Journal of Medical Signals and Sensors
Volume:4 Issue: 2, Apr-Jun 2014

Diffusion weighted imaging uses the signal loss associated with the random thermal motion of water molecules in the presence of magnetic field gradients to derive a number of parameters that reflect the translational mobility of the water molecules in tissues. With a suitable experimental set-up, it is possible to calculate all the elements of the local diffusion tensor (DT) and derived parameters describing the behavior of the water molecules in each voxel. One of the emerging applications of the information obtained is an interpretation of the diffusion anisotropy in terms of the architecture of the underlying tissue. These interpretations can only be made provided the experimental data which are sufficiently accurate. However, the DT results are susceptible to two systematic error sources: On one hand, the presence of signal noise can lead to artificial divergence of the diffusivities. In contrast, the use of a simplified model for the interaction of the protons with the diffusion weighting and imaging field gradients (b matrix calculation), common in the clinical setting, also leads to deviation in the derived diffusion characteristics. In this paper, we study the importance of these two sources of error on the basis of experimental data obtained on a clinical magnetic resonance imaging system for an isotropic phantom using a state of the art single-shot echo planar imaging sequence. Our results show that optimal diffusion imaging require combining a correct calculation of the b-matrix and a sufficiently large signal to noise ratio.

Portable wireless neuro‑stimulators have been developed to facilitate long‑term cognitive and behavioral studies on the central nervous system in freely moving animals. These stimulators can provide precisely controllable input(s) to the nervous system, without distracting the animal attention with cables connected to its body. In this study, a low power backpack neuro‑stimulator was developed for animal brain researches that can provides arbitrary stimulus waveforms for the stimulation, while it is small and light weight to be used for small animals including rats. The system consists of a controller that uses an RF link to program and activate a small and light microprocessor‑based stimulator. A Howland current source was implemented to produce precise current controlled arbitrary waveform stimulations. The system was optimized for ultra‑low power consumption and small size. The stimulator was first tested for its electrical specifications. Then its performance was evaluated in a rat experiment when electrical stimulation of medial longitudinal fasciculus induced circling behavior. The stimulator is capable of delivering programmed stimulations up to ± 2 mA with adjusting steps of 1 µA, accuracy of 0.7% and compliance of 6 V. The stimulator is 15 mm × 20 mm × 40 mm in size, weights 13.5 g without battery and consumes a total power of only 5.l mW. In the experiment, the rat could easily carry the stimulator and demonstrated the circling behavior for 0.1 ms current pulses of above 400 µA. The developed system has a competitive size and weight, whereas providing a wide range of operation and the flexibility of generating arbitrary stimulation patterns ideal for long‑term experiments in the field of cognitive and neuroscience research.

We propose a novel approach for detecting precursors to epileptic seizures in intracranial electroencephalograms (iEEG), which is based on the analysis of system dynamics. In the proposed scheme, the largest Lyapunov exponent of the discrete wavelet packet transform (DWPT) of the segmented EEG signals is considered as the discriminating features. Such features are processed by a support vector machine (SVM) classifier to identify whether the corresponding segment of the EEG signal contains a precursor to an epileptic seizure. When consecutive EEG segments contain such precursors, a decision is made that a precursor is in fact detected. The proposed scheme is applied to the Freiburg dataset, and the results show that seizure precursors are detected in a time frame that unlike other existing schemes is very much convenient to patients, with sensitivity of 100% and negligible false positive detection rates.

This study is the first research investigating the possible effect of pulsed power signals on the characteristics of cortical bone by comparing the mechanical properties of this type of bone pre and post expose to pulsed power. A positive buck-boost converter was applied to generate adjustable high voltage, high frequency pulses (up to 500 V and 10 kHz). The functional behaviour of bone in response to pulse power excitation was elucidated by applying compressive loading until failure. The stiffness, failure stress (strength) and the total fracture energy (bone toughness) were determined as a measure of the main bone characteristics. Furthermore, an ultrasonic technique was applied to determine and comprise bone elasticity before and after pulse power stimulation. The elastic property of cortical bone samples appeared to remain unchanged following exposure to pulse power excitation for all three orthogonal directions obtained from ultrasonic technique and similarly from the compression test. Nevertheless, the compressive strength and toughness of bone samples were increased when they were exposed to 66 hours of high power pulsed electromagnetic field compared to the control samples. These results can suggest that the pulse power stimulation has influenced the arrangement or the quality of collagen fibrils with no significant effect on bone mineral content. The results also confirm that the indirect application of high power pulsed electromagnetic field at 500 V and 10 kHz through capacitive coupling method did not destroy the bone structure.

Detecting blood vessels is an important task in retinal image analysis. The task is more challenging with the presence of bright and dark lesions in retinal images. Here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. First, the negative impact of bright lesions is reduced by using k-means segmentation in a perceptive space. Then, a multi-scale line operator is utilized to detect vessels while ignoring most of the dark lesions, which have intensity structures different from the line-shaped vessels in retina. The proposed algorithm is tested on two publicly available STARE and DRIVE databases. The performance of the method is measured by calculating the area under the receiver operating characteristic (ROC) curve and the segmentation accuracy. The proposed method achieves 0٫9483 and 0٫9387 localization accuracy against STARE and DRIVE respectively.

Polymer gel dosimeter is the only accurate three dimensional (3D) dosimeter that can measure the absorbed dose distribution in a perfect 3D setting. Gel dosimetry by using optical computed tomography (OCT) has been promoted by several researches. In the current study, we designed and constructed a prototype OCT system for gel dosimetry. First, the electrical system for optical scanning of the gel container using a Helium-Neon laser and a photocell was designed and constructed. Then, the mechanical part for two rotational and translational motions was designed and step motors were assembled to it. The data coming from photocell was grabbed by the home-built interface and sent to a personal computer. Data processing was carried out using MATLAB software. To calibrate the system and tune up the functionality of it, different objects was designed and scanned. Furthermore, the spatial and contrast resolution of the system was determined. The system was able to scan the gel dosimeter container with a diameter up to 11 cm inside the water phantom. The standard deviation of the pixels within water flask image was considered as the criteria for image uniformity. The uniformity of the system was about ±0.05%. The spatial resolution of the system was approximately 1 mm and contrast resolution was about 0.2%. Our primary results showed that this system is able to obtain two-dimensional, cross-sectional images from polymer gel samples.

Histopathology slides are one of the most applicable resources for pathology studies. As observation of these kinds of slides even by skillful pathologists is a tedious and time‑consuming activity, computerizing this procedure aids the experts to have faster analysis with more case studies per day. In this paper, an automatic mitosis detection system (AMDS) for breast cancer histopathological slide images is proposed. In the proposed AMDS, the general phases of an automatic image based analyzer are considered and in each phase, some special innovations are employed. In the pre‑processing step to segment the input digital histopathology images more precisely, 2D anisotropic diffusion filters are applied to them. In the training segmentation phase, the histopathological slide images are segmented based on RGB contents of their pixels using maximum likelihood estimation. Then, the mitosis and non‑mitosis candidates are processed and hence that their completed local binary patterns are extracted object‑wise. For the classification phase, two subsequently non‑linear support vector machine classifiers are trained pixel‑wise and object‑wise, respectively. For the evaluation of the proposed AMDS, some object and region based measures are employed. Having computed the evaluation criteria, our proposed method performs more efficient according to f‑measure metric (70.94% for Aperio XT scanner images and 70.11% for Hamamatsu images) than the methods proposed by other participants at Mitos‑ICPR2012 contest in breast cancer histopathological images. The experimental results show the higher performance of the proposed AMDS compared with other competitive systems proposed in Mitos‑ICPR2012 contest.

Vessel extraction is a critical task in clinical practice. In this paper, we propose a new approach for vessel extraction using an active contour model by defining a novel vesselness‑based term, based on accurate analysis of the vessel structure in the image. To achieve the novel term, a simple and fast directional filter bank is proposed, which does not employ down sampling and resampling used in earlier versions of directional filter banks. The proposed model not only preserves the performance of the existing models on images with intensity inhomogeneity, but also overcomes their inability both to segment low contrast vessels and to omit non‑vessel structures. Experimental results for synthetic images and coronary X‑ray angiograms show desirable performance of our model.