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.     

一种基于ARM的集中器的硬件实现

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Automatic inpainting by removing fence-like structures in RGBD images

Recent inpainting techniques usually require human interactions which are labor intensive and dependent on the user experiences. In this paper, we introduce an automatic inpainting technique to remove undesired fence-like structures from images. Specifically, the proposed technique works on the RGBD images which have recently become cheaper and easier to obtain using the Microsoft Kinect. The basic idea is to segment and remove the undesired fence-like structures by using both depth and color information, and then adapt an existing inpainting algorithm to fill the holes resulting from the structure removal. We found that it is difficult to achieve a satisfactory segmentation of such structures by only using the depth channel. In this paper, we use the depth information to help identify a set of foreground and background strokes, with which we apply a graph-cut algorithm on the color channels to obtain a more accurate segmentation for inpainting. We demonstrate the effectiveness of the proposed technique by experiments on a set of Kinect images.     

Leave-one-out cross-validation-based model selection for multi-input multi-output support vector machine

As an effective approach for multi-input multi-output regression estimation problems, a multi-dimensional support vector regression (SVR), named M-SVR, is generally capable of obtaining better predictions than applying a conventional support vector machine (SVM) independently for each output dimension. However, although there are many generalization error bounds for conventional SVMs, all of them cannot be directly applied to M-SVR. In this paper, a new leave-one-out (LOO) error estimate for M-SVR is derived firstly through a virtual LOO cross-validation procedure. This LOO error estimate can be straightway calculated once a training process ended with less computational complexity than traditional LOO method. Based on this LOO estimate, a new model selection methods for M-SVR based on multi-objective optimization strategy is further proposed in this paper. Experiments on toy noisy function regression and practical engineering data set, that is, dynamic load identification on cylinder vibration system, are both conducted, demonstrating comparable results of the proposed method in terms of generalization performance and computational cost.     

Enhanced Photocatalytic Hydrogen Evolution Over CaTi1−x Zr x O3 Composites Synthesized by Polymerized Complex Method

The solid solution of CaTi_1−x Zr _x O₃ (x = 0–0.15) was successfully synthesized by the polymerized complex (PC) method. This study has exhibited the advantage of the PC method to prepare a highly active CaTiO₃ compared with the conventional solid-state reaction (SSR) method. More importantly, further improvement in phase purity and large surface area was achieved by the doping of Zr⁴⁺, leading to remarkable enhancement of photocatalytic activities compared to pure CaTiO₃. The quantum yield for H₂ evolution over the most active photocatalyst, Pt (1.0 wt%)/CaTi_0.93Zr_0.07O₃, was 1.91% and 13.3% in photoreactions from pure water and aqueous ethanol solution, respectively for 0.1 g photocatalyst, which was about 3.3 and 2.5 times compared to that of PC-derived CaTiO₃.     

Study on the structure and properties of cyanate ester/bentonite nanocomposites

Cyanate ester (CE)/bentonite (BT) nanocomposites were prepared by melt blending of CE with NH₄⁺‐BT. The nanostructure of CE/BT nanocomposites was studied by X‐ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). It was found that partially intercalated and partially exfoliated structures coexisted in CE/BT nanocomposites containing 2.5 wt % BT with respect to that of bulk CE. Below 2.5 wt % BT content, a totally exfoliated and disordered structure was formed in the nanocomposites. The exfoliated BT enhanced the toughness of CE/BT nanocomposites. The impact strength showed a maximum of 7.1kJ/m² at 1 wt % BT, compared to 3.8kJ/m² of pure CE. Furthermore, results of thermogravimetric analysis (TGA) suggest that CE/BT nanocomposites have higher thermal stability. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 632–637, 2005     

MFE环氧乙烯基酯树脂固化性能的研究

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半圆电极对测量壁面处的湍流速度梯度脉动

壁面处湍流速度梯度脉动的测量对于深入了解壁面附近湍流的结构和传热、传质是很重要的.本文叙述了电化学法测量的原理,介绍了用一半圆电极对同时测量壁面上二维湍流速度梯度脉动的方法和测量结果.在直径0.194m的充分发展圆管湍流中,用碘和碘化钾溶液作为流动介质,半圆电极对直径为5×10~-4m,测得壁面处轴向和周向速度梯度的湍流脉动强度分别为0.3—0.33和0.11—0.12.     

用紫外吸收光谱法测定粗蒽中菲、蒽的含量

用紫外吸收光谱法同时测定粗蒽中菲、蒽的含量,结果表明,采用环已烷作溶剂,吸收波长分别为293nm和357nm,在0.004～0.04g/L范围内,菲、蒽符合线性关系。该方法操作简单、测定迅速、结果准确。     

焙烧硫酸铁铵催化合成季戊四醇双缩苯甲醛

以硫酸铁铵经600℃高温焙烧制得一类新型固体酸催化剂，该催化剂在合成季戊四醇双缩苯甲醛中具有较高的催化活性，其优化条件是：苯甲醛与季戊四醇物质的量比为2．0：1，催化剂用量为5％(以醇的质量为准)，回流温度83℃，反应时间2．5h，在此优化条件下，反应产率为87％。且催化剂容易制备，可连续使用。