration between the operator and the underlying segmentation algorithm, thus contributing to higher segmentation accuracy, while keeping total analysis time competitive. To this end, we formalize the user interaction paradigm using a geometrical approach, where the user input is mapped to a non-cartesian space while this information is used to drive the boundary towards the position provided by the user. Additionally, we propose a shape regularization term which improves the interaction with the segmented surface, thereby making the interactive segmentation process less cumbersome. The resulting algorithm offers competitive performance both in terms of segmentation accuracy, as well as in terms of total analysis time. This contributes to a more efficient use of the existing segmentation tools in daily clinical practice. Furthermore, it compares favorably to state-of-the-art interactive segmentation software based on a 3D livewire-based algorithm.     

CT/MRI混合配准方法及其在放疗计划系统中的应用

旨在研究放疗中图像配准方法,特别是针对放疗中常用的CT、MRI,提出基于混合框架的配准方法,该方法主要包 括两个方面:（1）采用掩膜（Mask）提取感兴趣区域、形态学运算等图像处理方法以及CPU多线程并行技术,大幅度提高配 准速度;（2）采用由全局到局部的混合配准策略,首先利用基于仿射变换的刚性配准整体配准,以防止图像间偏差过大,在 此基础上针对感兴趣区域采用B样条弹性配准,调整局部形变。通过实验表明,采用预处理及加速策略的刚性配准,在保 持其精度的情况下,提速比可达10倍,测试结果已达到临床需求;此外,采用基于GPU加速的混合配准策略,其配准速度 提至约4 min。     

A regression spline model for developmental toxicity data.

Observed dose-response patterns of data from several developmental toxicity experiments appear to be nonlinear and should be characterized by an appropriate model to adequately fit this observed pattern. Information from these animal studies of ambient substances that are noncarcinogenic, yet potentially toxic, to humans is used by federal protection agencies (Environmental Protection Agency, Occupational Safety and Health Administration, Food and Drug Administration) to determine safe exposure levels, such as no observed adverse effects level and benchmark dose. We have developed a flexible regression linear B-spline model for application to developmental toxicity dose-response data from animal studies of these noncarcinogens. We apply our model to data from two CD-1 mice studies of the National Toxicology Program; the observed dose-response pattern from both appears nonlinear: (1) experiment of 131 pregnant mice allocated over five exposure levels (0, 0.025, 0.05, 0.10, and 0.15% diet) of diethylhexyl phthalate and (2) experiment of 111 pregnant mice exposed to five levels (0, 62.5, 125, 250, and 500 mg/kg/day) of diethylene glycol dimethyl ether. In each study, we measure litter response as the proportion of adversely affected fetuses. Upon applying our B-spline model to the data from both studies, we predict nonlinear dose-response, with improvement over the more typical logistic dose-response model in each of the two studies.     

超声图像中基于经验模态分解自动提取内-中膜厚度

目的为改善传统人工标记测量血管内-中膜厚度(IMT)的准确性和稳定性,提出基于图像分割技术的经验模态分解(EMD)改进算法。方法采用EMD改进算法去噪,根据血管壁的特点,在其中的极值点插值步骤使用非均匀的二维B样条函数,在水平和垂直方向上控制网格的密度不同,分别满足不同的分辨精度和平滑程度要求,改进了原始的二维EMD算法;然后通过K均值方法从图像中分离出血管腔、血管壁和其他组织,使用数学形态学算法逐步得到最终的内-中膜组织分割结果。结果改进EMD算法取得了较好的重建和滤波效果,有效克服了超声图像的强噪声和低分辨力对图像分割的限制,整个算法分割比较准确,算法复杂度相对较小。结论改进EMD算法是在超声图像中自动提取内-中膜的较有潜力的方法,能有效去除超声噪声,同时保留条纹结构的细节和边缘信息,有望于其他强噪声环境下提取条纹结构。     

Constrained non-rigid registration for use in image-guided adaptive radiotherapy

A constrained non-rigid registration (CNRR) algorithm for use in prostate image-guided adaptive radiotherapy is presented in a coherent mathematical framework. The registration algorithm is based on a global rigid transformation combined with a series of local injective non-rigid multi-resolution cubic B-spline Free Form Deformation (FFD) transformations. The control points of the FFD are used to non-rigidly constrain the transformation to the prostate, rectum, and bladder. As well, the control points are used to rigidly constrain the transformation to the estimated position of the pelvis, left femur, and right femur. The algorithm was tested with both 3D conformal radiotherapy (3DCRT) and intensity-modulated radiotherapy (IMRT) dose plan data sets. The 3DCRT dose plan set consisted of 10 fan-beam CT (FBCT) treatment-day images acquired from four different patients. The IMRT dose plan set consisted of 32 cone-beam CT (CBCT) treatment-day images acquired from 4 different patients. The CNRR was tested with different combinations of anatomical constraints and each test significantly outperformed both rigid and non-rigid registration at aligning constrained bones and critical organs. The CNRR results were used to adapt the dose plans to account for patient positioning errors as well as inter-day bone motion and intrinsic organ deformation. Each adapted dose plan improved performance by lowering radiation distribution to the rectum and bladder while increasing or maintaining radiation distribution to the prostate.