Volume 14, Issue 4

Magnetic resonance imaging (MRI) is a widely used imaging modality to evaluate brain disorders. MRI generates huge volumes of data, which consist of a sequence of scans taken at different instances of time. As the presence of brain disorders has to be evaluated on all magnetic resonance (MR) sequences, manual brain disorder detection becomes a tedious process and is prone to inter- and intra-rater errors. A technique for detecting abnormalities in brain MRI using template matching is proposed. Bias filed correction is performed on volumetric scans using N4ITK filter, followed by volumetric registration. Normalized cross-correlation template matching is used for image registration taking into account, the rotation and scaling operations. A template of abnormality is selected which is then matched in the volumetric scans, if found, the corresponding image is retrieved. Post-processing of the retrieved images is performed by the thresholding operation; the coordinates and area of the abnormality are reported. The experiments are carried out on the glioma dataset obtained from Brain Tumor Segmentation Challenge 2013 database (BRATS 2013). Glioma dataset consisted of MR scans of 30 real glioma patients and 50 simulated glioma patients. NVIDIA Compute Unified Device Architecture framework is employed in this paper, and it is found that the detection speed using graphics processing unit is almost four times faster than using only central processing unit. The average Dice and Jaccard coefficients for a wide range of trials are found to be 0.91 and 0.83, respectively.

The acquisition of positron emission tomography (PET) pulses introduces artifacts and limits the performance of the scanner. To minimize these inadequacies, this work focuses on the design of an offset compensated digital baseline restorer (BLR) along with a two-stage hybrid interpolator. They respectively treat the incoming pulse offsets and limited temporal resolution and improve the scanner performance in terms of calculating depth of interactions and line of responses. The offset of incoming PET pulses is compensated by the BLR and then their interesting parts are selected. The selected signal portion is up-sampled with a hybrid interpolator. It is composed of an optimized weighted least-squares interpolator (WLSI) and a simplified linear interpolator. The processes of calibrating the WLSI coefficients and characterizing the BLR and the interpolator modules are described. The functionality of the proposed modules is verified with an experimental setup. Results have shown that the devised BLR effectively compensates a dynamic range of bipolar offsets. The signal selection process allows focusing only on the relevant signal part and avoids the unnecessary operations during the post-interpolation process. Additionally, the hybrid nature allows improving the signal temporal resolution with an appropriate precession at a reduced computational complexity compared to the mono-interpolation-based arithmetically complex counterparts. The component-level architectures of the BLR and the interpolator modules are also described. It promises an efficient integration of these modules in modern PET scanners while using standard and economical analog-to-digital converters and field-programmable gate arrays. It avoids the development of high-performance and expensive application-specific integrated circuits and results in a cost-effective realization.

The paper presents the physicochemical and structural characteristics as well as the comparison of selected statins. Statins are relatively popular compounds used in modern medicine. They are increasingly often combined with other medications to improve the effectiveness of therapy. We analyzed the characteristics of pravastatin, simvastatin, atorvastatin, pitavastatin, lovastatin, mevastatin, fluvastatin, and rosuvastatin obtained from the PubChem Substance database. On the basis of data related to chemical structure and physicochemical properties, the statins were grouped into more and less similar ones. Statins are not homogeneous in terms of physicochemical properties and structure. Three groups of statins were identified. Mevastatin, lovastatin, and simvastatin are the most similar to each other, while pravastatin shows a slightly lower similarity to them. Pitavastatin and fluvastatin are also highly similar, while atorvastatin and rosuvastatin, because of their properties, are the most different from other statin groups.

The interaction between oppositely charged membranes and polycations causes cell aggregation, loss of membrane fluidity, and membrane degeneration and may cause an increase of its permeability. Unfortunately, the interaction is the reason why the use of polycations in medicine is severely limited. Therefore, in this paper, we share our observations related to the action of 40-kDa dextran modified using glycidyltrimethylammonium chloride, resulting in increased fibroblast cell proliferation. Using viability and proliferation tests [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide, crystal violet, 3 H-thymidine incorporation], we have observed that cationic dextran derivatives exert a positive impact on nonepithelial cell proliferation in vitro . This phenomenon has been noted for human and mouse fibroblasts and several other nonepithelial cell lines. However, the effect seems to be most pronounced for fibroblast cell lines. The presented studies allow to examine the impact of the polymer structure and the methods of its cationic modification on this newly observed phenomenon. The observation is unique because positively charged macromolecules usually exhibit high toxicity in all cell types in vitro .

Background This article proposes an extension of empirical wavelet transform (EWT) algorithm for multivariate signals specifically applied to cardiovascular physiological signals. Materials and methods EWT is a newly proposed algorithm for extracting the modes in a signal and is based on the design of an adaptive wavelet filter bank. The proposed algorithm finds an optimum signal in the multivariate data set based on mode estimation strategy and then its corresponding spectra is segmented and utilized for extracting the modes across all the channels of the data set. Results The proposed algorithm is able to find the common oscillatory modes within the multivariate data and can be applied for multichannel heterogeneous data analysis having unequal number of samples in different channels. The proposed algorithm was tested on different synthetic multivariate data and a real physiological trivariate data series of electrocardiogram, respiration, and blood pressure to justify its validation. Conclusions In this article, the EWT is extended for multivariate signals and it was demonstrated that the component-wise processing of multivariate data leads to the alignment of common oscillating modes across the components.