Studying the Effects of Cold Plasma Phosphorus Using Physiological and Digital Image Processing Techniques.

The goal of this study is to see how cold plasma affects rabbit bone tissue infected with osteoporosis. The search is divided into three categories: control, infected, and treated. The rabbits were subjected to cold plasma for five minutes in a room with a microwave plasma voltage of "175 V" and a gas flow of "2." A histopathological photograph of infected bone cells is obtained to demonstrate the influence of plasma on infected bone cells, as well as the extent of destruction and effect of plasma therapy before and after exposure. The findings of the search show that plasma has a clear impact on Ca and vitamin D levels. In the cold plasma, the levels of osteocalcin and alkali phosphates (ALP) respond as well. Image processing techniques (second-order gray level matrix) with textural elements are employed as an extra proof. The outcome gives good treatment indicators, and the image processing result corresponds to the biological result.

Visual Sensor Image Analysis and Massage Techniques to Prevent and Treat Common Injuries of Sports Dance Practitioners.

In recent years, the performance of sports dance in China has become better and better. Naturally, the technical requirements for this dance are getting higher and higher, and the number and intensity of training have also increased, which has led to increasing injuries in sports dance. This article is based on visual sensor images to analyze and study the common injuries and prevention of sports dance practitioners. It is aimed at providing a certain reference basis for athletes' injuries, so that dance practitioners and coaches can better master sports dance training and teaching. Injury-related rules and prevention reduce the injury rate. This article puts forward the related technology of a visual sensor image and applies its technology to the prevention and research of common injuries in sports dance. At the same time, it analyzes the causes of sports dance practitioners' injuries and seeks economical and affordable massage techniques for prevention, and the method of treatment provides protection for dance practitioners. The experimental results in this article show that the Tuina group cured 15 subjects, 41 subjects were markedly effective, 13 subjects were improved, and 6 subjects were unhealed. The total effective rate was 92%.

Preventing Loss of Independence through Exercise (PLIÉ): A Pilot Trial in Older Adults with Subjective Memory Decline and Mild Cognitive Impairment.

BACKGROUND: Preventing Loss of Independence through Exercise (PLIÉ) is a group movement program initially developed for people with mild-to-moderate dementia that integrates principles from several well-established traditions to specifically address the needs of people with cognitive impairment. OBJECTIVE: To investigate whether PLIÉ would benefit cognitive and behavioral outcomes and functional brain connectivity in older adults with milder forms of cognitive impairment. METHODS: Participants (≥55 y) with subjective memory decline (SMD) or mild cognitive impairment (MCI) were assessed with tests of cognitive and physical function, self-report questionnaires, and resting state functional magnetic resonance imaging (rs-fMRI) on a 3 Tesla scanner before and after participating in twice weekly PLIÉ classes for 12 weeks at the San Francisco Veterans Affairs Medical Center. RESULTS: Eighteen participants completed the pre-post intervention pilot trial. We observed significant improvements on the Alzheimer's Disease Assessment Scale cognitive subscale (ADAS-cog; effect size 0.34, p = 0.002) and enhanced functional connections between the medial prefrontal cortex (mPFC) and other nodes of the default mode network (DMN) after PLIÉ. Improvements (i.e., lower scores) on ADAS-cog were significantly correlated with enhanced functional connectivity between the mPFC and left lateral parietal cortex (Spearman's ρ= -0.74, p = 0.001) and between the mPFC and right hippocampus (Spearman's ρ= -0.83, p = 0.001). After completing PLIÉ, participants reported significant reductions in feelings of social isolation and improvements in well-being and interoceptive self-regulation. CONCLUSION: These preliminary findings of post-PLIÉ improvements in DMN functional connectivity, cognition, interoceptive self-regulation, well-being and reduced feelings of social isolation warrant larger randomized, controlled trials of PLIÉ in older adults with SMD and MCI.

A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops.

Traditional methods to measure spatio-temporal variations in biomass rely on a labor-intensive destructive sampling of the crop. In this paper, we present a high-throughput phenotyping approach for the estimation of Above-Ground Biomass Dynamics (AGBD) using an unmanned aerial system. Multispectral imagery was acquired and processed by using the proposed segmentation method called GFKuts, that optimally labels the plot canopy based on a Gaussian mixture model, a Montecarlo based K-means, and a guided image filtering. Accurate plot segmentation results enabled the extraction of several canopy features associated with biomass yield. Machine learning algorithms were trained to estimate the AGBD according to the growth stages of the crop and the physiological response of two rice genotypes under lowland and upland production systems. Results report AGBD estimation correlations with an average of r = 0.95 and R2 = 0.91 according to the experimental data. We compared our segmentation method against a traditional technique based on clustering. A comprehensive improvement of 13% in the biomass correlation was obtained thanks to the segmentation method proposed herein.

Spatiotemporal Characterizations of Spontaneously Beating Cardiomyocytes with Adaptive Reference Digital Image Correlation.

We developed an Adaptive Reference-Digital Image Correlation (AR-DIC) method that enables unbiased and accurate mechanics measurements of moving biological tissue samples. We applied the AR-DIC analysis to a spontaneously beating cardiomyocyte (CM) tissue, and could provide correct quantifications of tissue displacement and strain for the beating CMs utilizing physiologically-relevant, sarcomere displacement length-based contraction criteria. The data were further synthesized into novel spatiotemporal parameters of CM contraction to account for the CM beating homogeneity, synchronicity, and propagation as holistic measures of functional myocardial tissue development. Our AR-DIC analyses may thus provide advanced non-invasive characterization tools for assessing the development of spontaneously contracting CMs, suggesting an applicability in myocardial regenerative medicine.

Intravoxel incoherent motion MRI as a biomarker of sorafenib treatment for advanced hepatocellular carcinoma: a pilot study.

BACKGROUND: To evaluate the association between the therapeutic outcomes of sorafenib for advanced hepatocellular carcinoma (HCC) and the parameters of intravoxel incoherent motion (IVIM). METHODS: Nine patients were evaluated prospectively. All patients were Child-Pugh score A. The mean dimension of the lesion was 32 mm (range: 15-74 mm). MR images were obtained using a 1.5-Tesla superconductive MRI system. Diffusion-weighted imaging was performed under breath-holding using b-values of 0, 50, 100, 150, 200, 400, and 800 s/mm(2). The following IVIM parameters were calculated: apparent diffusion coefficient, true diffusion coefficient (DC), pseudo-diffusion coefficient, and perfusion fraction. MRI was performed before treatment and at 1, 2, and 4 weeks after beginning treatment. Tumor response at 4 weeks was assessed by CT or MRI using modified RECIST. IVIM parameters of the treatment responders and non-responders were compared. RESULTS: The DC of responders at baseline was significantly higher than that of the non-responders. The sensitivity and specificity, when a DC of 0.8 (10(-3) mm(2)/s) or higher was considered to be a responder, were 100 % and 67 %, respectively. No significant differences were found in the other parameters between the responders and the non-responders. All IVIM parameters of the responders and non-responders did not change significantly after treatment. CONCLUSION: The DC before treatment may be a useful parameter for predicting the therapeutic outcome of sorafenib for advanced HCC.

Infrared machine vision system for the automatic detection of olive fruit quality.

External quality is an important factor in the extraction of olive oil and the marketing of olive fruits. The appearance and presence of external damage are factors that influence the quality of the oil extracted and the perception of consumers, determining the level of acceptance prior to purchase in the case of table olives. The aim of this paper is to report on artificial vision techniques developed for the online estimation of olive quality and to assess the effectiveness of these techniques in evaluating quality based on detecting external defects. This method of classifying olives according to the presence of defects is based on an infrared (IR) vision system. Images of defects were acquired using a digital monochrome camera with band-pass filters on near-infrared (NIR). The original images were processed using segmentation algorithms, edge detection and pixel value intensity to classify the whole fruit. The detection of the defect involved a pixel classification procedure based on nonparametric models of the healthy and defective areas of olives. Classification tests were performed on olives to assess the effectiveness of the proposed method. This research showed that the IR vision system is a useful technology for the automatic assessment of olives that has the potential for use in offline inspection and for online sorting for defects and the presence of surface damage, easily distinguishing those that do not meet minimum quality requirements.

The day-after effect: long term, Hebbian-like restructuring of resting-state fMRI patterns induced by a single epoch of cortical activation.

During rest, the cerebral cortex displays rich, coordinated patterns of spontaneous activity. The mechanism that shapes these patterns is largely unknown. Here we demonstrate that a Hebbian-like, sustained process plays a role in focusing these coherent patterns. Human subjects used an fMRI-based neurofeedback (NF) paradigm to intensely activate the dorsal anterior cingulate cortex for a single epoch (30 min). Resting-state correlations between all of the cortical voxels' BOLD time courses (functional connectivity) were mapped before, immediately after, and one day after the NF session. We found that the single epoch of cortical activation induced a lasting restructuring of the functional connections according to a Hebbian-like rule. Therefore, the change (increase and decrease) in functional connectivity strength of cortical voxels during rest reflected the level of their prior coactivation during the NF epoch. Interestingly, the effect was significantly enhanced 1 d after the NF activation epoch. The effect was evident in each subject individually, indicating its potential as a diagnostic window into the personal history of prior brain activations of both healthy and abnormal individuals.

The accuracy of three-dimensional model generation. What makes it accurate to be used for surgical planning?

Computerized treatment planning is routinely used in cranio-maxillofacial applications. For these therapeutic applications, it is of critical importance to have a precise model of the structures in question. Improved imaging techniques and advances in software engineering have moved three-dimensional (3D) computer models from the research and development area into routine clinical application. The importance of high-resolution source imaging is well understood by surgeons. The influence of image processing is poorly understood in the surgical community and we hypothesize that this may be a source of significant error. We evaluated the workflow for creating a virtual model using computed tomography data, and the impact that image processing decisions have on final virtual model accuracy. We chose to create a model of the dental surface since it is one of the most complex structures in the area. Individual image processing steps are explained and the magnitudes of their influence on model quality are demonstrated and compared. This study demonstrates that inappropriate image processing can introduce errors of similar magnitude as the use of inadequate source data. Finally, the study shows that errors caused by inappropriate image processing amplify the inaccuracies of low-resolution source imagery and eliminate the benefits of high-resolution source imaging.

The effect of surrounding conditions on pixel value of cone beam computed tomography.

OBJECTIVE: The purpose of this study was to evaluate the reliability of pixel value in CBCT, especially with regard to the effect of surrounding objects that are presented outside the field of view (FOV). MATERIALS AND METHODS: This experiment used the GE Hi-Speed QXi, a multidetector helical computed tomography (MDCT) scanner, and the 3D Accuitomo FPD 8, a cone beam computed tomography (CBCT) scanner. Two types of phantoms were used, both of which contained Lipiodol Ultra Fluid (Lipiodol UF). The type A phantom was a target phantom for pixel value measurement while type B was used for the surrounding environment. For CBCT, the type A phantom was placed in a water bath, and 4 types of surrounding environmental conditions were created: (1) no other phantom present, (2) phantom type B also within the FOV, (3) half of phantom type B within the FOV, (4) phantom type B entirely outside the FOV but within the path of x-rays aimed at phantom A. RESULTS: In MDCT, pixel value (CT number) showed an almost linear correlation with the concentration of Lipiodol UF. In CBCT, on the other hand, pixel value was not linearly correlated with Lipiodol UF concentration. The position of the type B phantom affected pixel values in images of the type A phantom. CONCLUSIONS: Pixel value in CBCT may be affected by various conditions such as beam hardening and surrounding materials, and is therefore not reliable. Caution is essential when pixel values in CBCT are used to estimate bone density at potential implant sites.

Complex-number representation of informed basis functions in general linear modeling of Functional Magnetic Resonance Imaging.

Functional Magnetic Resonance Imaging (fMRI), measuring Blood Oxygen Level-Dependent (BOLD), is a widely used tool to reveal spatiotemporal pattern of neural activity in human brain. Standard analysis of fMRI data relies on a general linear model and the model is constructed by convolving the task stimuli with a hypothesized hemodynamic response function (HRF). To capture possible phase shifts in the observed BOLD response, the informed basis functions including canonical HRF and its temporal derivative, have been proposed to extend the hypothesized hemodynamic response in order to obtain a good fitting model. Different t contrasts are constructed from the estimated model parameters for detecting the neural activity between different task conditions. However, the estimated model parameters corresponding to the orthogonal basis functions have different physical meanings. It remains unclear how to combine the neural features detected by the two basis functions and construct t contrasts for further analyses. In this paper, we have proposed a novel method for representing multiple basis functions in complex domain to model the task-driven fMRI data. Using this method, we can treat each pair of model parameters, corresponding respectively to canonical HRF and its temporal derivative, as one complex number for each task condition. Using the specific rule we have defined, we can conveniently perform arithmetical operations on the estimated model parameters and generate different t contrasts. We validate this method using the fMRI data acquired from twenty-two healthy participants who underwent an auditory stimulation task.

Applications of 'TissueQuant'- a color intensity quantification tool for medical research.

This paper demonstrates the use of TissueQuant - an image analysis tool for quantification of color intensities which was developed for use in medical research where the stained biological specimen such as tissue or antigen needs to be quantified. TissueQuant provides facilities for user interaction to choose and quantify the color of interest and its shades. Gaussian weighting functions are used to provide a color score which quantifies how close the shade is to the user specified reference color. We describe two studies in medical research which use TissueQuant for quantification. The first study evaluated the effect of petroleum-ether extract of Cissus quadrangularis (CQ) on osteoporotic rats. It was found that the analysis results correlated well with the manual evaluation, p < 0.001. The second study evaluated the nerve morphometry and it was found that the adipose and non adipose tissue content was maximum in radial nerve among the five nerves studied.

Demonstration of decreased gray matter concentration in the midbrain encompassing the dorsal raphe nucleus and the limbic subcortical regions in major depressive disorder: an optimized voxel-based morphometry study.

BACKGROUND: Previous neuroimaging studies in patients with major depressive disorder (MDD) have reported changes in several brain areas, such as the medial and dorsolateral orbital cortex, amygdala, hippocampus, and basal ganglia. However, the results of these studies are inconsistent, and relatively few studies have been conducted using voxel-based morphometry (VBM) to detect gray matter concentration (GMC) abnormalities in patients with MDD. METHODS: We examined 47 MDD patients and 51 healthy controls to investigate structural abnormalities using a 1.5 T magnetic resonance imaging system, which was normalized to a customized T1 template and segmented with optimized VBM. Analysis of covariance with age and gender as covariates was adopted for the VBM statistics; the level of statistical significance was set at P<0.05 for the corrected false discovery rate. RESULTS: Decreased GMC was found in MDD patients in the bilateral amygdalae, hippocampi, fusiform gyri, lingual gyri, insular gyri, middle-superior temporal gyri, thalami, cingulate gyri, the central lobule of the cerebellum, and the midbrain encompassing the dorsal raphe nuclei (DRN). LIMITATIONS: Half of our study subjects were taking antidepressants. This may have been a potential confounding factor if any of the medications affected cortical volume. CONCLUSIONS: The results suggest that the GMC of several regions associated with emotion regulation was lower in MDD patients. In particular, we found decreased GMC in the DRN. These findings may provide a better understanding of the anatomical properties of the neural mechanisms underlying the etiology of MDD.

Digital holographic microscopy by use of surface plasmon resonance for imaging of cell membranes.

A technique called surface plasmon resonance digital holographic microscopy (SPRDHM) for optical imaging of cell membranes is proposed. The intensity and phase distributions of the reflected light that is modulated by the cell membrane in surface plasmon resonance can be simultaneously obtained. The imaging principle and capability are theoretically analyzed and demonstrated by experiments. In addition, the technique is compared with total internal reflection digital holographic microscopy (TIRDHM) in theory and experiment, respectively. The results show that the SPRDHM technique is better in spatial resolution and phase sensitivity than the TIRDHM technique for imaging of cell membranes.

Novel automatic endotracheal position confirmation system: mannequin model algorithm evaluation.

OBJECTIVE: A novel endotracheal intubation accurate positioning confirmation system based on image classification algorithm is introduced and evaluated using a mannequin model. METHODS: The system comprises a miniature complementary metal oxide silicon sensor (CMOS) attached to the tip of a semi rigid stylet and connected to a digital signal processor (DSP) with an integrated video acquisition component. Video signals acquired and processed by an algorithm implemented on the processor. During mannequin intubations, video signals were continuously recorded. A total of 10 videos were recorded. From each video, 7 images of esophageal intubation and 8 images of endotracheal intubation (in which the carina could be clearly seen) were extracted, yielding a total of 150 images taken from arbitrary positions and angles which were processed by the confirmation algorithm. RESULTS: The performance of the confirmation algorithm was evaluated using a leave-one-out method: in each iteration, 149 images were used to train the system and estimate the models, and the remaining image was used to test the system. This process was repeated 150 times such that each image participated once in testing. The system correctly identified 80 out of 80 endotracheal intubations and 70 out of 70 esophageal intubations. CONCLUSIONS: This fully automatic image recognition system was used successfully to discriminate airway carina and non-carina endotracheal tube positioning. The system had a 100% success rate using a mannequin model and therefore further investigation including live tissue model and human research should follow.

An integrated one-step system to extract, analyze and annotate all relevant information from image-based cell screening of chemical libraries.

Here we report the development and validation of a complete solution to manage and analyze the data produced by image-based phenotypic screening campaigns of small-molecule libraries. In one step initial crude images are analyzed for multiple cytological features, statistical analysis is performed and molecules that produce the desired phenotypic profile are identified. A naïve Bayes classifier, integrating chemical and phenotypic spaces, is built and utilized during the process to assess those images initially classified as "fuzzy"-an automated iterative feedback tuning. Simultaneously, all this information is directly annotated in a relational database containing the chemical data. This novel fully automated method was validated by conducting a re-analysis of results from a high-content screening campaign involving 33 992 molecules used to identify inhibitors of the PI3K/Akt signaling pathway. Ninety-two percent of confirmed hits identified by the conventional multistep analysis method were identified using this integrated one-step system as well as 40 new hits, 14.9% of the total, originally false negatives. Ninety-six percent of true negatives were properly recognized too. A web-based access to the database, with customizable data retrieval and visualization tools, facilitates the posterior analysis of annotated cytological features which allows identification of additional phenotypic profiles; thus, further analysis of original crude images is not required.

Evaluation of rapid dual-tracer (62)Cu-PTSM + (62)Cu-ATSM PET in dogs with spontaneously occurring tumors.

We are developing methods for imaging multiple PET tracers in a single scan with staggered injections, where imaging measures for each tracer are separated and recovered using differences in tracer kinetics and radioactive decay. In this work, signal separation performance for rapid dual-tracer (62)Cu-PTSM (blood flow) + (62)Cu-ATSM (hypoxia) tumor imaging was evaluated in a large animal model. Four dogs with pre-existing tumors received a series of dynamic PET scans with (62)Cu-PTSM and (62)Cu-ATSM, permitting evaluation of a rapid dual-tracer protocol designed by previous simulation work. Several imaging measures were computed from the dual-tracer data and compared with those from separate, single-tracer imaging. Static imaging measures (e.g. SUV) for each tracer were accurately recovered from dual-tracer data. The wash-in (k(1)) and wash-out (k(2)) rate parameters for both tracers were likewise well recovered (r = 0.87-0.99), but k(3) was not accurately recovered for PTSM (r = 0.19) and moderately well recovered for ATSM (r = 0.70). Some degree of bias was noted, however, which may potentially be overcome through further refinement of the signal separation algorithms. This work demonstrates that complementary information regarding tumor blood flow and hypoxia can be acquired by a single dual-tracer PET scan, and also that the signal separation procedure works effectively for real physiologic data with realistic levels of kinetic model mismatch. Rapid multi-tracer PET has the potential to improve tumor assessment for image-guide therapy and monitoring, and further investigation with these and other tracers is warranted.

Detecting auditory cortex: a comparison of SPM and WSPM.

Nowadays, statistical parametric mapping (SPM) is the most widely-used method for the analysis of fMRI data. As the progress of SPM, some researchers have proposed WSPM, a new method based on wavelet transform. The advantage of WSPM is that it can not only reduce the spatial bias of SPM, but also shows the closer result to the true active areas. In this paper, there are eight sets of fMRI data stimulated by voice, from which we want to figure out the active brain areas under the stimulation. To confirm the active areas, we used the two methods based on different smoothing methods and made comparison. WSPM was showed to have stronger control of type-I error (false positives) than SPM.

WSPM: wavelet-based statistical parametric mapping.

Recently, we have introduced an integrated framework that combines wavelet-based processing with statistical testing in the spatial domain. In this paper, we propose two important enhancements of the framework. First, we revisit the underlying paradigm; i.e., that the effect of the wavelet processing can be considered as an adaptive denoising step to "improve" the parameter map, followed by a statistical detection procedure that takes into account the non-linear processing of the data. With an appropriate modification of the framework, we show that it is possible to reduce the spatial bias of the method with respect to the best linear estimate, providing conservative results that are closer to the original data. Second, we propose an extension of our earlier technique that compensates for the lack of shift-invariance of the wavelet transform. We demonstrate experimentally that both enhancements have a positive effect on performance. In particular, we present a reproducibility study for multi-session data that compares WSPM against SPM with different amounts of smoothing. The full approach is available as a toolbox, named WSPM, for the SPM2 software; it takes advantage of multiple options and features of SPM such as the general linear model.

Substantial thalamostriatal dopaminergic defect in Unverricht-Lundborg disease.

PURPOSE: Unverricht-Lundborg disease (ULD) is currently classified as progressive myoclonus epilepsy. Myoclonus, the characteristic symptom in ULD, suggests that dopamine neurotransmission may be involved in the pathophysiology of ULD. Our purpose was to examine brain dopaminergic function in ULD patients. METHODS: Four genetically and clinically diagnosed ULD patients and eight healthy controls were scanned with [(11)C]raclopride-PET. PET images were coregistered to individual 1.5 T MR images and region-of-interest analysis was performed for the striatum and thalamus. Standardized uptake values and individual voxel-wise binding potential maps of the patients and controls were also analyzed. RESULTS: ULD patients had markedly higher (31-54%) dopamine D2-like receptor availabilities than healthy controls in both the striatum and the thalamus. The proportionally highest binding potentials were detected in the thalamus. There were no significant differences in the cerebellar uptake of [(11)C]raclopride in ULD patients versus healthy controls. Voxel-based results were in accordance with the region-of-interest analysis. CONCLUSIONS: These results suggest that dopaminergic modulation at the level of the striatum and thalamus could be a crucial factor contributing to the symptoms of ULD. In the light of our data, we propose that ULD with dopamine dysfunction and dyskinetic symptoms shares certain pathophysiological mechanisms with classical movement disorders. Future studies are therefore warranted to study the effect of dopaminergic pharmacotherapy in ULD.