Image registration by maximization of mutual information based on edge width matching using particle swarm optimization

Mutual information (MI) based image registration has been found to be quite effective in many medical image applications. However, standard MI hampers the convergence of registration transformation parameters since it contains local maxima. In this paper, a novel registration method is proposed. At first,MI based on edge width matching is computed to avoid great change of joint probability distribution and get less local maxima. Particle swarm optimization (PSO), which combines local search methods with global ones balancing exploration and exploitation, is done to search the optimal registration parameter.PSO has less computational complexity as its complex behavior follows only a few simple rules. It could avoid local maxima and reach global optimal results. This method is applicable to a variety of multimodal images, and suitable to different interpolation methods. Theoretical analysis and experiments show that this method is effective and accurate to register multimodal medical images.     

Speaker identification based on complete feature corpusand evaluation of mutual information

A speaker model called complete feature corpus (CFC) and an evaluation algorithm of mutual information (MIE) are proposed for text-independent speaker identification. The CFC model represents the speech and pronunciation characteristics of speaker by a feature vector corpus which was trained from some typical speech samples. It hires multi-step mini-max search matching scheme for MIE algorithm to evaluate the similarity of speech features between input speech and the models in distance and information space. Maximum mutual information (MMI) decision criterion is used to decide the identity of speaker. Experiments on performance analysis with comparison to GMM method show that proposed model and evaluation algorithm are quite effective and presented a higher performance than ordinary GMM method.     

Continuous EEG-fMRI in patients with partial epilepsy and focal interictal slow-wave discharges on EEG

Purpose

To verify whether in patients with partial epilepsy and routine electroenecephalogram (EEG) showing focal interictal slow-wave discharges without spikes combined EEG–functional magnetic resonance imaging (fMRI) would localize the corresponding epileptogenic focus, thus providing reliable information on the epileptic source.

Methods

Eight patients with partial epileptic seizures whose routine scalp EEG recordings on presentation showed focal interictal slow-wave activity underwent EEG–fMRI. EEG data were continuously recorded for 24 min (four concatenated sessions) from 18 scalp electrodes, while fMRI scans were simultaneously acquired with a 1.5-Tesla magnetic resonance imaging (MRI) scanner. After recording sessions and MRI artefact removal, EEG data were analyzed offline. We compared blood oxygen level-dependent (BOLD) signal changes on fMRI with EEG recordings obtained at rest and during activation (with and without focal interictal slow-wave discharges).

Results

In all patients, when the EEG tracing showed the onset of focal slow-wave discharges on a few lateralized electrodes, BOLD-fMRI activation in the corresponding brain area significantly increased. We detected significant concordance between focal EEG interictal slow-wave discharges and focal BOLD activation on fMRI. In patients with lesional epilepsy, the epileptogenic area corresponded to the sites of increased focal BOLD signal.

Conclusions

Even in patients with partial epilepsy whose standard EEGs show focal interictal slow-wave discharges without spikes, EEG–fMRI can visualize related focal BOLD activation thus providing useful information for pre-surgical planning.     

Quantitative evaluation of optimal imaging parameters for single-cell detection in MRI using simulation

Super-paramagnetic iron oxide (SPIO) nanoparticles are actively investigated to enhance disease detection through molecular imaging using magnetic resonance imaging (MRI). Detection of the cells labeled by SPIO depends on the MRI protocols and pulse sequence parameters that can be optimized. To evaluate the sensitivity and specificity of the image acquisition methods and to obtain optimal imaging parameters for single-cell detection, we further developed an MRI simulator. The simulator models an object (tissue) at a microscopic level to evaluate effects of spatial distribution and concentration of nanoparticles on the resulting image. In this study, the simulator was used to evaluate and compare imaging of the labeled cells by the gradient-echo (GE), true-FISP [fast imaging employing steady-state acquisition (FIESTA)] and echo-planar imaging (EPI) pulse sequences. Effects of the imaging and object parameters, such as field strength, imaging protocol and pulse sequence parameters, imaging resolution, cell iron load, position of SPIO within the voxel and cell division within the voxel, were investigated in the work. The results suggest that true-FISP has the highest sensitivity for single-cell detection by MRI.     

基于互信息方法的燃油品质光谱分析模型构建与简化

近红外漫反射光谱和紫外吸收光谱分别用于燃油的辛烷值和单芳香族化合物含量的测定,偏最小二乘回归(partial least squares regression,PLSR)用于光谱多元校正模型的构建。基于互信息(mutual infor-mation,MI)理论的变量筛选方法用于模型优化以提高模型的预测精度,降低模型的复杂度。结果表明,MI-PLSR可以有效的提高燃油品质模型的预测精度,简化分析模型。辛烷值的预测均方根误差(root meansquare error of prediction,RMSEP)由0.288减小为0.111,预测相关系数R从0.985提高到0.998,建模变量由401减小为112;单芳香族化合物含量的RMSEP从0.753减小为0.478,R由0.996提高为0.998,建模变量由572缩减为37。说明振动光谱结合MI-PLSR方法可用于燃油品质检测,具有高效率低成本的特点。     

Quantitative magnetic resonance imaging in consecutive patients evaluated for surgical treatment of temporal lobe epilepsy

We present the results of quantitative Magnetic Resonance Imaging (MRI) in 55 consecutively referred patients with clinical evidence of temporal lobe epilepsy (TLE). The Cavalieri method was used in combination with point counting to provide unbiased estimates of the volume of the left and right hippocampus, amygdala, temporal lobe, lateral ventricles and cerebral hemisphere, and pixel by pixel maps of the T2 relaxation time were computed for both central and anterior sections of the hippocampus. The 99th centiles of hippocampal volume, hippocampal volume asymmetry and T2 relaxation times in 20 control subjects provided limits which identified the presence of MTS. The results of the quantitative MRI were compared with the results of conventional diagnostic MRI, foramen ovale (FO) recording and the WADA test. Thirty-one patients were found to have unilateral MTS (17 left and 14 right) and 7 bilateral MTS. No evidence of MTS was detected in 16 patients. Of the 31 patients diagnosed with unilateral MTS on the basis of hippocampal volume and T2 measurement, 74% and 77% would respectively have received the same diagnosis on the basis of hippocampal volume and T2 measurements alone. In comparison to FO recording, quantitative MRI has a sensitivity of 55% and a specificity of 86%, while conventional diagnostic MRI has a sensitivity of 42% and a specificity of 80% for detection of MTS. Unilateral abnormalities were detected by FO recording in 30% cent of patients who appeared normal on quantitative MRI. WADA test results were available for 40 patients. The findings were consistent with quantitative MRI showing reduced memory function ipsilateral to unilateral MTS in 18 patients, but reduced memory function contralateral to unilateral MTS in two patients, and reduced memory function without MR abnormality in seven patients. WADA testing revealed unilateral memory impairments where MRI found bilateral pathology in 4 patients and in 4 patients in whom quantitative MRI detected unilateral MTS there was no evidence of reduced memory during WADA testing of the corresponding cerebral hemisphere. In the patients with unilateral right MTS a highly significant negative correlation (p = 0.0003) was observed between age of onset and the volume of the contralateral temporal lobe.

Quantitative MR imaging of the hippocampus (i.e. volume and T2 measurement) is preferable to conventional radiological reporting for providing objective evidence of the presence of MTS on which to base the referral of patients for surgery, and since it has associated morbidity FO recording is now only being used in selected patients. Furthermore, stereology provides a convenient method for estimating the volume of other brain structures, which is relevant to obtaining a better understanding of the effects of laterality and age of onset of TLE.     

Quantitative human in vivo evaluation of high resolution MRI for vessel wall morphometry after percutaneous transluminal angioplasty

Visualization of the vessel wall after transluminal angioplasty is important to monitor the restenosis progress. Intravascular ultrasound proved its capabilities as an invasive procedure in many studies. The aim of this study was to evaluate the feasibility of high-resolution MRI as a non-invasive tool for follow-up after PTA. High-resolution magnetic resonance images (pixel size: 0.49 * 0.49 mm(2)) were acquired on a 1.0 T clinical scanner. Morphometry was conducted after conversion of DICOM images into TIFF format using ScionImage on a PC. In-vitro studies using a polyvinylchloride tube were evaluated by two independent investigators. Goldstandard was a caliper rule and direct radiography. Five patients were monitored before and 24 h, six weeks, three months and six months after PTA. In vivo measurements promised a good concordance for both investigators for area as well as for diameter measurements. Area measurements showed correlations up to r = 0.86 (p < 0.001) whereas the correlations of diameters were slightly inferior (r between 0.58 and 0.84; p < 0.005). Relocation of the same slice position in the follow up studies could be guaranteed using anatomic landmarks in the images. As a non-invasive tool to assess restenosis after PTA high-resolution MRI promises to be a reproducible technique. It is easy to identify the same vascular region in different studies due to neighboring anatomic landmarks. Progression of disease as well as success of pharmacologic treatment to prevent restenosis may be monitored.     

Fractality in the neuron axonal topography of the human brain based on 3-D diffusion MRI

We report our results on the effect of incorporation of inorganic fullerene like nanoparticles (IF) and inorganic nanotubes (INT) of WS₂ into hybrid LED device structures. To disperse into a uniform fashion, the semiconducting INT/IF WS₂ NTs were functionalized with SDS (sodium dodecylsulphate). The IF/INT WS₂ nanotubes were used in combination with PEDOT:PSS and P3HT to realize the following LED device structures: ITO/(PEDOT:PSS):(WS₂:SDS)/P3HT/LiF-Al; ITO/PEDOT:PSS/P3HT/WS₂:SDS/LiF-Al. Morphological, optical and electrochemical analysis were performed to obtain the HOMO and the LUMO energy levels to hypothesize the most efficient device structure. The spectral positions of the electroluminescent bands were found out to be device-dependent and exhibits blue shift when the proposed nanostructure is dip coated on top of P3HT. Electro-optical analysis indicate that the WS₂:SDS based P3HT/semiconductor film can improve the charge recombination probability owing to its dual functionality as hole blocking layer and electron injection moiety.     

Automatic segmentation of brain MRI in high-dimensional local and non-local feature space based on sparse representation

Automatic extraction of the varying regions of magnetic resonance images is required as a prior step in a diagnostic intelligent system. The sparsest representation and high-dimensional feature are provided based on learned dictionary. The classification is done by employing the technique that computes the reconstruction error locally and non-locally of each pixel. The acquired results from the real and simulated images are superior to the best MRI segmentation method with regard to the stability advantages. In addition, it is segmented exactly through a formula taken from the distance and sparse factors. Also, it is done automatically taking sparse factor in unsupervised clustering methods whose results have been improved.     

Small hyperintense hepatic lesions on T1-weighted images in patients with cirrhosis: evaluation with serial MRI and imaging features for clinical benignity

PURPOSE: The aim of this study was to evaluate the frequency and magnetic resonance imaging (MRI) features of clinically benign, small (<2 cm) hyperintense hepatic lesions in the cirrhotic liver on T1-weighted MR images seen at serial MRI. MATERIALS AND METHODS: This study included 189 patients with cirrhosis, who underwent hepatic MRI more than twice with an interval of at least 12 months. The initial MR images were reviewed for the presence of small hyperintense lesions on T1-weighted images. The size, location and signal intensity on T2-weighted images as well as enhancement patterns of the corresponding lesions were recorded. RESULTS: On the initial T1-weighted MR images, 43 small hyperintense hepatic lesions were detected in 23 (12%) of 189 patients. Twelve (28%) of 43 lesions showed early enhancement and were pathologically diagnosed as hepatocellular carcinoma (HCC) during the follow-up period. Thirty-one (72%) of 43 lesions showed no early enhancement with various signal intensity on T2-weighted images (hyperintensity=4, isointensity=20, hypointensity=7). Among these 31 lesions, 12 showed no interval change, while 11 disappeared (n=10) or decreased in size (n=1). In the remaining eight lesions, seven were diagnosed as HCC on the basis of pathologic confirmation or the interval growth. CONCLUSION: Small hyperintense hepatic lesions on T1-weighted magnetic resonance (MR) images without early enhancement on the arterial-phase contrast-enhanced dynamic studies in patients with cirrhosis usually showed no interval growth or disappeared during the serial MRI. These lesions with additional findings of iso- or hypointensity on the T2-weighted MR images without "washout effect" on the contrast-enhanced equilibrium-phase images may more frequently be clinically benign or hyperplastic nodules than HCCs.     

Comparison of analytical strategies for EEG-correlated fMRI data in patients with epilepsy

The simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can be used to localize interictal epileptiform discharges (IEDs). Previous studies have reported varying degrees of concordance of EEG-fMRI with electroclinical findings. The aim of the present study is to evaluate to what extent this variability is determined by the analytical strategy or by the properties of the EEG data. For that purpose, 42 IED sets obtained in 29 patients with epilepsy were reanalyzed using a finite impulse response approach, which estimates the hemodynamic response function (HRF) from the data and allows non-causal effects. Cardiac effects were treated as additional confounders in the model. This approach was compared to the classical approach assuming a fixed HRF for each voxel in the brain. The performance of each method was assessed by comparing the fMRI results to the EEG focus. The flexible model revealed more significantly activated voxels, which resulted in more activated brain regions concordant with the EEG focus (26 vs. 16). Correction for cardiac effects improved the results in 7 out of the 42 data sets. Furthermore, design theory for event-related experiments was applied in order to determine the influence of the number of IEDs and their temporal distribution on the success of an experiment. It appeared that this success is highly dependent upon the number of IEDs present during the recording and less on their temporal spacing. We conclude that the outcome of EEG-fMRI can be improved by using an optimized analytical strategy, but also depends on the number of IEDs occurring during the recording.     

Estimation of mutual information objective function based on Fourier shift theorem: an application to eddy current distortion correction in diffusion tensor imaging

Diffusion tensor imaging requires correction of eddy current distortion in diffusion-weighted images. An effective retrospective correction approach is to transform a diffusion-weighted image to maximize the mutual information (MI) between the transformed diffusion-weighted image and the corresponding T2-weighted image. In the literature, either linear interpolation or partial volume interpolation is applied to estimate the MI objective function. However, these interpolation methods induce artifacts to the MI objective function, thus compromising correction results. In this work, the MI objective function is estimated based on interpolation using Fourier shift theorem. This method eliminates the artifacts incurred with the aforementioned interpolation methods. The algorithm is further improved by approximating pixel values using their nearest neighbors in the up-sampled spatial domain, resulting in dramatically increased computational efficiency without compromising the correction results. The effects of varying the number of quantization levels and using Parzen window filtering to smooth the MI objective function are also investigated to obtain optimized algorithm parameters. The diffusion tensor image quality after applying the proposed distortion correction method is significantly improved visually.     

Effect of the mutual rectification of two electromagnetic waves with perpendicular polarization planes in a superlattice based on graphene

The effect of the mutual rectification of two electromagnetic waves with perpendicular polarization planes in a superlattice based on graphene was investigated. It was shown that, due to the nonadditive nature of the electronic spectrum of a superlattice based on grapheme, a constant term of current arises along its axes. The dependence of the constant of current density on the intensity of an electromagnetic wave is oscillatory in nature.     

Feasibility of similarity coefficient map in improving morphological evaluation of T2* weighted MRI for renal cancer

The purpose of this paper is to investigate the feasibility of similarity coefficient map (SCM) in improving morphological evaluation of T₂^* weighted (T₂^*W) magnatic resonance imaging (MRI) for renal cancer. Simulation studies and in vivo 12-echo T₂^*W experiments for renal cancers were performed for this purpose. The results of the first simulation study suggest that SCM can reveal small structures which are hard to be distinguished from the background tissue in T₂^*W images and the corresponding T₂^* map. The capability of improving morphological evaluation is likely due to the improvement in signal to noise ratio (SNR) and carrier to noise ratio (CNR) by SCM technique. Compared with T₂^*W images, SCM can improve SNR by a factor ranging from 1.87 to 2.47. Compared with T₂^* maps, SCM can improve SNR by a factor ranging from 3.85 to 33.31. Compared with T₂^*W images, SCM can improve CNR by a factor raging from 2.09 to 2.43. Compared with T₂^* maps SCM can improve CNR by a factor raging from 1.94 to 8.14. For a given noise level, the improvements of SNR and CNR depend mainly on the original SNRs and CNRs in T₂^*W images, respectively. In vivo experiments confirmed the results of the first simulation study. The results of the second simulation study suggest that more echoes are used to generate SCM, and higher SNR and CNR can be achieved in SCM. In conclusion, SCM can provide improved morphological evaluation of T₂^*W MR images for renal cancer by unveiling fine structures which are ambiguous or invisible in the corresponding T₂^*W MR images and T₂^* maps. What is more, in practical application, for a fixed total sampling time, one should increase the number of echoes as much as possible to achieve SCMs with better SNR and CNR.     

A new quantitative evaluation method of spiral drawing for patients with Parkinson’s disease based on a polar coordinate system with varying origin

Parkinson’s disease (PD) is a common disease of the central nervous system among the elderly, and its complex symptoms bring up challenges for the clinical diagnosis. In this paper, a new method based on a polar coordinate system with varying origin was proposed in order to quantitatively evaluate the performance in spiral drawing tasks for patients with Parkinson’s disease, since this method can assess the movement ability of spiral drawing before and after deep brain stimulation (DBS) among the patients. In this paper, three normal subjects and twelve PD patients participated in spiral drawing experiment. The hand movements of patients, before and after DBS, were recorded by a digitized tablet respectively in this experiment. And the variation of origin, radius, degree and other characteristics of hand movements were evaluated by introducing a set of parameters for feature extraction. The result showed that the proposed polar coordinate system embraced good performance in the quantitative evaluation of spiral drawing. Therefore, the proposed method overcame the limitation of data processes with fixed origin for diagnosis and evaluation, and by combining with extraction and analysis of characteristic parameters it had clinical significance in measuring the effectiveness of operation or treatment for the PD patients.     

In vivo evaluation of the reproducibility of T1 and T2 measured in the brain of patients with multiple sclerosis.

The precision (reproducibility) of relaxation times derived from magnetic resonance images of patients with multiple sclerosis (MS) were investigated. Measurements of 10 MS patients were performed at 1.5 T on two occasions within 1 wk. T1 and T2 was measured using a partial saturation inversion recovery sequence (6 points) and a Carr-Purcell-Meiboom-Gill phase alternating-phase shift multiple spin-echo sequence with 32 echoes. Regions of interest (ROI) were placed both in apparently normal white matter and plaques. The precision (+/- 1.96 SD) and the confidence intervals for T1 and T2 for white matter and plaques were calculated. The precision of T1 for white matter and plaques was respectively +/- 94 msec and +/- 208 msec. The precision of T2 for white matter and plaques was respectively +/- 18 msec and +/- 26 msec. For all measurements the coefficient of variation was about 9%. Judging from our own study and others as well, a precision better than 10% for T1 and T2 would seem unrealistic at present.     

Critical evaluation of screening techniques for emerging environmental contaminants based on accurate mass measurements with time-of-flight mass spectrometry

Emerging contaminants from wastewater effluent samples were analysed, using posttarget and nontarget analysis techniques. The samples were analysed with an ultra performance liquid chromatograph-time-of-flight mass spectrometer (UPLC-TOF-MS), and the resulting data were processed with commercial deconvolution software. The method works well for posttarget analysis with prior information about the retention times of the compounds of interest. With positive polarity, 63 of 66 compounds and with negative polarity, 18 of 20 compounds were correctly identified in a spiked sample, while two compounds of a total of 88 fell out of the mass range. Furthermore, a four-stage process for identification was developed for the posttarget analysis lacking the retention time data. In the process, the number of candidate compounds was reduced by using the accurate mass of selected compounds in two steps (stages 1 and 2), structure-property relationships (stage 3) and isotope patterns of the analytes (stage 4). The process developed was validated by analysing wastewater samples spiked with 88 compounds. This procedure can be used to gain a preliminary indication of the presence of certain analytes in the samples. Nontarget analysis was tested by applying a theoretical mass spectra library for a wastewater sample spiked with six pharmaceuticals. The results showed a high number of false identifications. In addition, manual processing of the data was considered laborious and ineffective. Finally, the posttarget analysis was applied to a real wastewater sample. The analysis revealed the presence of six compounds that were afterwards confirmed with standard compounds as being correct. Three psycholeptics (nordiazepam, oxazepam and temazepam) could be tentatively identified, using the identification process developed. Posttarget analysis with UPLC-TOF-MS proved to be a promising method for analysing wastewater samples, while we concluded that the software for nontarget analysis will need improvement before it can be used in environmental analytical work with LC-TOF-MS systems.     

Quantitative model for the change of optical resonance in neural activity detection systems based on surface plasmon resonance

The mechanism of neural activity detection using the surface plasmon resonance (SPR) phenomenon was theoretically explored in this paper. Investigating the mechanism of SPR neural recordings has been difficult due to the complex relationship between different physiological and physical processes such as excitation of a nerve fiber and coherent charge fluctuations on the metal surface. This paper examines how these different processes may be connected by introducing a set of compartmental theoretical models that deal with the molecular scale phenomena; Poisson-Boltzmann (PB) equation, which was used to describe the ion concentration change under the time varying electrostatic potential, Drude-Lorentz electron model, which was used to describe electron dynamics under the time varying external forces, and a Fresnel's three-layered model, which expresses the reflectivity of the SPR system in terms of the dielectric constants. Each physical theoretical model was numerically analyzed using the finite element method (FEM) formulated for the PB equation and the Green's method formulated for the Drude-Lorentz electron equation. The model predicts that the ionic thermal force originating from the opening of the K⁺ ion channel is fundamental for modifying the dipole moment of the gold's free electron; thus, the reflectivity is changed in the SPR system. The discussion was done also on important attributes of the SPR signal such as biphasic fluctuation and the electrical noise-free characteristics.     

A method of segment protection based on p-cycle for dynamic multicast with limited-range wavelength converter in WDM network

In the optical multicast network, node and link failures have very important influence on the network survivability which may lead to multiple destinations cannot receive data. Based on the wavelength layered-graph method, a method of efficiency-score based on heuristic algorithm of pre-configured cycle (p-Cycle) based-segment protection (ESHS) for dynamic multicast with limited-range wavelength conversion was presented in this paper. By finding the multicast tree segment protection, the total available p-Cycles are constructed for the multicast. Then we calculate each p-Cycle efficiency-score, the highest efficient-score p-Cycle is selected as the multicast route protection p-Cycle. The simulation results show that the ESHS can get higher performance than the existing ESHT algorithm, in terms of multicast request blocking probability and wavelength utilization.