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Small animal magnetic resonance microscopy (MRM) has been widely used today in computational neuroanatomy. Accurate identification of brain tissue in a mouse MRM is a critical fundamental step in neuroimaging processing, which is given less attention. This study presents an automatic skull-stripping technique based on template models and histogram analysis. Results were evaluated by calculating the Jaccard similarity index (JSI) and boundary concordance ratio (BCR) between the automatically segmented and manually traced brain volumes. Results demonstrate that this technique accurately extracts the brain volume (mean JSI = 97.1%, BC = 94.4%). The brain extraction method presented in this study will greatly facilitate analysis of neuroimaging studies of rodent animals in neurodegenerative diseases.

Small animal neuroimaging using magnetic resonance microscopy (MRM) has evolved significantly from understanding of imaging physics to widely use today as an important tool in computational neuroanatomy, while how to get optimal inhomogeneity correction for inhomogeneous mouse brain MRM has been given less attention.This present study investigates the ability of fine-tuning the nonparametric nonuniform intensity normalization (N3) technique to get optimal inhomogeneity correction of mouse brain MRM. Six mice were scanned on a 7-T scanner with a phased array surface coil of four elements. The N3 parameters such as stopping criteria, maximum iterations, down-sampling ratio, full width at half maximum, spline distance, and brain mask have been tuned to get optimal correction result. We used coefficient of variation of the white matter and joint variation to ascertain quantitatively the correction. The data were analyzed by two-way repeated measures analysis of variance and Bonferroni post hoc test.The quantitative outcomes show that brain mask and spline distance have a significant influence on correcting performance.The present study demonstrates the benefit of reducing the spline distance values to 25 and tighter mask. The finding can help researches to enhance precision in studies where mouse MRM need further registration or segmentation.

This study aims to investigate the regional changes in the early onset of blindness using the deformation-based morphometry (DBM) method.A total of 15 early blindness and 30 gender- and age-matched sighted control subjects were recruited for the study. Statistically significant changes in regional volume were analyzed using DBM through HAMMER registration. Using this technique, changes in regional tissue volume can be detected on the basis of the deformation field derived from the warping subject to the template image. A voxelwise estimation of the morphological differences between the two groups can be acquired after applying a threshold (P.001, uncorrected) to the statistic maps.Regions with enlarged volume in the brains of blind subjects are mainly localized in the left associated visual cortex, posterior cingulated cortex, and cerebellum, whereas volume reductions are primarily localized in the left early visual cortex.DBM is an effective method for detecting entire brain structural changes in blindness. Visual deprivation actually alters the local structural organization during the early critical periods of neurodevelopment. Volume increases outside the occipital lobe detected with DBM may suggest compensatory adaptations.

This paper proposes the topological conjugacy classification of two-dimensional binary cellular automata (2D CA) with von Neumann neighborhood. By exploiting four fundamental homeomorphisms in two-dimensional symbolic sequence space, it actually partitions the global mappings, not only of the additive rules, but also of all rules, in the sense that different mappings in the same global equivalence are mutually topologically conjugate. Such classification makes it available to directly compute equivalent rules for a given rule.

The main purpose of this paper was to validate whether the method using features of ultrasonic radio frequency signal (URFS) is effective for non-invasive monitoring in microwave ablation. A total of 15 fresh in vitro porcine livers were experimented. Features of amplitude integral, energy, sum of absolute value of difference (SAD) integral, time-shift and attenuation coefficient of URFS were extracted. Changing rules of these features and the relationships between time-shift, attenuation coefficient and tissue temperature were analyzed. Experimental results showed that maximums of amplitude integral, energy and SAD integral occur at the temperature within 50-60?C. In addition, there was a linear relationship between time-shift and tissue temperature within 60oC and the ultrasonic attenuation coefficient increased with the temperature rising. Therefore, features of URFS can reflect the change of tissue property and may be used in the non-invasive monitoring of microwave ablation in the future.

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Fetal ECG Extraction has the vital significance for fetal monitoring. This paper introduced a method of extracting fetal ECG based on adaptive linear neural network. The method can be realized by training a small quantity of data. In addition, a better result can be achieved by improving neural network structure. Thus, more easily identified fetal ECG can be extracted. Experimental results show that the adaptive linear neural network can be used to extract fetal ECG from maternal abdominal signal effectively. What's more, a clearer fetal ECG can be extracted by improving neural network structure.

Adipose tissue segmentation of thigh magnetic resonance images is very valuable in diagnosis of metabolic syndrome and metabolic dysfunction. But it's more difficult to segment the subcutaneous fat from inter-muscular fat. In this paper, a method combining the level-set and fuzzy C-means algorithms is proposed. The experimental results show that the subcutaneous fat tissue, inter-muscular fat tissue and other tissues of thigh can be segmented successfully using this method.

Microwave (MW) ablation is a minimally invasive therapeutic strategy for the local treatment of solid malignancies that has received much attention over the past few years. It is very important to detect and evaluate lesions generated by MW during treatment procedures. This study describes one new ultrasonic imaging technique to characterize lesions based on estimation of relative changes in tissue properties derived from backscattered RF data. A single microwave heating antenna was used to produce coagulation in vitro pig liver tissues. The RF signals were recorded as outputs from a modified diagnostic ultrasound system. The integrated backscatter values, which can be used as an indicator of the microstructure and backscattering property of tissues, were calculated in water-bath experiment and MW treatment. The rule of change in integrated backscatter values with temperature has been analyzed by statistics through water-bath experiment. The integrated backscatter ratio values were subsequently used to form images revealing the lesion areas. It is possible using ultrasonic integral backscatter to monitor microwave coagulation. The result shows that this approach can be used to identify the normal and coagulated tissue caused by temperature rise and provide the information of tissue damage.

3D shape reconstruction of the liver from its 2D cross-sections improves the surgeon's knowledge of liver anatomy and makes even more complicated liver surgery safe, which can be employed to aid clinical practice as an alternative tool. In this paper, a new method for 3D reconstruction of liver is proposed. It mainly consists of three steps: liver auto-segmentation, surface reconstruction and surface rendering. Firstly, an effective automatic segmentation method based on graph-theory is proposed for extracting liver. Then, NMC algorithm based on a combination of MC and Cuberille algorithms is applied to accomplish surface reconstruction of liver. Finally, surface rendering of liver is implemented by 3D graphics library OpenGL. The method mentioned above is being tested on numerous experiments of 3D reconstruction of liver and results are promising.

Many studies have already demonstrated structural brain differences among different patient populations using the morphometric analysis techniques. Voxel-based morphometry (VBM) and deformation-based morphometry (DBM) are the two widely used methods. This paper mainly compared the difference of the two methods and analyzed the reason why many differences exist in the experimental results focused on the same disease. The first-episode schizophrenia's brain structures were analyzed using both VBM and DBM. The results based on the two methods exactly evaluated our analysis and provided pathological evidence for the first-episode schizophrenia.

The dynamical behaviors of elementary cellular automata rules are investigated from the viewpoint of symbolic dynamics in the space of bi-infinite symbolic sequences. It turns out the topologically conjugate equivalences between rules by applying blocking transformation and releasing transformation. Based on this result, the topological chaos of rule 22 is detailedly characterized; that is, rule 22 is topologically mixing and possesses the positive topological entropy on two subsystems. Thus, rule 22 is chaotic in the sense of both Li-Yorke and Devaney on these two subsystems. Finally, it is worth mentioning that the method presented in this paper is also applicable to other blocking transformation equivalences therein.

Image segmentation is a focused issue in image processing. Especially, brain segmentation is a key problem in neuroscience. In this study, our aim is to segment the real MR image into gray matter, white matter and cerebrospinal fluid. Several methods were compared. However, traditional methods such as fuzzy c-means, mixture Gaussian model can't achieve a satisfied result successfully. Markov random field (MRF) model is used and the experimental results show that MRF method is robust to noise which can achieves a perfect segmentation.

Microwave ablation (MA) is popular as a minimally invasive, painless and effective oncological treatment. The paper presents an approach of characterizing the thermal coagulation during microwave ablation using B-mode ultrasound image textures and pattern recognition technique. During the MA treatment, the series of B-mode ultrasound images were obtained. Textures of different ROIs such as gray level histogram and gray level co-occurrence matrices from the obtained ultrasound images were extracted separately. And then these textures were classified by support vectors machine (SVM). The experimental results have shown that the textures of coagulated and non-coagulated region have significant differences. The classification accuracy of SVM by 19 parameters is 0.9528. The method described in this paper is an effective way to realize thermal coagulation monitoring using texture features of B-mode ultrasound images.

Many studies have already demonstrated structural brain differences among different patient populations using the morphometric analysis techniques. Voxel-based morphometry (VBM) and deformation-based morphometry (DBM) are the two widely used methods. This paper mainly compared the difference of the two methods and analyzed the reason why many researches exist differences in the experimental results focused on the same disease. The blind men's brain structures were analyzed using both VBM and DBM. The results based on the two methods exactly evaluated our analysis and provided evidence for the functional relevance of cross-modal plasticity studies.

Voxel based morphometry (VBM) methods are used to detect the difference in brain structures between the posttraumatic stress disorder (PTSD) sufferers and the normal controls. Standard VBM method can detect the difference of the gray matter or white matter densities while the optimized VBM method can detect the difference of gray matter or white matter volumes in the whole brain. The experiments showed that for the patient group, gray matter density or volumes significantly increased in the right frontal lobe, middle frontal gyrus, vermis, left caudate and parietal lobe, compared with the normal controls. However, in the left frontal lobe and middle frontal gyrus, gray matter density significantly decreased. There is no significant difference in white matter between the two groups. These results are consistent with those of the fMRI, which not only provide the evidence for further study of the pathogeny in PTSD but also validate the efficiency of the VBM methods for detecting the difference in the whole brain structure.

[Objective] To implement a computer aided system for liver hyperthermia treatment planning. [Methods] VC++ 6.0 and MITK(Medical Imaging ToolKit) were chosen as the development platform for a good efficiency in both runtime and development phases. Based on these, the system framework was designed. By Amira and ANSYS, the system could be initially implemented. [Results] The designed system can be applied for liver hyperthermia treatment planning, and was expected to guide the process of clinical operation by further improvement. [Conclusion] The system can offer scientific and reliable evidences for hyperthermia treatment planning, and it can make hyperthermia treatment parameters quantificational and treatment process settled. All of these can reduce the dependent degree to clinical experience for doctors.

Many studies have shown the functional relevance of cross-modal plasticity in blind men. However, few researches have focused on whether such functional plasticity is associated with macroscopic changes of structural anatomy in brain regions. Fortunately, deformation based morphometry (DBM) provides an important tool for the computational anatomy research. In this study we detected the changes of regional volume in brain structures between the blind men and normal controls with DBM method. Information of the difference is derived from the deformation field acquired during HAMMER non-rigid registration. The experimental results show that the regions expanded in the blind men’s brain are located at Brodmann 19,31 while the contracted regions located at Brodmann 17,18. This research is very helpful to discover the relationship between structural anatomy and functional data of blind men at a macroscopic level from neuroimaging perspective.

Constitutive activation of Notch signaling was found in melanoma cells. Using siRNA specifically knocking down Notch co-activator MAML1 blocked Notch down stream transcriptional repressor Hey1 expression, significantly upregulated TweakR and CCL2 mRNA and protein expression in melanoma cell line M624. Exogenous Tweak stimulated high level CCL2 production in siMAML transfected M624 cells, which was critically dependent on Tweak-TweakR ligation. CCL2 produced by siMAML1 transfected M624 stimulated with exogenous Tweak was functional chemoattractant to activated monocytes. This study supports targeting Notch signaling using small siRNA in melanoma cells may increase immune cell recruitment and restore natural immune surveillance in tumor microenvironment.

The pathological reason for schizophrenia is still unknown to date. Fortunately, deformation based morphometry (DBM) provides an important tool for the computational anatomy research. In this study we detected the changes of regional volume in brain structures between the first episode schizophrenia (FES) and normal controls with DBM method. Information of the difference is derived from the deformation field acquired during HAMMER non-rigid registration. The experimental results show that contracted regions are mainly located in Brodmann42 and right occipital lobe while the expanded regions are located in Brodmann38, 21, left middle frontal gyrus and left cerebellum. This research is very helpful to make the cause of changes in schizophrenia's brain structures clear.

As a transmembrane chemokine, CXCL16 has been detected in various tissues and organs under normal and pathological conditions, it also plays an important role in macrophages/dendritic cells (DC) and T cell interactions and trafficking during inflammation and immune responses. LysoPtdOH, a bioactive lipid mediator has been indicated to regulate DC and epithelial functions during wound healing and inflammation responses. However, the direct link of CXCL16 expression with lysoPtdOH has not been established. Using monocyte-derived macrophages/DC (MoDC), we investigated the roles of lysoPtdOH in CXCL16 production and cell surface presentation. We found that macrophages/MoDC constitutively express and secrete CXCL16, lysoPtdOH significantly enhanced CXCL16 protein production stimulated with lipopolysaccharide (LPS) by more than twofold, which was reflected by increased mRNA transcription by 64-fold. Production of CXCL16 increased by lysoPtdOH and LPS from macrophages was inhibited around 70% by Pertussis toxin (G(i/o) specific inhibitor), exoC3 (Rho specific inhibitor), and pyrrolidine dithiocarbamate (the NF-kappaB-dependent pathway inhibitor) separately. LysoPtdOH treatment increased macrophages' chemotactic activity to activated T cells. The soluble form of CXCL16 produced by macrophages/MoDC was functionally chemoattractive to T cells.

Tomato bacterial wilt caused by Ralstonia solanacearum bacterium is a severe problem in Southern China, where relatively high environmental temperatures commonly prevails during the crop seasons. Previous research has indicated that bacterial wilt disease incidence generally increases during the warm months of summer leading to reduced tomato yield. Moreover, the efficacy of bio-organic fertilizers (BOFs)-organic compost fortified with pathogen-suppressive bacteria-is often lost during the periods of high environmental temperatures. Here we studied if the disease incidence could be reduced and the BOF performance enhanced by simply preponing and postponing the traditional seedling transplantation times to avoid tomato plant development during periods of high environmental temperature. To this end, a continuous, two-year field experiment was conducted to evaluate the performance of BOF in two traditional (late-spring [LS] and early-autumn [EA]) and two alternative (early-spring [ES] and late-autumn [LA]) crop seasons. We found that changing the transplantation times reduced the mean disease incidence from 33.9% (LS) and 54.7% (EA) to 11.1% (ES) and 7.1% (LA), respectively. Reduction in disease incidence correlated with the reduction in R. Solanacearum pathogen density in the tomato plant rhizosphere and stem base. Applying BOF during alternative transplantation treatments improved biocontrol efficiency from 43.4% (LS) and 3.1% (EA) to 67.4% (ES) and 64.8% (LA). On average, the mean maximum air temperatures were positively correlated with the disease incidence, and negatively correlated with the BOF biocontrol efficacy over the crop seasons. Crucially, even though preponing the transplantation time reduced the tomato yield in general, it was still economically more profitable compared to LS season due to reduced crop losses and relatively higher market prices. Preponing and postponing traditional tomato transplantation times to cooler periods could thus offer simple but effective way to control R. solanacearum disease outbreaks.

Along with the development of medical assistant techniques, brain network is becoming an important tool for analysing brain nervous system diseases and researching the pathogenesis of diseases. Epilepsy is one of the common brain nervous system diseases, and it has been popular in researches. Idiopathic generalized epilepsy (IGE) is a set of epilepsy syndrome with no other obvious causes besides genetic factors, accounting for about 30% of all kinds of epilepsies. This article summarizes recent progresses in IGE foci detection based on brain network analysis, mainly focusing on the applications in IGE, including functional and structural brain network. Moreover, trends in future development of brain network applications in IGE have been

A high resolution non-contact optical sensor for surface roughness has been developed. The principle of the sensor is based on the dynamic focusing in combination with astigmatic method, a popular focus-error detection approach. The measuring principle of the method and the optical system arrangement are described in detail firstly. Then, a mathematical model of the system based on Fresnel diffraction theory is derived. According to the model, a plot of the focus error signal (FES) versus the misfocusing is easily got. The effect of various system parameters on the FES is discussed, and this is very useful for system optimization. Besides, results of numerical calculation, namely optical field distributions on the quadrant photodetector surface at different misfocusing, are presented.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.