Augment low-field intra-operative MRI with preoperative MRI using a hybrid non-rigid registration method

Background

Preoperatively acquired diffusion tensor image (DTI) and blood oxygen level dependent (BOLD) have been proved to be effective in providing more anatomical and functional information; however, the brain deformation induced by brain shift and tumor resection severely impairs the correspondence between the image space and the patient space in image-guided neurosurgery.

Method

To address the brain deformation, we developed a hybrid non-rigid registration method to register high-field preoperative MRI with low-field intra-operative MRI in order to recover the deformation induced by brain shift and tumor resection. The registered DTI and BOLD are fused with low-field intra-operative MRI for image-guided neurosurgery.

Results

The proposed hybrid registration method was evaluated by comparing the landmarks predicted by the hybrid registration method with the landmarks identified in the low-field intra-operative MRI for 10 patients. The prediction error of the hybrid method is 1.92 ± 0.54 mm, and the compensation accuracy is 74.3 ± 5.0%. Compared to the landmarks far from the resection region, those near the resection region demonstrated a higher compensation accuracy (P-value = .003) although these landmarks had larger initial displacements.

Conclusions

The proposed hybrid registration method is able to bring preoperatively acquired BOLD and DTI into the operating room and compensate for the deformation to augment low-field intra-operative MRI with rich anatomical and functional information.     

New software developments for quality mesh generation and optimization from biomedical imaging data

In this paper we present a new software toolkit for generating and optimizing surface and volumetric meshes from three-dimensional (3D) biomedical imaging data, targeted at image-based finite element analysis of some biomedical activities in a single material domain. Our toolkit includes a series of geometric processing algorithms including surface re-meshing and quality-guaranteed tetrahedral mesh generation and optimization. All methods described have been encapsulated into a user-friendly graphical interface for easy manipulation and informative visualization of biomedical images and mesh models. Numerous examples are presented to demonstrate the effectiveness and efficiency of the described methods and toolkit.     

Personalized identification of abdominal wall hernia meshes on computed tomography

An abdominal wall hernia is a protrusion of the intestine through an opening or area of weakness in the abdominal wall. Correct pre-operative identification of abdominal wall hernia meshes could help surgeons adjust the surgical plan to meet the expected difficulty and morbidity of operating through or removing the previous mesh. First, we present herein for the first time the application of image analysis for automated identification of hernia meshes. Second, we discuss the novel development of a new entropy-based image texture feature using geostatistics and indicator kriging. Third, we seek to enhance the hernia mesh identification by combining the new texture feature with the gray-level co-occurrence matrix feature of the image. The two features can characterize complementary information of anatomic details of the abdominal hernia wall and its mesh on computed tomography. Experimental results have demonstrated the effectiveness of the proposed study. The new computational tool has potential for personalized mesh identification which can assist surgeons in the diagnosis and repair of complex abdominal wall hernias.     

基于Gabor多尺度空间的不变兴趣点检测

针对以往仿射不变兴趣点的特征尺度不能直接断定的问题, 提出一种基于Gabor多尺度空间的不变兴趣点检测算法。该算法主要包括三个步骤：应用Gabor滤波器组与图像卷积建立图像Gabor多尺度空间; 通过极大值准则检测兴趣点并直接断定特征尺度; 采用二阶矩矩阵描述兴趣点局部结构。实验结果表明, 相比较其他Hessian-Affine、MSER等算法, 该算法在图像模糊和JPEG压缩情况下可重复率和可匹配率均取得最好结果, 是一种能有效直接提取特征尺度的兴趣点检测算法。     

CFD modeling of pilot-scale pump-mixer: Single-phase head and power characteristics

The present work involves single-phase computational fluid dynamics (CFD) simulations of continuous flow pump-mixer employing top-shrouded Rushton turbines with trapezoidal blades. Baffle—impeller interaction has been modeled using sliding mesh and multiple reference frame approaches. Standard k-ε model has been used for turbulence modeling. Several CFD runs representing different combinations of geometric and process parameters have been carried out. Results of CFD simulations have been used to find out two macroscopic performance parameters of pump-mixer—power consumption and head generated by the impeller. The simulation results have been compared with the experimental data obtained on a pilot-scale setup. Good agreement between CFD predictions and experimental results is observed. In most cases, sliding mesh approach is found to perform better than multiple reference frame approach. Details from CFD simulations have been used to have an insight into the pumping action of the impeller.     

基于弹性网格混合特征的脱机手写维文识别

手写体维文识别技术的关键在于特征提取方法的选择。为探求一种可靠性高、可分性强的脱机手写维文特征提取方法,在分析现有方法的基础上,结合维吾尔文字词自身的特点,提出一种在局部特征上基于弹性网格区域笔划密度、方向分解特征,在全局特征上提取交叉点、环、弧形笔划、附加笔划、外围轮廓特征的混合特征提取方法。通过在IFN/ENIT标准数据库及自采样数据集的聚类分析实验,识别正确率分别达到85%、84.3%。结果表明,方法综合统计特征和结构特征提取的优点,具有较强的抗扰能力,可分性优于GSC法。     

In situ visualization of drop deformation,erosion, and breakup in high viscosity ratio polymeric systems under high shearing stress conditions

In this paper, deformation and breakup under simple shear of single molten polymer drops in a polymer matrix were investigated. Flow visualization was carried out in a Couette‐Flow apparatus under relatively high shear rates and temperatures up to 230°C. Drop/Matrix combinations were composed of polystyrene drops of 0.5–0.6 mm in diameter in polyethylene matrix, and ethylene–propylene copolymer drops of approximately the same size in polypropylene matrix. The deformation and breakup processes were studied under steady state and time‐dependent shearing conditions. Either for steady state or time‐dependant shearing conditions, drop elasticity generated at relatively high shear rates helped the drops to align perpendicular to the flow direction, i.e., parallel to vorticity axis. Also, the most striking non‐Newtonian effects for the high viscosity ratio systems were the surface erosion and the drop splitting mechanisms. The particles eroded off the main droplet surface were very fine, in the range of 10–50 μm, and led to a significant reduction in main drop size before its final breakup. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 2582–2591, 2006     

基于GM（1，1）和线性回归模型在印刷包衬压缩变形中的数据预测研究

运用线性回归对预测数据进行分析,剔除异常数据,用GM（1,1）模型进行预测,有效降低了数据相对误差,提高了预测数据的精度。选用印刷包衬压缩变形的压缩变形量值,用线性回归进行数据分析并剔除异常数据后用GM（1,1）进行预测,使得预测数据具有更高的准确性和适应性。实验及仿真结果表明,经过前期数据分析整理后的灰色预测模型,其预测期望值远优于单纯的回归模型和GM（1,1）模型。     

基于重标极差法和神经网络的隧道变形趋势判断

为准确、科学及全面地对隧道变形进行趋势判断和预测分析,将隧道的变形过程划分为中期阶段和长期阶段,利用R/S分析对其位移序列和速率序列进行趋势判断研究,再利用PSO-BP神经网络对各阶段的变形进行预测,将预测结果与R/S分析结果进行对比,验证两者的一致性。利用两个工程实例进行检验,得出各序列的Hurst指数均大于0.5,说明各序列均具有持续变形的长期性,且位移序列的趋势性均大于速率序列的趋势性;同时,变形预测结果也显示隧道后期变形将持续增加,验证了R/S分析的准确性。     

地铁深基坑分区开挖监测及数值模拟

对于狭长的地铁车站深基坑,围护结构区域内岩土体在实际施工时经常采用分区的方式进行开挖。为了分析分区开挖工况下深基坑的稳定性规律,选取合肥市某地铁车站深基坑作为研究对象,运用有限差分软件对实际工程进行数值模拟。比较模型计算结果与现场实测结果,得到了基坑分区开挖过程中围护结构侧向位移、横向支撑轴力,以及地表沉降的变化规律。研究结果表明:现场实测结果与数值模拟结果较为接近且均小于规范限值,数值模型能较好地反映基坑变形特性;随着开挖的进行,围护结构变形出现明显的"鼓肚"状,最大侧向位移点向基坑中段移动;支撑轴力前期发展较快,之后趋于平稳;邻近地表沉降呈现为凹槽状,基坑开挖影响范围约在40 m内。研究结果可为其他类似工程设计或施工决策提供参考。