ROI-Based Compression Strategy of 3D MRI Brain Datasets for Wireless Communications

ObjectivesBecause of the large amount of medical imaging data, the transmission process becomes complicated in telemedicine applications. Thus, in order to adapt the data bit streams to the constraints related to the limitation of the bandwidths a reduction of the size of the data by compression of the images is essential. Despite the improvements in the field of compression, the transmission itself can also introduce errors. For this reason, it is important to develop an adequate strategy which will help reduce this volume of data without having to introduce some distortion and resist the errors introduced by the channel noise during transmission. Thus, in this paper, we propose a ROI-based coding strategy and unequal bit stream protection to meet this dual constraint.Material and methodsThe proposed ROI-based compression strategy with unequal bit stream protection is composed of three parts: the first one allows the extraction of the ROI region, the second one consists of a ROI-based coding and the third one allows an unequal protection of the ROI bit stream.First, the Regions Of Interest (ROI) are extracted by hierarchical segmentation of these regions according to a segmentation method based on the technique of Marker-based-watershed combined with the technique of active contours by level set. The resulting regions are selectively encoded by a 3D coder based on a shape adaptive discrete wavelet transform 3D-BISK, where the compression ratio of each region depends on its relevance in diagnosis. These obtained regions of interest are protected with an error-correcting code of Reed-Solomon type with a code rate that varies according to the relevance of the region by an unequal protection strategy (UEP).ResultsThe performance of the proposed compression scheme is evaluated in several ways. First, tests are performed to study the impact of errors on the different bit streams. In the first place, these tests are carried out in order to study the effect of the variation of the compression rates on the different bit streams. Secondly, different Reed Solomon error-correcting codes of different code rates are tested at different compression rates on a BSC channel. Finally, the performances of this coding strategy are compared with those of SPIHT 3D in the case of transmission on a BSC channel.ConclusionThe obtained results show that the proposed method is quite efficient in transmission time reduction. Therefore, our proposed scheme will reduce the volume of data without having to introduce some distortion and resist the errors introduced by the channel noise in the case of telemedicine.     

Empirical Mode Decomposition and Wavelet Transform Based ECG Data Compression Scheme

ObjectiveIn health-care systems, compression is an essential tool to solve the storage and transmission problems. In this regard, this paper reports a new electrocardiogram (ECG) data compression scheme which employs sifting function based empirical mode decomposition (EMD) and discrete wavelet transform.MethodEMD based on sifting function is utilized to get the first intrinsic mode function (IMF). After EMD, the first IMF and four significant sifting functions are combined together. This combination is free from many irrelevant components of the signal. Discrete wavelet transform (DWT) with mother wavelet ‘bior4.4’ is applied to this combination. The transform coefficients obtained after DWT are passed through dead-zone quantization. It discards small transform coefficients lying around zero. Further, integer conversion of coefficients and run-length encoding are utilized to achieve a compressed form of ECG data.ResultsCompression performance of the proposed scheme is evaluated using 48 ECG records of the MIT-BIH arrhythmia database. In the comparison of compression results, it is observed that the proposed method exhibits better performance than many recent ECG compressors. A mean opinion score test is also conducted to evaluate the true quality of the reconstructed ECG signals.ConclusionThe proposed scheme offers better compression performance with preserving the key features of the signal very well.     

Modified Fuzzy Q Learning Based Classifier for Pneumonia and Tuberculosis

This work proposes reinforcement learning for correctly identifying pneumonia and tuberculosis (TB) using a repository of X ray images. To our knowledge, this is a first attempt at employing reinforcement learning for pneumonia and TB classification. In particular, modified fuzzy Q learning (MFQL) algorithm in conjunction with wavelet based pre-processing has been used to build a classifier for identifying pneumonia and tuberculosis's severity. Proposed classifier is a self-learning one and uses pneumonia dataset (no pneumonia, mild pneumonia and severe pneumonia) and tuberculosis dataset (TB present, TB absent) samples to classify X ray images of subjects. Results indicate that MFQL based approach achieves high accuracy and fares much better over contemporary Support Vector Machine (SVM) and k-Nearest Neighbor (KNN) classifiers. Proposed classifier can be a useful tool for pneumonia and tuberculosis diagnosis in a practical setting.     

C/C++ Coding for Matrix Pseudo Inverses in Clinical Near Infrared Spectroscopy

Near infrared spectroscopy is used clinically to investigate patterns of change in cerebral oxygenation. We have shown that differences reported between authors are likely the result of computer encoding errors in the manipulation of matrices. Current methods compute the inverse of a non-square matrix to derive chromophore concentration values, and solution of another non-square matrix to derive polynomial coefficients of a least squares best fit curve from which the first derivative can be used to estimate blood flow values. Encoding of these pseudo inverses involves too many nested looping steps to easily identify encoding errors. We have given C/C++ source code along with sample numerical values at the termination of each loop within the algorithm. This provides counter checking for future software development by other programmers, and also permits other investigators to report whether the software used for their experiments agrees with previously published material.     

QT interval measurement using RMED curve; a novel approach based on wavelet techniques

Hypothesis/objective: Prolonged QT interval is an index of propensity for dangerous ventricular tachyarrhythmias. The aim of this article is to establish an automatic algorithm for QT interval measurement.

Method: The proposed method is based on the continuous wavelet transform. In this method, the concepts of the rescaled wavelet coefficients and dominant scales of the electrocardiogram (ECG) components are used to perform detection of ECG characteristic points. A new concept of rescaled maximum energy density is introduced so as to perform the estimation of the QT interval.

Results and conclusion: We have applied the algorithm to the PTB database of the Physiobank?Physionet in lead II. Then, the results were evaluated using pertinent reference QT. The criterion used for evaluation of the method's performance is the root mean square (RMS) error. The method approached the RMS error of 27.89 ms for 549 subjects. The proposed method is fast, simple and is applicable to a wide range of ECG cardio cycle morphologies.     

A time–frequency approach to estimate critical time intervals in postural control

The critical time interval (CTI) is a parameter that has been used to distinguish open-loop from closed-loop control during upright stance. The aim of this study was to develop a new method to determine CTIs. The new approach, termed the intermittent critical time interval (ICTI) method, was motivated from evidence that upright standing is an intermittent rather than an asymptotic stability control process. For this ICTI method, center-of-pressure time series are first transformed to the time–frequency domain with a wavelet method. Subsequently, the CTI is assumed equal to the time span between two local maxima in the time–frequency domain within a distinct frequency band (i.e., 0.5–1.1 Hz). This new method may help facilitate better estimates of the transition time interval between open and closed-loop control during upright stance and can also be applied in future work such as in simulating postural control. In addition, this method can be used in future work to assess temporal changes in CTIs.     

New head models extracted from thermal infrared (IR) images for dosimetry computations

In electromagnetic dosimetry, anatomical human models are commonly obtained by segmentation of magnetic resonance imaging or computed tomography scans. In this paper, a human head model extracted from thermal infrared images is examined in terms of its applicability to specific absorption rate (SAR) calculations. Since thermal scans are two-dimensional (2D) representation of surface temperature, this allows researchers to overcome the extensive computational demand associated with 3D simulation. The numerical calculations are performed using the finite-difference time-domain method with mesh sizes of 2 mm at 900 MHz plane wave irradiation. The power density of the incident plane wave is assumed to be 10 W/m². Computations were compared with a realistic anatomical head model. The results show that although there were marked differences in the local SAR distribution in the various tissues in the two models, the 1 g peak SAR values are approximately similar in the two models.     

Antibacterial activity and spectral studies of trivalent chromium,manganese, iron macrocyclic complexes derived from oxalyldihydrazide and glyoxal

A new series of complexes is synthesized by template condensation of oxalyldihydrazide and glyoxal in methanolic medium in the presence of trivalent chromium, manganese and iron salts forming complexes of the type: [M(C₈H₈N₈O₄)X]X₂ where M = Cr(III), Mn(III), Fe(III) and X = Cl^{? 1}, , CH₃COO^{? 1}. The complexes have been characterized with the help of elemental analyses, conductance measurements, magnetic susceptibility measurements, electronic, NMR, infrared and far infrared spectral studies. On the basis of these studies, a five coordinate square pyramidal geometry for these complexes has been proposed. The biological activities of the metal complexes were tested in vitro against a number of pathogenic bacteria and some of the complexes exhibited remarkable antibacterial activities.     

Interaction of cyproheptadine hydrochloride with human serum albumin using spectroscopy and molecular modeling methods

The interaction between cyproheptadine hydrochloride (CYP) and human serum albumin (HSA) was investigated by fluorescence spectroscopy, UV–vis absorption spectroscopy, Fourier transform infrared spectroscopy (FT‐IR) and molecular modeling at a physiological pH (7.40). Fluorescence of HSA was quenched remarkably by CYP and the quenching mechanism was considered as static quenching since it formed a complex. The association constants K_a and number of binding sites n were calculated at different temperatures. According to Förster's theory of non‐radiation energy transfer, the distance r between donor (human serum albumin) and acceptor (cyproheptadine hydrochloride) was obtained. The effect of common ions on the binding constant was also investigated. The effect of CYP on the conformation of HSA was analyzed using FT‐IR, synchronous fluorescence spectroscopy and 3D fluorescence spectra. The thermodynamic parameters ΔH and ΔS were calculated to be ?14.37 kJ mol^?1 and 38.03 J mol^?1 K^?1, respectively, which suggested that hydrophobic forces played a major role in stabilizing the HSA‐CYP complex. In addition, examination of molecular modeling indicated that CYP could bind to site I of HSA and that hydrophobic interaction was the major acting force, which was in agreement with binding mode studies. Copyright © 2012 John Wiley & Sons, Ltd.     

High prevalence of serum folate receptor autoantibodies in children with autism spectrum disorders

Abstract

Background: Supplementation of folic acid by pregnant mothers is thought to lower the risk of autism spectrum disorders (ASDs) in the offspring. Folic acid is taken up by cells via receptors with high affinity for folate and reduced folic acid derivatives. However, this is blocked by the presence of folate receptor autoantibodies (FRAA). Cerebral FRAA have been detected with high frequency in children with ASDs, suggesting the existence of a link between folic acid uptake and disease aetiology.

Methods: We investigated the frequency of FRAA in serum samples from 40 children with ASDs and 42 gender- and age-matched children with typical development (TD). Serum FRAA concentrations were measured by enzyme-linked immunosorbent assay.

Results: We found a significant difference in the frequency of serum FRAA in the two study cohorts. Serum FRAA were present in 77.5% (31/40) of children with ASDs compared with 54.8% (23/42) of TD children (p?=?0.03746, Fischer’s exact test). Thus, serum FRAA are more prevalent in children with ASDs than in TD children.

Conclusions: Our data suggest that children with ASDs may have defects in folic acid absorption that play a role in the onset of ASDs.