Optimization of montages and electric currents in tDCS.

In order to optimize the capability of transcranial Direct Current Stimulation (tDCS), electrode arrangements and the inward current stimulation are taken into account as two crucial factors. In this contribution, in order to specify the electrode positions, a detailed protocol is investigated, in which regarding the intended targeted regions, the optimal montages with an arbitrary number of electrodes are developed. After designing the positions of all active and returned electrodes, the corresponding inward current density is determined for each electrode. The outcomes of the simulation and the electric field distributions in the hand cortex prove that the proposed protocol is capable of improving the tDCS efficiency substantially in all head layers. Furthermore, in order to compare our approach with the other works found in the literature, a performance evaluation is curried out by calculating the maximum electric field distribution in the targeted region. This study shows that it improves tDCS efficiency virtually 2.5 times in comparison to High Definition (HD) montages in the gray matter and nearly 1.5 times in comparison to the other inner layers. Such an outstanding achievement in the gray matter can be regarded as an interesting standpoint in tDCS-rehabilitation studies.

The effect of electromagnetic fields on survival and proliferation rate of dental pulp stem cells.

Aims: Extremely low-frequency electromagnetic fields (ELF-EMF) can affect biological systems and alter some cell functions like proliferation rate. Dental pulp tissue is known as a source of multipotent stromal stem cells (MSCs), which can be obtained by a less invasive and more available process compared to bone marrow-derived stem cells (BMSCs). This study aimed to consider the effect of ELF-EMF on proliferation rates of human dental pulp stem cells (hDPSCs).Material and methods: ELF-EMF was generated by a system including autotransformer, multi-meter, solenoid coils, teslameter and its probe. The effect of ELF-EMF with the intensity of 0.5 and 1 mT and 50 Hz on the proliferation rate of hDPSCs was assessed in 20 and 40 min per day for 7 days. MTT assay and DAPI test were used to determine the growth and proliferation of DPSCs.Results: Based on MTT, ELF-EMF has maximum effect with the intensity of 1 mT for 20 min/day on the proliferation of hDPSCs. The survival and proliferation rate in all exposure groups were significantly higher than the control group. Based on the data obtained from MTT and DAPI assay, the number of viable cells in the group exposed to 1 mT for 20 min/day was higher than other groups (p < .05).Conclusions: Regarding to the results of this study, 0.5 and 1 mT ELF-EMF can enhance survival and proliferation rates of hDPSCs.

PET and MRI image fusion based on combination of 2-D Hilbert transform and IHS method.

BACKGROUND: The process of medical image fusion is combining two or more medical images such as Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET) and mapping them to a single image as fused image. So purpose of our study is assisting physicians to diagnose and treat the diseases in the least of the time. METHODS: We used Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET) as input images, so fused them based on combination of two dimensional Hilbert transform (2-D HT) and Intensity Hue Saturation (IHS) method. Evaluation metrics that we apply are Discrepancy (Dk) as an assessing spectral features and Average Gradient (AGk) as an evaluating spatial features and also Overall Performance (O.P) to verify properly of the proposed method. RESULTS: In this paper we used three common evaluation metrics like Average Gradient (AGk) and the lowest Discrepancy (Dk) and Overall Performance (O.P) to evaluate the performance of our method. Simulated and numerical results represent the desired performance of proposed method. CONCLUSIONS: Since that the main purpose of medical image fusion is preserving both spatial and spectral features of input images, so based on numerical results of evaluation metrics such as Average Gradient (AGk), Discrepancy (Dk) and Overall Performance (O.P) and also desired simulated results, it can be concluded that our proposed method can preserve both spatial and spectral features of input images.

Fusion of ECG and ABP signals based on wavelet transform for cardiac arrhythmias classification.

BACKGROUND AND OBJECTIVE: Each of Electrocardiogram (ECG) and Atrial Blood Pressure (ABP) signals contain information of cardiac status. This information can be used for diagnosis and monitoring of diseases. The majority of previously proposed methods rely only on ECG signal to classify heart rhythms. In this paper, ECG and ABP were used to classify five different types of heart rhythms. To this end, two mentioned signals (ECG and ABP) have been fused. METHODS: These physiological signals have been used from MINIC physioNet database. ECG and ABP signals have been fused together on the basis of the proposed Discrete Wavelet Transformation fusion technique. Then, some frequency features were extracted from the fused signal. To classify the different types of cardiac arrhythmias, these features were given to a multi-layer perceptron neural network. RESULTS: In this study, the best results for the proposed fusion algorithm were obtained. In this case, the accuracy rates of 96.6%, 96.9%, 95.6% and 93.9% were achieved for two, three, four and five classes, respectively. However, the maximum classification rate of 89% was obtained for two classes on the basis of ECG features. CONCLUSIONS: It has been found that the higher accuracy rates were acquired by using the proposed fusion technique. The results confirmed the importance of fusing features from different physiological signals to gain more accurate assessments.

Cross-linked Polyelectrolyte and Its Function in Adsorption of Fluid and Excess Nitrogen Waste Products: an Experimental Study on Dialysate Effluent Fluid.

INTRODUCTION: One of the most important issues in patients with chronic kidney disease is fluid retention and volume overload accompanied by retention of nitrogenous waste products and some electrolytes. Bowel fluid contains high levels of urea, creatinine, uric acid, and electrolytes, which make it a potential candidate for intestinal excretion of nitrogen wastes and electrolytes. Cross-linked polyelectrolyte (CLP) is a polymer that, given orally, absorbs excess fluid, electrolyte, and nitrogenous waste products. MATERIALS AND METHODS: In an experimental study on 30 hemodialysis patients, the effect of CLP on adsorption of fluid, urea, creatinine, uric acid, sodium, and potassium were evaluated. For this purpose, 500 mL of effluent fluid of each patient were collected at the 1st hour of dialysis. The concentrations of the abovementioned products were measured by standard methods. Then the dialysate effluent samples were treated with 6 g of CLP and incubated for 4 hours at 37°C. RESULTS: Up to 80% of effluent fluid water was adsorbed by CLP. There were significant reductions in urea, creatinine, uric acid, and sodium levels in the remaining effluent fluid (P < .001). In contrast, the amount of potassium increased in the effluent fluid. CONCLUSIONS: Using CLP in addition to functional medical super adsorbents can be a possible adequate substitute for conventional dialysis methods, especially hemodialysis.

Future of the Renal Biopsy: Time to Change the Conventional Modality Using Nanotechnology.

At the present time, imaging guided renal biopsy is used to provide diagnoses in most types of primary and secondary renal diseases. It has been claimed that renal biopsy can provide a link between diagnosis of renal disease and its pathological conditions. However, sometimes there is a considerable mismatch between patient renal outcome and pathological findings in renal biopsy. This is the time to address some new diagnostic methods to resolve the insufficiency of conventional percutaneous guided renal biopsy. Nanotechnology is still in its infancy in renal imaging; however, it seems that it is the next step in renal biopsy, providing solutions to the limitations of conventional modalities.

Retinal image registration using geometrical features.

In this study, we have introduced an accurate retinal images registration method using affine moment invariants (AMI's) which are the shape descriptors. First, some closed-boundary regions are extracted in both reference and sensed images. Then, AMI's are computed for each of those regions. The centers of gravity of three pairs of regions which have the minimum of distances are selected as the control points. The region matching is performed by the distance measurements of AMI's. The evaluation of region matching is performed by comparing the angles of three triangles which are built on these three-point pairs in reference and sensed images. The parameters of affine transform can be computed using these three pairs of control points. The proposed algorithm is applied on the valid DRIVE database. In general (for the case, each sensed image is produced by rotating, scaling, and translating the reference image with different angles, scale factors, and translation factors), the success rate and accuracy is 95 and 96 %, respectively.

The effects of sedative music, arousal music, and silence on electrocardiography signals.

INTRODUCTION: Research indicates that music can affect heart rate, blood pressure, and skin conductance. Music can stimulate central emotions in the brain and release biochemical materials that change the physiologic state. We sought to compare changes in the electrical function of the heart in response to music. METHOD: Subjects were asked to listen to 2 types of music, namely, sedative and arousal music, in conjunction with two 30-second periods of complete silence. The experiment was conducted in 4 segments: the first and third parts were silence, and the second and fourth parts were music. First, the response to each type of music was compared with that to the preceding period of silence. Next, the responses to both types of music were compared. Finally, the response to music regardless of the type was compared with that to silence. RESULTS: The amplitude of polarization and depolarization changed in response to different kinds of music. The electrical function of the heart in response to music, irrespective of the music type, differed from that in response to silence. The 2 types of music impacted the electrical function of the heart in different ways: the arousal music influenced T-wave maximum amplitude, whereas no such change was recorded in response to the sedative music. CONCLUSIONS: The bandwidth of the polarization and depolarization of the heart rate and R-wave amplitude increased in response to music by comparison with silence. In addition, the heart did not seem to try to synchronize with music. The mean R-wave amplitude in sedative music is higher than the arousal music, so our heart works differently when different types of music are heard.

A feedback retina model for improving medical images fusion.

Image fusion has become a powerful technique for increasing the interpretation quality of images in medical applications. The diagnostic potential of brain positron emission tomography (PET) imaging is limited by low spatial resolution. For solving this problem, the high-frequency part of the MRI, which would be unrecoverable by the set PET acquisition system, is extracted and added to the PET image. The procedure has the potential of increasing the diagnostic value of a PET image. This paper presents a feedback retina model technique to reduce the spectral distortion and preserve high spatial resolution. Visual and statistical analyses show that the proposed feedback retina model significantly improves the fusion quality compared to non-feedback retina model.

A hybrid algorithm for medical image registration.

Registration is a process to align different acquired images of the same subject. A major problem in this field is to register images captured by different imaging systems. These images have different gray values so simple methods like correlation are not applicable. In this paper automated registration of CT and MR head images is studied. It is assumed that images are only of relative translation and rotation. The proposed method includes two stages. First, feature extraction of CT and MR images, (should be extractable and constant in both imaging systems). Second, feature alignment which is moment-based. The results confirm the accuracy and robustness of the proposed method.