Assessing Brain Pathophysiology through Non-Linear Analysis of MEG in Ιdiopathic Generalized Epilepsy Cases

Background: Non-linear signal analysis has proven to be a technique that is capable of revealing qualitative and quan- titative differentiations between different dynamical systems (biological or otherwise). In the present work it has been demonstrated that this capability reveals quantitative differences in the Magnetoencephalograms (MEG) received from patients with Idiopathic Generalized Epilepsy (IGE) and from healthy volunteers. Method: We present MEG record- ings of 10 epileptic patients with IGE and the corresponding ones from 10 healthy volunteers. A 122-channel SQUID biomagnetometer in an electromagnetically shielded room was used to record the MEG signals and the Grassber- ger-Procaccia method for the estimation of the correlation dimension was applied in the phase space reconstruction of the recorded signal from each patient. Results: The aforementioned analysis demonstrates the existence of spatially diffused low dimensionality in the MEG signals of patients with IGE. Conclusion: The obtained results provide support for the hypothesis that low dimensionality in MEG signals is linked to functional brain pathogeny.

An algorithm for computed tomography image reconstruction from limited-view projections

With the development of the compressive sensing theory, the image reconstruction from the projections viewed in limited angles is one of the hot problems in the research of computed tomography technology. This paper develops an iterative algorithm for image reconstruction, which can fit the most cases. This method gives an image reconstruction flow with the difference image vector, which is based on the concept that the difference image vector between the reconstructed and the reference image is sparse enough. Then the l1-norm minimization method is used to reconstruct the difference vector to recover the image for flat subjects in limited angles. The algorithm has been tested with a thin planar phantom and a real object in limited-view projection data. Moreover, all the studies showed the satisfactory results in accuracy at a rather high reconstruction speed.

A new level set model for cell image segmentation

In this paper we first determine three phases of cell images： background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

Interleaving Gradient Magnetic Field Method for Diffusion Weighted Spectroscopy

Diffusion-weighted magnetic resonance spectroscopy （DWS） has considerable potential in clinical and research applications. However, it is seldom implemented in conventional magnetic resonance imaging （MRI） scanners due to the strict hardware requirements. We propose an interleaving gradient magnetic field （IGMF） method based on point resolved spectroscopy （PRESS）. Four interlaced powerful diffusion sensitive gradient magnetic fields are positioned around the two π refocusing rf pulses in the PRESS sequence. This method utilizes the interval time in the PRESS pulse sequence, doubles the duration time of the diffusion sensitive gradient magnetic field and decreases the detrimental effect of the induced eddy current. The results of theoretical analysis and experimental observation demonstrate that the IGMF method is suitable for conventional MRI scanners.

Scattering correction method for panel detector based cone beam computed tomography system

A scattering correction method for a panel detector based cone beam computed tomography system is presented. First, the x-ray spectrum of the system is acquired by using the Monte Carlo simulation method. Secondly, scattered photon distribution is calculated and stored as correction matrixes by using the Monte Carlo simulation method according to scanned objects and computed tomography system specialties. Thirdly, scattered photons are removed from projection data by correction matrixes. A comparison of reconstruction image between before and after scattering correction demonstrates that the scattering correction method is effective for the panel detector based cone beam computed tomography system.

Local synchronization and amplitude of the fluctuation of spontaneous brain activity in attention-deficit/hyperactivity disorder:a resting-state fMRI study

Regional homogeneity（ReHo）and the amplitude of low-frequency fluctuation（ALFF）are two approaches to depicting different regional characteristics of resting-state functional magnetic resonance imaging（RS-fMRI）data.Whether they can complementarily reveal brain regional functional abnormalities in attention-deficit/hyperactivity disorder（ADHD）remains unknown.In this study,we applied ReHo and ALFF to 23 medication-na ve boys diagnosed with ADHD and 25 age-matched healthy male controls using whole-brain voxel-wise analysis.Correlation analyses were conducted in the ADHD group to investigate the relationship between the regional spontaneous brain activity measured by the two approaches and the clinical symptoms of ADHD.We found that the ReHo method showed widely-distributed differences between the two groups in the fronto-cingulo-occipitocerebellar circuitry,while the ALFF method showed a difference only in the right occipital area.When a larger smoothing kernel and a more lenient threshold were used for ALFF,more overlapped regions were found between ALFF and ReHo,and ALFF even found some new regions with group differences.The ADHD symptom scores were correlated with the ReHo values in the right cerebellum,dorsal anterior cingulate cortex and left lingual gyrus in the ADHD group,while no correlation was detected between ALFF and ADHD symptoms.In conclusion,ReHo may be more sensitive to regional abnormalities,at least in boys with ADHD,than ALFF.And ALFF may be complementary to ReHo in measuring local spontaneous activity.Combination of the two may yield a more comprehensive pathophy-siological framework for ADHD.