共查询到20条相似文献,搜索用时 31 毫秒
1.
In the process of sudden natural disasters (such as earthquake or typhoon), the active mass damper (AMD) system can reduce the structural vibration response optimally, which serves as a frequently applied but less mature vibration-reducing technology in wind and earthquake resistance of high-rise buildings. As the core of this technology, the selection of control algorithm is extremely challenging due to the uncertainty of structural parameters and the randomness of external loads. It is not necessary for the Model Reference Adaptive Control (MRAC) based on the Minimal Controller Synthesis (MCS) algorithm to know in advance the structural parameters, which produces special advantages in conditions of real-time change of system parameters, uncertain external disturbance, and the nonlinear dynamic system. This paper studies the application of the MRAC into the AMD active control system. The principle of MRAC algorithm is recommended and the dynamic model and the motion differential equation of AMD system based on MRAC is established under seismic excitation. The simulation analysis for linear and nonlinear structures when the structural stiffness is degenerated is performed under AMD system controlled by MRAC algorithm. To verify the validity of the MRAC over the AMD system, experimental tests are carried out on a linear structure and a structure with variable stiffness with the AMD system under seismic excitation on the shake table, and the experimental results are compared with those of the traditional pole assignment control algorithm. 相似文献
2.
3.
Magnetic Resonance Imaging (MRI) provides excellent soft tissue contrast with one significant limitation of slow data acquisition. Dynamic Contrast Enhanced MRI (DCE-MRI) is one of the widely employed techniques to estimate tumor tissue physiological parameters using contrast agents. DCE-MRI data acquisition and reconstruction requires high spatiotemporal resolution, especially during the post-contrast phase. The region of Interest Compressed Sensing (ROICS) is based on Compressed Sensing (CS) framework and works on the hypothesis that limiting CS to an ROI can achieve superior CS performance. In this work, ROICS has been demonstrated on breast DCE-MRI data at chosen acceleration factors and the results are compared with conventional CS implementation. Normalized Root Mean Square Error (NRMSE) was calculated to compare ROICS with CS quantitatively. CS and ROICS reconstructed images were used to compare Ktrans and ve values derived using standard Tofts Model (TM). This also validated the superior performance of ROICS over conventional CS. ROICS generated Concentration Time Curves (CTC's) at chosen acceleration factors follow similar trend as the ground truth data as compared to CS. Both qualitative and quantitative analyses show that ROICS outperforms CS particularly at acceleration factors of 5× and above. 相似文献
4.
Rajaraman S Rodriguez JJ Graff C Altbach MI Dragovich T Sirlin CB Korn RL Raghunand N 《Magnetic resonance imaging》2011,29(5):668-682
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly in use as an investigational biomarker of response in cancer clinical studies. Proper registration of images acquired at different time points is essential for deriving diagnostic information from quantitative pharmacokinetic analysis of these data. Motion artifacts in the presence of time-varying intensity due to contrast enhancement make this registration problem challenging. DCE-MRI of chest and abdominal lesions is typically performed during sequential breath-holds, which introduces misregistration due to inconsistent diaphragm positions and also places constraints on temporal resolution vis-à-vis free-breathing. In this work, we have employed a computer-generated DCE-MRI phantom to compare the performance of two published methods, Progressive Principal Component Registration and Pharmacokinetic Model-Driven Registration, with Sequential Elastic Registration (SER) to register adjacent time-sample images using a published general-purpose elastic registration algorithm. In all three methods, a 3D rigid-body registration scheme with a mutual information similarity measure was used as a preprocessing step. The DCE-MRI phantom images were mathematically deformed to simulate misregistration, which was corrected using the three schemes. All three schemes were comparably successful in registering large regions of interest (ROIs) such as muscle, liver, and spleen. SER was superior in retaining tumor volume and shape, and in registering smaller but important ROIs such as tumor core and tumor rim. The performance of SER on clinical DCE-MRI data sets is also presented. 相似文献
5.
PurposeDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) measures changes in the concentration of an administered contrast agent to quantitatively evaluate blood circulation in a tumor or normal tissues. This method uses a pharmacokinetic analysis based on the time course of a reference region, such as muscle, rather than arterial input function. However, it is difficult to manually define a homogeneous reference region. In the present study, we developed a method for automatic extraction of the reference region using a clustering algorithm based on a time course pattern for DCE-MRI studies of patients with prostate cancer.MethodsTwo feature values related to the shape of the time course were extracted from the time course of all voxels in the DCE-MRI images. Each voxel value of T1-weighted images acquired before administration were also added as anatomical data. Using this three-dimensional feature vector, all voxels were segmented into five clusters by the Gaussian mixture model, and one of these clusters that included the gluteus muscle was selected as the reference region.ResultsEach region of arterial vessel, muscle, and fat was segmented as a different cluster from the tumor and normal tissues in the prostate. In the extracted reference region, other tissue elements including scattered fat and blood vessels were removed from the muscle region.ConclusionsOur proposed method can automatically extract the reference region using the clustering algorithm with three types of features based on the time course pattern and anatomical data. This method may be useful for evaluating tumor circulatory function in DCE-MRI studies. 相似文献
6.
A nonrigid registration algorithm for longitudinal breast MR images and the analysis of breast tumor response 总被引:1,自引:0,他引:1
Xia Li Benoit M. Dawant E. Brian Welch A. Bapsi Chakravarthy Darla Freehardt Ingrid Mayer Mark Kelley Ingrid Meszoely John C. Gore Thomas E. Yankeelov 《Magnetic resonance imaging》2009,27(9):1258-1270
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can estimate parameters relating to blood flow and tissue volume fractions and therefore may be used to characterize the response of breast tumors to treatment. To assess treatment response, values of these DCE-MRI parameters are observed at different time points during the course of treatment. We propose a method whereby DCE-MRI data sets obtained in separate imaging sessions can be co-registered to a common image space, thereby retaining spatial information so that serial DCE-MRI parameter maps can be compared on a voxel-by-voxel basis. In performing inter-session breast registration, one must account for patient repositioning and breast deformation, as well as changes in tumor shape and volume relative to other imaging sessions. One challenge is to optimally register the normal tissues while simultaneously preventing tumor distortion. We accomplish this by extending the adaptive bases algorithm through adding a tumor-volume preserving constraint in the cost function. We also propose a novel method to generate the simulated breast magnetic resonance (MR) images, which can be used to evaluate the proposed registration algorithm quantitatively. The proposed nonrigid registration algorithm is applied to both simulated and real longitudinal 3D high resolution MR images and the obtained transformations are then applied to lower resolution physiological parameter maps obtained via DCE-MRI. The registration results demonstrate the proposed algorithm can successfully register breast MR images acquired at different time points and allow for analysis of the registered parameter maps. 相似文献
7.
Julio Cárdenas-Rodríguez Christine M. Howison Terry O. Matsunaga Mark D. Pagel 《Magnetic resonance imaging》2013
Dynamic Contrast Enhancement (DCE) MRI has been used to measure the kinetic transport constant, Ktrans, which is used to assess tumor angiogenesis and the effects of anti-angiogenic therapies. Standard DCE MRI methods must measure the pharmacokinetics of a contrast agent in the blood stream, known as the Arterial Input Function (AIF), which is then used as a reference for the pharmacokinetics of the agent in tumor tissue. However, the AIF is difficult to measure in pre-clinical tumor models and in patients. Moreover the AIF is dependent on the Fahraeus effect that causes a highly variable hematocrit (Hct) in tumor microvasculature, leading to erroneous estimates of Ktrans. To overcome these problems, we have developed the Reference Agent Model (RAM) for DCE MRI analyses, which determines the relative Ktrans of two contrast agents that are simultaneously co-injected and detected in the same tissue during a single DCE-MRI session. The RAM obviates the need to monitor the AIF because one contrast agent effectively serves as an internal reference in the tumor tissue for the other agent, and it also eliminates the systematic errors in the estimated Ktrans caused by assuming an erroneous Hct. Simulations demonstrated that the RAM can accurately and precisely estimate the relative Ktrans (RKtrans) of two agents. To experimentally evaluate the utility of RAM for analyzing DCE MRI results, we optimized a previously reported multiecho 19F MRI method to detect two perfluorinated contrast agents that were co-injected during a single in vivo study and selectively detected in the same tumor location. The results demonstrated that RAM determined RKtrans with excellent accuracy and precision. 相似文献
8.
为提高基于动态增强磁共振成像(DCE-MRI)的计算机辅助(CAD)方法对乳腺病变良恶性鉴别的精度,本文基于多模态特征融合,提出一种联合非对称卷积和超轻子空间注意模块的卷积神经网络AC_Ulsam_CNN.首先,采用迁移学习方法预训练模型,筛选出对乳腺病变良恶性鉴别最为有效的DCE-MRI扫描时序.而后,基于最优扫描时序图像,搭建基于AC_Ulsam_CNN网络的模型,以增强分类模型的特征表达能力和鲁棒性.最后,将影像特征与乳腺影像数据报告和数据系统(BI-RADS)分级、表观扩散系数(ADC)和时间-信号强度曲线(TIC)类型等多模态信息进行特征融合,以进一步提高模型对病灶的预测性能.采用五折交叉验证方法进行模型验证,本文方法获得了0.826的准确率(ACC)和0.877的受试者工作曲线下面积(AUC).这表明该算法在小样本量数据下可较好区分乳腺病变的良恶性,而基于多模态数据的融合模型也进一步丰富了特征信息,从而提高病灶的检出精度,为乳腺病灶良恶性的自动鉴别诊断提供了新方法. 相似文献
9.
提出基于细分和数值积分思想的一种离散的守恒重映方法——质点重映方法.密度分布可采用一阶精度的分片常数分布,或二阶精度的分片线性分布.分片线性密度分布函数采用面平均方法构造.重映过程中,借助四边形辅助网格,实现了交错网格节点量的重映.质点重映方法既适用于结构网格,也适用于非结构网格,且不要求新旧网格之间一一对应.数值结果表明,一阶精度重映算法健壮性好,但会产生较大的扩散效应;二阶精度重映算法可较好地保持密度分布的特性,但存在单调性问题.为改善二阶精度重映方法单调性,将结构网格质量守恒调整算法推广到非结构网格上,以限制新网格的质量密度.给出了一些重映的例子,并进行了误差分析. 相似文献
10.
Han S Paulsen JL Zhu G Song Y Chun S Cho G Ackerstaff E Koutcher JA Cho H 《Magnetic resonance imaging》2012,30(6):741-752
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides critical information regarding tumor perfusion and permeability by injecting a T(1) contrast agent, such as Gd-DTPA, and making a time-resolved measurement of signal increase. Both temporal and spatial resolutions are required to be high to achieve an accurate and reproducible estimation of tumor perfusion. However, the dynamic nature of the DCE experiment limits simultaneous improvement of temporal and spatial resolution by conventional methods. Compressed sensing (CS) has become an important tool for the acceleration of imaging times in MRI, which is achieved by enabling the reconstruction of subsampled data. Similarly, CS algorithms can be utilized to improve the temporal/spatial resolution of DCE-MRI, and several works describing retrospective simulations have demonstrated the feasibility of such improvements. In this study, the fast low angle shot sequence was modified to implement a Cartesian, CS-optimized, sub-Nyquist phase encoding acquisition/reconstruction with multiple two-dimensional slice selections and was tested on water phantoms and animal tumor models. The mean voxel-level concordance correlation coefficient for Ak(ep) values obtained from ×4 and ×8 accelerated and the fully sampled data was 0.87±0.11 and 0.83±0.11, respectively (n=6), with optimized CS parameters. In this case, the reduction of phase encoding steps made possible by CS reconstruction improved effectively the temporal/spatial resolution of DCE-MRI data using an in vivo animal tumor model (n=6) and may be useful for the investigation of accelerated acquisitions in preclinical and clinical DCE-MRI trials. 相似文献
11.
Fan X Medved M Karczmar GS Yang C Foxley S Arkani S Recant W Zamora MA Abe H Newstead GM 《Magnetic resonance imaging》2007,25(5):593-603
The purpose of this study was to test whether an empirical mathematical model (EMM) of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can distinguish between benign and malignant breast lesions. A modified clinical protocol was used to improve the sampling of contrast medium uptake and washout. T(1)-weighted DCE magnetic resonance images were acquired at 1.5 T for 22 patients before and after injection of Gd-DTPA. Contrast medium concentration as a function of time was calculated over a small region of interest containing the most rapidly enhancing pixels. Then the curves were fitted with the EMM, which accurately described contrast agent uptake and washout. Results demonstrate that benign lesions had uptake (P<2.0 x 10(-5)) and washout (P<.01) rates of contrast agent significantly slower than those of malignant lesions. In addition, secondary diagnostic parameters, such as time to peak of enhancement, enhancement slope at the peak and curvature at the peak of enhancement, were derived mathematically from the EMM and expressed in terms of primary parameters. These diagnostic parameters also effectively differentiated benign from malignant lesions (P<.03). Conventional analysis of contrast medium dynamics, using a subjective classification of contrast medium kinetics in lesions as "washout," "plateau" or "persistent" (sensitivity=83%, specificity=50% and diagnostic accuracy=72%), was less effective than the EMM (sensitivity=100%, specificity=83% and diagnostic accuracy=94%) for the separation of benign and malignant lesions. In summary, the present research suggests that the EMM is a promising alternative method for evaluating DCE-MRI data with improved diagnostic accuracy. 相似文献
12.
It is widely recognised that the measurement of the arterial input function (AIF) is a key issue and a major source of errors in the pharmacokinetic modelling of dynamic, contrast-enhanced magnetic resonance imaging (DCE-MRI) data, and the modality of the AIF determination is still a matter of debate. In this study we addressed the problem of the intrinsic variability of the AIF within the imaged volume of a DCE-MRI scan by systematically investigating the change in the concentration of contrast agent over time and the fit parameters of the derived vascular input function (VIF) obtained from the superior sagittal sinus (SSS) of a patient population that was scanned longitudinally during treatment for high grade glioma. From a total of 82 scanning sessions, we compared the results obtained with three different DCE-MRI protocols and between two different fitting functions. We applied a correction algorithm to the measured concentration-time curves to minimize the effect of the low temporal resolution on the VIF, and investigated the effect of this algorithm on the reproducibility. Finally, where possible, we compared the signal obtained in the SSS to the signal obtained in the middle cerebral artery. We found a good intrapatient reproducibility of both the measured gadolinium concentrations and VIF parameters, and that the variation of the parameters due to slice location within a patient was significantly lower than the intra patient variation. Intrapatient, interscan differences were significantly less marked than inter-patient differences showing a good intraclass correlation coefficient. We did encounter a MRI protocol dependence of the VIF fitting parameters. The correction algorithm significantly improved the reproducibility of the fitting parameters. These results support the idea that the use of a patient specific measured AIF, not necessarily averaged over a large volume, offers a significant benefit with respect to an external AIF or a measured cohort average AIF. 相似文献
13.
A traditional successive cancellation (SC) decoding algorithm produces error propagation in the decoding process. In order to improve the SC decoding performance, it is important to solve the error propagation. In this paper, we propose a new algorithm combining reinforcement learning and SC flip (SCF) decoding of polar codes, which is called a Q-learning-assisted SCF (QLSCF) decoding algorithm. The proposed QLSCF decoding algorithm uses reinforcement learning technology to select candidate bits for the SC flipping decoding. We establish a reinforcement learning model for selecting candidate bits, and the agent selects candidate bits to decode the information sequence. In our scheme, the decoding delay caused by the metric ordering can be removed during the decoding process. Simulation results demonstrate that the decoding delay of the proposed algorithm is reduced compared with the SCF decoding algorithm, based on critical set without loss of performance. 相似文献
14.
Wilmes LJ Pallavicini MG Fleming LM Gibbs J Wang D Li KL Partridge SC Henry RG Shalinsky DR Hu-Lowe D Park JW McShane TM Lu Y Brasch RC Hylton NM 《Magnetic resonance imaging》2007,25(3):319-327
Dynamic contrast-enhanced MRI (DCE-MRI) was used to noninvasively evaluate the effects of AG-03736, a novel inhibitor of vascular endothelial growth factor (VEGF) receptor tyrosine kinases, on tumor microvasculature in a breast cancer model. First, a dose response study was undertaken to determine the responsiveness of the BT474 human breast cancer xenograft to AG-013736. Then, DCE-MRI was used to study the effects of a 7-day treatment regimen on tumor growth and microvasculature. Two DCE-MRI protocols were evaluated: (1) a high molecular weight (MW) contrast agent (albumin-(GdDTPA)(30)) with pharmacokinetic analysis of the contrast uptake curve and (2) a low MW contrast agent (GdDTPA) with a clinically utilized empirical parametric analysis of the contrast uptake curve, the signal enhancement ratio (SER). AG-013736 significantly inhibited growth of breast tumors in vivo at all doses studied (10-100 mg/kg) and disrupted tumor microvasculature as assessed by DCE-MRI. Tumor endothelial transfer constant (K(ps)) measured with albumin-(GdDTPA)(30) decreased from 0.034+/-0.005 to 0.003+/-0.001 ml min(-1) 100 ml(-1) tissue (P<.0022) posttreatment. No treatment-related change in tumor fractional plasma volume (fPV) was detected. Similarly, in the group of mice studied with GdDTPA DCE-MRI, AG-013736-induced decreases in tumor SER measures were observed. Additionally, our data suggest that 3D MRI-based volume measurements are more sensitive than caliper measurements for detecting small changes in tumor volume. Histological staining revealed decreases in tumor cellularity and microvessel density with treatment. These data demonstrate that both high and low MW DCE-MRI protocols can detect AG-013736-induced changes in tumor microvasculature. Furthermore, the correlative relationship between microvasculature changes and tumor growth inhibition supports DCE-MRI methods as a biomarker of VEGF receptor target inhibition with potential clinical utility. 相似文献
15.
16.
17.
18.
19.