Average Gray Value Research Articles

Automated brain tumor segmentation in magnetic resonance imaging based on sliding-window technique and symmetry analysis

Background Brain tumor segmentation from magnetic resonance imaging (MRI) is an important step toward surgical planning, treatment planning, monitoring of therapy. However, manual tumor segmentation commonly used in clinic is time-consuming and challenging, and none of the existed automated methods are highly robust, reliable and efficient in clinic application. An accurate and automated tumor segmentation method has been developed for brain tumor segmentation that will provide reproducible and objective results close to manual segmentation results. Methods Based on the symmetry of human brain, we employed sliding-window technique and correlation coefficient to locate the tumor position. At first, the image to be segmented was normalized, rotated, denoised, and bisected. Subsequently, through vertical and horizontal sliding-windows technique in turn, that is, two windows in the left and the right part of brain image moving simultaneously pixel by pixel in two parts of brain image, along with calculating of correlation coefficient of two windows, two windows with minimal correlation coefficient were obtained, and the window with bigger average gray value is the location of tumor and the pixel with biggest gray value is the locating point of tumor. At last, the segmentation threshold was decided by the average gray value of the pixels in the square with center at the locating point and 10 pixels of side length, and threshold segmentation and morphological operations were used to acquire the final tumor region. Results The method was evaluated on 3D FSPGR brain MR images of 10 patients. As a result, the average ratio of correct location was 93.4% for 575 slices containing tumor, the average Dice similarity coefficient was 0.77 for one scan, and the average time spent on one scan was 40 seconds. Conclusions An fully automated, simple and efficient segmentation method for brain tumor is proposed and promising for future clinic use. Correlation coefficient is a new and effective feature for tumor location.

Computerized characterization of lung nodule subtlety using thoracic CT images

The goal of this work is to design computerized image analysis techniques for automatically characterizing lung nodule subtlety in CT images. Automated subtlety estimation methods may help in computer-aided detection (CAD) assessment by quantifying dataset difficulty and facilitating comparisons among different CAD algorithms. A dataset containing 813 nodules from 499 patients was obtained from the Lung Image Database Consortium. Each nodule was evaluated by four radiologists regarding nodule subtlety using a 5-point rating scale (1: most subtle). We developed a 3D technique for segmenting lung nodules using a prespecified initial ROI. Texture and morphological features were automatically extracted from the segmented nodules and their margins. The dataset was partitioned into trainers and testers using a 1:1 ratio. An artificial neural network (ANN) was trained with average reader subtlety scores as the reference. Effective features for characterizing nodule subtlety were selected based on the training set using the ANN and a stepwise feature selection method. The performance of the classifier was evaluated using prediction probability (PK) as an agreement measure, which is considered a generalization of the area under the receiver operating characteristic curve when the reference standard is multi-level. Using an ANN classifier trained with a set of 2 features (selected from a total of 30 features), including compactness and average gray value, the test concordance between computer scores and the average reader scores was 0.789 ± 0.014. Our results show that the proposed method had strong agreement with the average of subtlety scores provided by radiologists.

A New Image Segmentation Model

To build a new image segmentation model based on level set theory : Add edge detection operator to edgeless active contour model to detect local information; introduce adaptive coefficient of area item to let the model autonomously adjust and evolve curve position according to image information; adopt weighted average gray value to replace traditional absolute mean value to reduce error and improve segmentation result. Experimental result comparison shows that the new model can detect global information and local information at the same time, adaptively adjust curve evolution direction, and has a fast segmentation speed. Compared to edgeless active contour model, the new model is a more effective image segmentation method as it has greater advantages in image segmentation accuracy and computational complexity.

A New Image Segmentation Model

To build a new image segmentation model based on level set theory : Add edge detection operator to edgeless active contour model to detect local information; introduce adaptive coefficient of area item to let the model autonomously adjust and evolve curve position according to image information; adopt weighted average gray value to replace traditional absolute mean value to reduce error and improve segmentation result. Experimental result comparison shows that the new model can detect global information and local information at the same time, adaptively adjust curve evolution direction, and has a fast segmentation speed. Compared to edgeless active contour model, the new model is a more effective image segmentation method as it has greater advantages in image segmentation accuracy and computational complexity.

Illuminant direction estimation for a single image based on local region complexity analysis and average gray value

Illuminant direction estimation is an important research issue in the field of image processing. Due to low cost for getting texture information from a single image, it is worthwhile to estimate illuminant direction by employing scenario texture information. This paper proposes a novel computation method to estimate illuminant direction on both color outdoor images and the extended Yale face database B. In our paper, the luminance component is separated from the resized YCbCr image and its edges are detected with the Canny edge detector. Then, we divide the binary edge image into 16 local regions and calculate the edge level percentage in each of them. Afterward, we use the edge level percentage to analyze the complexity of each local region included in the luminance component. Finally, according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model, we calculate the illuminant directions of the luminance component's three local regions, which meet the requirements of lower complexity and larger average gray value, and synthesize them as the final illuminant direction. Unlike previous works, the proposed method requires neither all of the information of the image nor the texture that is included in the training set. Experimental results show that the proposed method works better at the correct rate and execution time than the existing ones.

Cytoskeleton changes of airway smooth muscle cells in juvenile rats with airway remodeling in asthma and the RhoA/ROCK signaling pathway mechanism

This article aimed to investigate changes in the cytoskeleton of airway smooth muscle cells (ASMCs) in juvenile rats with airway remodeling in asthma. We further investigated the involvement of the RhoA/ROCK signaling pathway mechanism. Rat models of airway remodeling in asthma were established by antigen sensitization with ovalbumin for 2, 4, 6, and 8 weeks. The control group was treated with normal saline instead of ovalbumin. In the intervention group, after 8 weeks of culture, ASMCs were treated with the ROCK-specific inhibitor Y-27632. Immunofluorescence, real-time polymerase chain reaction, and Western blot analyses were used to observe changes in the cytoskeleton (F-actin and α-tubulin) of ASMCs and expressions of RhoA and ROCK. The asthmatic groups had significantly higher average gray values of F-actin in ASMCs compared to the control group (P < 0.01), and these values for the intervention group were significantly lower than those of the 8-week asthmatic group (P < 0.05). Expression levels of the α-tubulin protein in the asthmatic groups were all significantly higher than those of the control group (P < 0.01), and the levels in the intervention group were significantly reduced (P < 0.05). Expressions of RhoA and ROCK mRNA and proteins in all asthmatic groups were significantly higher than those of the control group (P < 0.01). Together, these results demonstrate substantial changes of the ASMC cytoskeleton and abnormal expressions of RhoA and ROCK mRNA and proteins in juvenile rats with airway remodeling in asthma.

In vivo exposure to benzo(a)pyrene induces significant DNA damage in mouse oocytes and cumulus cells

Does in vivo exposure to benzo(a)pyrene (BaP) induce DNA damage in oocytes and cumulus cells (CCs) in mice? Significant increases in DNA strand breaks in oocytes and CCs and in BaP-induced DNA adducts in CCs were detected in exposed mice compared with controls. BaP has well-known mutagenic and carcinogenic effects on somatic cells, and is also registered as potential reproductive toxicant by several environmental protection agencies. It has been shown to cause a significant increase in DNA adducts in ovarian tissues; however, to our knowledge, the genotoxic effects of BaP on oocytes and CCs have not been studied to date. Female CD1 mice were exposed to BaP via the oral administration of a single dose of 13 mg/kg body weight (bw); matched controls were exposed to the vehicle only (soya oil). A total of 15 groups of 6 mice (exposed or controls) were sacrificed 2, 4, 6, 15 or 22 days after BaP exposure, and after collection of oviducts, the oocyte-CC complexes (COC) were released. The alkaline comet assay was used to quantify the DNA breaks in oocytes and CCs; DNA damage was expressed as the Olive Tail Moment (OTM). Immunofluorescent staining was used to quantify BaP-induced DNA adducts in CCs. Fluorescence was expressed as the average grey value (AGVA; arbitrary units). The differences between the exposed and control groups were assessed using analysis of variance (ANOVA) and the non-parametric Mann-Whitney test. Higher levels of DNA damage were observed in the oocytes and CCs of BaP-exposed mice than in those of vehicle controls. Significant increases in OTM (mean ± SE) were detected in (i) oocytes from females exposed for 4 (10.5 ± 0.9 versus 3.1 ± 0.4, P < 0.0001) or 6 days before collection (15.6 ± 2.0 versus 3.6 ± 0.9, P < 0.0001) and (ii) CCs from females exposed 2 (6.4 ± 0.6 versus 2.1 ± 0.2, P < 0.0001), 4 (7.8 ± 0.4 versus 2.4 ± 0.1, P < 0.0001) or 6 days before collection (7.3 ± 0.3 versus 3.2 ± 0.5, P < 0.0001) compared with controls. A significant increase in benzo(a)pyrene-7,8-9,10 diol epoxide (BPDE)-DNA adducts and higher AGVA (mean ± SE) scores were observed in CCs from females exposed 2 (6.1 ± 0.3 versus 3.6 ± 0.5, P < 0.0001), 4 (7.5 ± 0.1 versus 3.4 ± 0.1, P < 0.0001) or 6 days before collection (11.6 ± 0.4 versus 3.7 ± 0.1, P < 0.0001) compared with control mice. Mice were given one treatment via the oral route because this dose and mode of administration have been shown to induce detectable BPDE-DNA adduct levels in mouse organs and sperm cells. Additional data are needed to assess DNA damage in oocytes and CCs after chronic exposure to BaP in vivo. To our knowledge, this is the first study examining the in vivo genotoxicity of BaP in oocytes and CCs. We observed significant DNA damage in the oocytes and CCs of mice after acute BaP exposure. BPDE-DNA adducts result directly from BaP metabolism while DNA breaks could result mainly from BPDE-DNA adduct excision and repair and/or through direct genotoxicity from increased reactive oxygen species. These results add new and important insights regarding the recently suggested toxicity of chronic BaP exposure in the ovary. This work was supported by a grant (93-CPQ 2012-05) from the DIRRECTE, Provence Alpes Côte d'Azur, France. None of the authors have any conflict of interest to declare.

Expression of CD44 in articular cartilage is associated with disease severity in knee osteoarthritis

Objectives To investigate CD44 levels in articular cartilage of knee osteoarthritis (OA) and the relationship between CD44 and severity of the disease.Methods All 50 cartilage tissues included normal and OA cartilage, and were ascribed to the following four groups on the basis of modified Mankin score: normal, mild lesions, moderate lesions and severe lesions. CD44 levels in articular cartilage were assessed by immunohistochemical methods.Results CD44 levels were detected in all four groups. The difference in average gray value of CD44 expression showed statistical significance when compared between each group (P < 0.05). In addition, CD44 expression in each group correlated with disease severity, according to the modified Mankin score (ρ = −0.848, P < 0.01).Conclusions CD44 in articular cartilage is associated with progressive knee OA joint damage.

Visual-based spatter detection during high-power disk laser welding

The spatters created during laser welding are considered as essential information for welding quality inspection. This paper proposes a laser welding quality inspection method based on the high-speed visual detection. A high-power (10kW) disk laser bead-on-plate welding of Type 304 austenitic stainless workpiece was carried out and two high-speed cameras were used to capture the spatter images. The first one was used to measure the near infrared (IR) light emitted from a molten pool, and the second was utilized to measure the ultraviolet (UV) light and visible light. By comparing the images captured from two different cameras, it was found that the measurement of UV light and visible light was more appropriate for spatter detection. Based on image process technology, a novel spatter detection algorithm was presented. A shape similarity function and angle similarity function of the spatters were established for spatter recognition by defining the spatter features, such as centroid position, gray-value, average gray-value and radius. The spatter volume, spatter gray-value and spatter radius were used to evaluate the welding quality. By comparing the spatter information with the molten pool width, this paper investigates the internal relationship between the welding quality and the spatter feature parameters. Experimental results proved that the proposed spatter feature extraction method could guarantee an accurate evaluation on the quality of high-power disk laser welding. In addition it was demonstrated in this study that, by using high-speed visual detection and image processing technology, the quantities and feature of spatters could be measured during the welding process.

Detection Algorithm of Vehicles Based on Image Statistical Characteristics

Aiming at the complexity of image recognition and the fluidity of the image itself, a new method to detect and track the target vehicles with the statistical features of the image gray was proposed. The one-to-one correspondence relationship between the target vehicle and the actual vehicle was built by the lane line symmetry and car installation angle. It will take the full image average grey value, target domain area, the perimeter between target domain and background domain border as the statistical characteristics. In addition, several order center distance of the target field distribution function was taken as one of statistical characteristics. The similarity between the extracted image characteristic parameter and the image characteristic parameter from the database at different distance is taken to identify the target vehicles accurately. The results shows that the algorithm cans effectively detecting and tracking the target vehicle in front of the host vehicle 90m apart.

Neuro-protective function of cytoglobin on neonatal rats with hypoxic-ischemic brain damage

Objective To investigate the protective function of cytoglobin (CYGB) on neurodevelopment of the neonatal rats with hypoxic-ischemic brain damage (HIBD).Methods Healthy seven day old Sprague-Dawlay rats were randomly divided into sham operated group,HIBD group,HIBD+Hemin group and HIBD+zinc protoporphyrin (ZnPP) group.The rats of HIBD,HIBD+Heminand HIBD+ZnPPgroup were given normal saline (0.5 ml),Hemin (50 mg/kg) and ZnPP (50 mg/kg) intraperitoneally respectively,and 12 hours later the left carotid arteries of these rats were ligated and cut off,then hypoxic treated for 2 hours to establish the HIBD models.At 0,24,48 h after HIBD models were established,the expressions of CYGB in the cerebral cortex and hippocampus were observed by immunohistochemistry analysis.At 48 h after HIBD,histopathological changes of brain were observed after HE staining.At 72 h after HIBD,the water content of the brain was observed.At 28 days after HIBD,long term study memory outcome was assessed by Morris water maze.Analysis of variance and Bonferroni test were applied as statistical methods.Results (1)The expression of CYGB in brain(expressed by average gray value which negatively correlated with protein levels):At 0 h,the average gray value of CYGB in the cerebral cortex in HIBD+ Hemin and HIBD group were 166.7±5.1 and 207.1±5.1,which were lower than that in sham operated group (232.3±3.4); but in HIBD+ZnPP group,it was higher (234.9±4.5)(P＜0.05).The average gray value of CYGB was decreased with the extension of hypoxic-ischemic time.At 48 h,the average gray value of CYGB was the lowest in HIBD+Hemin group (126.0± 2.6),followed by HIBD group (150.9±4.5) and HIBD+ZnPP group (163.7±6.3),and the highest was in sham operated group (232.1±5.8)(all P＜0.01).(2) Histopathologic changes of the brain:At 48 h,typical cerebral infarction and hemorrhage were seen in HIBD,HIBD+Hemin and HIBD+ZnPP group,but those were less severe in HIBD + Hemin group than in HIBD + ZnPP group.(3) The water content of the brain:At 72 h,the water content of the left brain in HIBD and HIBD+ZnPP group was (86.5±0.4)％ and (87.3±0.3)％,which was higher than that in right brain [(85.6±0.2)％ and (85.9±0.2)％] (t 12.57 and 11.32,P＜0.01,respectively).(4)Function of the hippocampus:Morris water-maze showed that the longest average escape latency in HIBD+ZnPP group [(76.7±29.8) s],followed by HIBD group [(71.0±30.5) s],HIBD+ Hemin group [(46.7±34.0) s],and sham operated group [(38.3±30.3) s] (all P＜0.01).(5) Long-term histopathologic changes of the brain:At 34 d,brain atrophy rate was the highest in HIBD+ZnPP group [(34.07± 6.75) ％],and then in HIBD group [(29.73± 6.53) ％] and HIBD+ Hemin group [(18.33±4.52)％],which were all higher than that in the sham operated group [(1.55±1.32)％](all P＜0.01).HE staining showed that the hippocampal stratum pgramidale was getting thinner and a large number of neurons was lost in HIBD and HIBD+ ZnPP group,but only a small amout of neurons was lost in HIBD+ Hemin group.Conclusions Increased expression of CYGB in HIBD brain could mitigate the short term and long term pathological injury,and protect the long-term study memory function of the hippocampus. Key words: Hypoxia ischemia, brain; Globins; Rats

Ion-enrichment and ion-depletion of nanochannels based on electrochemical potential in a micro-nanofluidic chip

In this paper, we present a new approach for ion-enrichment and ion-depletion effect (IEID) in micro-nanofluidic chips without external power source. The method utilizes different reducibility of various electrodes in the weak oxidizing solution to generate the electrochemical potential and then induce IEID at a micro-nano junction. The results show that the average gray values of the micro-nano junction based on Al–Pt, Fe–Pt, and Cu–Pt electrodes increase from 14.7 to 40.2, 27.1, 15.0 after 20 s, and electric currents for Al–Pt, Fe–Pt, and Cu–Pt electrodes are 5.0, 2.9 and 0 nA respectively. Metal cations generating from oxidation–reduction reaction and electroosmotic convection flow are evaluated and their influences to IEID can be neglected in this case. The IEID method based on the electrochemical potential is power-free and weak flow convective that will be beneficial to the integrity of micro-nanofluidic chips and stability of IEID.

A Method to Extract Contour of Wheat Pests Based on LCV Model&lt;sup&gt;&lt;/sup&gt;

A method to extract contour of wheat pests based on LCV model is proposed in this paper. This method uses calculation of the weighted average gray value of the partial window function to replace the global mean value, and added the constraint level set function as a the energy term of signed distance function to avoid the re-initialization of the level set function. This method can be extracted the contour of wheat pests effectively, and thus it improves the efficiency of the extraction of wheat pests shape feature. The effectiveness of this method is verified by MATLAB simulation experiments.

Seam-line removal method based on correction-ratio of average value

It has been widely used in computer vision,military investigation,medical care and some other fields.The widely used seam-line removal methods include overlapping-image method,wavelet transform method and hard-correction method.An improved method based on the correction-ratio of average gray value of the images on the two sides of the seam-line was proposed.This method calculated the rate of the corrected value and the former value.Then the ratio gradually changed from the seam-line to the boundary so that the seam-line was removed.The experiments have shown that the method proposed above is effective to eliminate seam-lines,especially when the difference of the gray level is big.

Multi-threshold image segmentation using maximum fuzzy entropy based on a new 2D histogram

The traditional fuzzy entropy segmentation method is based on 1D histogram which cannot reflect spatial information and is affected by noise acutely. In this paper a new definition of 2D histogram is proposed. Different images are divided into grids of different densities, and then the gray value of each pixel in the image and the average gray value of the grid which the pixel is located are used as two components of the 2D histogram. To get thresholds value which can be used to segment the image into three levels, a new multi-threshold image segmentation method using maximum fuzzy entropy based on the proposed 2D histogram is presented. The parameters of the fuzzy entropy function can be determined by genetic algorithm with an appropriate coding method. The experiment results show that by using different grids of proper density to divide different images, the proposed method obtains better performance for target information extraction.

Preliminary study for flaw detection in nodular cast iron by cyclic loading and thermography

The objective of this paper is to deduce thermographic parameters from infrared (IR) picture series which indicate the presence of bulk defects in nodular cast iron. For this task, specimens manufactured with and without artificial defects are sinusoidally loaded in the range of the fatigue limit for a short period. During this time, the IR picture series were recorded with a high-speed IR camera. After a picture alignment, the time-dependency of the average gray values in picture subsets was analyzed by discrete Fourier transform (DFT) to get the magnitude and phase shift of the fundamental frequency of the local IR radiation power. The results of the experiments and FE simulations indicate consistently that the volume defects can be detected on the basis of the average and standard deviation of the phase shift distributions on the surface of the specimens.

Expression of CD44 in articular cartilage is associated with disease severity in knee osteoarthritis

To investigate CD44 levels in articular cartilage of knee osteoarthritis (OA) and the relationship between CD44 and severity of the disease. All 50 cartilage tissues included normal and OA cartilage, and were ascribed to the following four groups on the basis of modified Mankin score: normal, mild lesions, moderate lesions and severe lesions. CD44 levels in articular cartilage were assessed by immunohistochemical methods. CD44 levels were detected in all four groups. The difference in average gray value of CD44 expression showed statistical significance when compared between each group (P < 0.05). In addition, CD44 expression in each group correlated with disease severity, according to the modified Mankin score (ρ = -0.848, P < 0.01). CD44 in articular cartilage is associated with progressive knee OA joint damage.

The Determination of the Minimum Force to Initiate Abrasion Damage of Digital Press Prints

The purpose of the project was to determine the minimum levels of force and abrasion cycles necessary to produce a just noticeable difference (JND) in objects printed with modern digital presses (documents, book pages, etc.). The results of this work are intended to help cultural heritage institutions that collect these materials develop policies for use and care to prevent damage to their collections. The results may also benefit commercial services that offer prints made with these processes or manufacturers of the equipment or media. A variety of digital press technologies and papers were studied. Specimens were abraded using the Sutherland 2000 Rub Tester with both &#xBC;-lb and 2-lb loads. The lighter weight was an attempt to replicate physical handling of materials such as page turning in books or sorting sheets in stacks of documents. The use of the heavier weight was an attempt to emulate unbound prints being pulled from larger stacks as well as unbound prints in stacks during transport. The abrading surfaces included unprinted and printed sheets to replicate single-sided prints in stacks or doublesided prints in stacks or books. A series of abrasion cycles were produced for each of the materials to determine when JND could be observed. Visual observations were correlated to average grey values to determine if a quantifiable threshold limit for this property was possible. Additionally, the relative sensitivity of the various materials to abrasion was compared. The tests included measuring colorant smear from a black printed area to an adjacent white area, loss of colorant from the black area, and transfer of colorant to an adjacent sheet. The change in average gray levels were measured with image analysis software for both the black patches and adjacent unprinted areas before and after abrasion as well as the transfer of colorant from printed faces to adjacent unprinted papers. Also gloss measurements before and after were used to determine the extent of gloss change in the black patches. The results show that the major factors influencing the extent of damage from abrasion are the printing technology and the printed paper. From previous work it was known that smear of colorant is more objectionable than gloss change. However, with some digital press/paper combinations noticeable gloss change can be seen before noticeable smear of colorant. While not as severe as smear, change in gloss, especially when it is uneven, is still of concern to museum, library, and archive personnel and patrons. Results from the use of the lighter abrasion weight to simulate the turning of pages or sorting of sheets in stacks This paper was presented at the 4th International Symposium on Technologies for Digital indicated that this should not be a problem no matter which printing technology or paper is used as no noticeable damage was observed either by measurement or visual assessment even after many hundreds of abrasion cycles. The heavier weight showed differentiation of the sensitivity of the different printer technology/paper combinations indicating a greater concern is needed for objects that may be inadvertently subjected to higher forces, especially with digital press inkjet technology.

Least-Squares Halftoning Algorithm Based on Image Segmentation

This work presents a method based on the image content for digital halftoning using K-means clustering theory. Our algorithm applies to both a printer model and a model for the human visual system (HVS). The method strives to minimize the perceived error between the continuous original image and the halftone image. First, the gray image is partitioned into two, three and four regions using K-means image segmentation method, whose performance depends on the selection of distance metrics. Next, the statistics of average gray value of each clustering is calculated. Each clustering uses the least-squares model-based(Lsmb) algorithm to obtain halftone image. Finally, analysis and simulation results show that the proposed algorithm produces better gray-scale halftone image quality when we increase the number of clustering with a certain range. A performance measure for halftone images is used to evaluate our algorithm. The value of MSEv, WSNR and PSNR for two partitions is almost the same as that of the Lsmb algorithm, but for three and four partitions that the proposed algorithm achieves consistently better values of MSEv, WSNR and PSNR than the Lsmb algorithm.

Meso Analysis on Soft Soil Uniaxial Consolidation Experiment with CT

In this paper, marine sediments soft soil of Beigangchi wharf in Tianjin port was scanned by Computer Tomography(CT) in different load during uniaxial consolidation experiment. The CT images were analyzed to research on the relationship between the microcosmic characteristics of Marine deposits soil and it’s compression in Tianjin areas. The results show that: with the increase of the pressure loading, the average grey value of the CT images increases gradually, which illustrates that soil samples are compacted and the density increases. The variance decreasing of CT image grey value indicates that the soil sample get more evenly. Soft soil of Beigangchi wharf in Tianjin port has high compressibility through the changes of grey compression coefficient. This paper can be referenced for the research of the structure changes of the soil sample consolidation process.