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Sample records for active contour segmentation

  1. Integrated active contours for texture segmentation.

    PubMed

    Sagiv, Chen; Sochen, Nir A; Zeevi, Yehoshua Y

    2006-06-01

    We address the issue of textured image segmentation in the context of the Gabor feature space of images. Gabor filters tuned to a set of orientations, scales and frequencies are applied to the images to create the Gabor feature space. A two-dimensional Riemannian manifold of local features is extracted via the Beltrami framework. The metric of this surface provides a good indicator of texture changes and is used, therefore, in a Beltrami-based diffusion mechanism and in a geodesic active contours algorithm for texture segmentation. The performance of the proposed algorithm is compared with that of the edgeless active contours algorithm applied for texture segmentation. Moreover, an integrated approach, extending the geodesic and edgeless active contours approaches to texture segmentation, is presented. We show that combining boundary and region information yields more robust and accurate texture segmentation results. PMID:16764287

  2. Multiple LREK active contours for knee meniscus ultrasound image segmentation.

    PubMed

    Faisal, Amir; Ng, Siew-Cheok; Goh, Siew-Li; George, John; Supriyanto, Eko; Lai, Khin W

    2015-10-01

    Quantification of knee meniscus degeneration and displacement in an ultrasound image requires simultaneous segmentation of femoral condyle, meniscus, and tibial plateau in order to determine the area and the position of the meniscus. In this paper, we present an active contour for image segmentation that uses scalable local regional information on expandable kernel (LREK). It includes using a strategy to adapt the size of a local window in order to avoid being confined locally in a homogeneous region during the segmentation process. We also provide a multiple active contours framework called multiple LREK (MLREK) to deal with multiple object segmentation without merging and overlapping between the neighboring contours in the shared boundaries of separate regions. We compare its performance to other existing active contour models and show an improvement offered by our model. We then investigate the choice of various parameters in the proposed framework in response to the segmentation outcome. Dice coefficient and Hausdorff distance measures over a set of real knee meniscus ultrasound images indicate a potential application of MLREK for assessment of knee meniscus degeneration and displacement. PMID:25910057

  3. Segmentation and Tracking of Cytoskeletal Filaments Using Open Active Contours

    PubMed Central

    Smith, Matthew B.; Li, Hongsheng; Shen, Tian; Huang, Xiaolei; Yusuf, Eddy; Vavylonis, Dimitrios

    2010-01-01

    We use open active contours to quantify cytoskeletal structures imaged by fluorescence microscopy in two and three dimensions. We developed an interactive software tool for segmentation, tracking, and visualization of individual fibers. Open active contours are parametric curves that deform to minimize the sum of an external energy derived from the image and an internal bending and stretching energy. The external energy generates (i) forces that attract the contour toward the central bright line of a filament in the image, and (ii) forces that stretch the active contour toward the ends of bright ridges. Images of simulated semiflexible polymers with known bending and torsional rigidity are analyzed to validate the method. We apply our methods to quantify the conformations and dynamics of actin in two examples: actin filaments imaged by TIRF microscopy in vitro, and actin cables in fission yeast imaged by spinning disk confocal microscopy. PMID:20814909

  4. An Investigation of Implicit Active Contours for Scientific Image Segmentation

    SciTech Connect

    Weeratunga, S K; Kamath, C

    2003-10-29

    The use of partial differential equations in image processing has become an active area of research in the last few years. In particular, active contours are being used for image segmentation, either explicitly as snakes, or implicitly through the level set approach. In this paper, we consider the use of the implicit active contour approach for segmenting scientific images of pollen grains obtained using a scanning electron microscope. Our goal is to better understand the pros and cons of these techniques and to compare them with the traditional approaches such as the Canny and SUSAN edge detectors. The preliminary results of our study show that the level set method is computationally expensive and requires the setting of several different parameters. However, it results in closed contours, which may be useful in separating objects from the background in an image.

  5. Segmentation of intensity inhomogeneous brain MR images using active contours.

    PubMed

    Akram, Farhan; Kim, Jeong Heon; Lim, Han Ul; Choi, Kwang Nam

    2014-01-01

    Segmentation of intensity inhomogeneous regions is a well-known problem in image analysis applications. This paper presents a region-based active contour method for image segmentation, which properly works in the context of intensity inhomogeneity problem. The proposed region-based active contour method embeds both region and gradient information unlike traditional methods. It contains mainly two terms, area and length, in which the area term practices a new region-based signed pressure force (SPF) function, which utilizes mean values from a certain neighborhood using the local binary fitted (LBF) energy model. In turn, the length term uses gradient information. The novelty of our method is to locally compute new SPF function, which uses local mean values and is able to detect boundaries of the homogenous regions. Finally, a truncated Gaussian kernel is used to regularize the level set function, which not only regularizes it but also removes the need of computationally expensive reinitialization. The proposed method targets the segmentation problem of intensity inhomogeneous images and reduces the time complexity among locally computed active contour methods. The experimental results show that the proposed method yields better segmentation result as well as less time complexity compared with the state-of-the-art active contour methods. PMID:25143780

  6. Implicit active contours for automatic brachytherapy seed segmentation in fluoroscopy

    NASA Astrophysics Data System (ADS)

    Moult, Eric; Burdette, Clif; Song, Danny; Fichtinger, Gabor; Fallavollita, Pascal

    2012-02-01

    Motivation: In prostate brachytherapy, intra-operative dosimetry would be ideal to allow for rapid evaluation of the implant quality while the patient is still in the treatment position. Such a mechanism, however, requires 3-D visualization of the currently deposited seeds relative to the prostate. Thus, accurate, robust, and fully-automatic seed segmentation is of critical importance in achieving intra-operative dosimetry. Methodology: Implanted brachytherapy seeds are segmented by utilizing a region-based implicit active contour approach. Overlapping seed clusters are then resolved using a simple yet effective declustering technique. Results: Ground-truth seed coordinates were obtained via a published segmentation technique. A total of 248 clinical C-arm images from 16 patients were used to validate the proposed algorithm resulting in a 98.4% automatic detection rate with a corresponding 2.5% false-positive rate. The overall mean centroid error between the ground-truth and automatic segmentations was measured to be 0.42 pixels, while the mean centroid error for overlapping seed clusters alone was measured to be 0.67 pixels. Conclusion: Based on clinical data evaluation and validation, robust, accurate, and fully-automatic brachytherapy seed segmentation can be achieved through the implicit active contour framework and subsequent seed declustering method.

  7. Active contour based segmentation of resected livers in CT images

    NASA Astrophysics Data System (ADS)

    Oelmann, Simon; Oyarzun Laura, Cristina; Drechsler, Klaus; Wesarg, Stefan

    2015-03-01

    The majority of state of the art segmentation algorithms are able to give proper results in healthy organs but not in pathological ones. However, many clinical applications require an accurate segmentation of pathological organs. The determination of the target boundaries for radiotherapy or liver volumetry calculations are examples of this. Volumetry measurements are of special interest after tumor resection for follow up of liver regrow. The segmentation of resected livers presents additional challenges that were not addressed by state of the art algorithms. This paper presents a snakes based algorithm specially developed for the segmentation of resected livers. The algorithm is enhanced with a novel dynamic smoothing technique that allows the active contour to propagate with different speeds depending on the intensities visible in its neighborhood. The algorithm is evaluated in 6 clinical CT images as well as 18 artificial datasets generated from additional clinical CT images.

  8. Segmentation of Coronal Holes Using Active Contours Without Edges

    NASA Astrophysics Data System (ADS)

    Boucheron, L. E.; Valluri, M.; McAteer, R. T. J.

    2016-09-01

    An application of active contours without edges is presented as an efficient and effective means of extracting and characterizing coronal holes. Coronal holes are regions of low-density plasma on the Sun with open magnetic field lines. The detection and characterization of these regions is important for testing theories of their formation and evolution, and also from a space weather perspective because they are the source of the fast solar wind. Coronal holes are detected in full-disk extreme ultraviolet (EUV) images of the corona obtained with the Solar Dynamics Observatory Atmospheric Imaging Assembly (SDO/AIA). The proposed method detects coronal boundaries without determining any fixed intensity value in the data. Instead, the active contour segmentation employs an energy-minimization in which coronal holes are assumed to have more homogeneous intensities than the surrounding active regions and quiet Sun. The segmented coronal holes tend to correspond to unipolar magnetic regions, are consistent with concurrent solar wind observations, and qualitatively match the coronal holes segmented by other methods. The means to identify a coronal hole without specifying a final intensity threshold may allow this algorithm to be more robust across multiple datasets, regardless of data type, resolution, and quality.

  9. Segmentation of Coronal Holes Using Active Contours Without Edges

    NASA Astrophysics Data System (ADS)

    Boucheron, L. E.; Valluri, M.; McAteer, R. T. J.

    2016-10-01

    An application of active contours without edges is presented as an efficient and effective means of extracting and characterizing coronal holes. Coronal holes are regions of low-density plasma on the Sun with open magnetic field lines. The detection and characterization of these regions is important for testing theories of their formation and evolution, and also from a space weather perspective because they are the source of the fast solar wind. Coronal holes are detected in full-disk extreme ultraviolet (EUV) images of the corona obtained with the Solar Dynamics Observatory Atmospheric Imaging Assembly (SDO/AIA). The proposed method detects coronal boundaries without determining any fixed intensity value in the data. Instead, the active contour segmentation employs an energy-minimization in which coronal holes are assumed to have more homogeneous intensities than the surrounding active regions and quiet Sun. The segmented coronal holes tend to correspond to unipolar magnetic regions, are consistent with concurrent solar wind observations, and qualitatively match the coronal holes segmented by other methods. The means to identify a coronal hole without specifying a final intensity threshold may allow this algorithm to be more robust across multiple datasets, regardless of data type, resolution, and quality.

  10. Lung segmentation from HRCT using united geometric active contours

    NASA Astrophysics Data System (ADS)

    Liu, Junwei; Li, Chuanfu; Xiong, Jin; Feng, Huanqing

    2007-12-01

    Accurate lung segmentation from high resolution CT images is a challenging task due to various detail tracheal structures, missing boundary segments and complex lung anatomy. One popular method is based on gray-level threshold, however its results are usually rough. A united geometric active contours model based on level set is proposed for lung segmentation in this paper. Particularly, this method combines local boundary information and region statistical-based model synchronously: 1) Boundary term ensures the integrality of lung tissue.2) Region term makes the level set function evolve with global characteristic and independent on initial settings. A penalizing energy term is introduced into the model, which forces the level set function evolving without re-initialization. The method is found to be much more efficient in lung segmentation than other methods that are only based on boundary or region. Results are shown by 3D lung surface reconstruction, which indicates that the method will play an important role in the design of computer-aided diagnostic (CAD) system.

  11. Evaluating geodesic active contours in microcalcifications segmentation on mammograms.

    PubMed

    Duarte, Marcelo A; Alvarenga, Andre V; Azevedo, Carolina M; Calas, Maria Julia G; Infantosi, Antonio F C; Pereira, Wagner C A

    2015-12-01

    Breast cancer is the most commonly occurring type of cancer among women, and it is the major cause of female cancer-related deaths worldwide. Its incidence is increasing in developed as well as developing countries. Efficient strategies to reduce the high death rates due to breast cancer include early detection and tumor removal in the initial stages of the disease. Clinical and mammographic examinations are considered the best methods for detecting the early signs of breast cancer; however, these techniques are highly dependent on breast characteristics, equipment quality, and physician experience. Computer-aided diagnosis (CADx) systems have been developed to improve the accuracy of mammographic diagnosis; usually such systems may involve three steps: (i) segmentation; (ii) parameter extraction and selection of the segmented lesions and (iii) lesions classification. Literature considers the first step as the most important of them, as it has a direct impact on the lesions characteristics that will be used in the further steps. In this study, the original contribution is a microcalcification segmentation method based on the geodesic active contours (GAC) technique associated with anisotropic texture filtering as well as the radiologists' knowledge. Radiologists actively participate on the final step of the method, selecting the final segmentation that allows elaborating an adequate diagnosis hypothesis with the segmented microcalcifications presented in a region of interest (ROI). The proposed method was assessed by employing 1000 ROIs extracted from images of the Digital Database for Screening Mammography (DDSM). For the selected ROIs, the rate of adequately segmented microcalcifications to establish a diagnosis hypothesis was at least 86.9%, according to the radiologists. The quantitative test, based on the area overlap measure (AOM), yielded a mean of 0.52±0.20 for the segmented images, when all 2136 segmented microcalcifications were considered. Moreover, a

  12. A Vessel Active Contour Model for Vascular Segmentation

    PubMed Central

    Chen, Qingli; Wang, Wei; Peng, Yu; Wang, Qingjun; Wu, Zhongke; Zhou, Mingquan

    2014-01-01

    This paper proposes a vessel active contour model based on local intensity weighting and a vessel vector field. Firstly, the energy function we define is evaluated along the evolving curve instead of all image points, and the function value at each point on the curve is based on the interior and exterior weighted means in a local neighborhood of the point, which is good for dealing with the intensity inhomogeneity. Secondly, a vascular vector field derived from a vesselness measure is employed to guide the contour to evolve along the vessel central skeleton into thin and weak vessels. Thirdly, an automatic initialization method that makes the model converge rapidly is developed, and it avoids repeated trails in conventional local region active contour models. Finally, a speed-up strategy is implemented by labeling the steadily evolved points, and it avoids the repeated computation of these points in the subsequent iterations. Experiments using synthetic and real vessel images validate the proposed model. Comparisons with the localized active contour model, local binary fitting model, and vascular active contour model show that the proposed model is more accurate, efficient, and suitable for extraction of the vessel tree from different medical images. PMID:25101262

  13. COMBINING ATLAS AND ACTIVE CONTOUR FOR AUTOMATIC 3D MEDICAL IMAGE SEGMENTATION.

    PubMed

    Gao, Yi; Tannenbaum, Allen

    2011-01-01

    Atlas based methods and active contours are two families of techniques widely used for the task of 3D medical image segmentation. In this work we present a coupled framework where the two methods are combined together, in order to exploit each's advantage while avoid their respective drawbacks. Indeed, the atlas based methods lacks the flexibility in locally tuning the segmentation boundary; whereas the active contour has the drawback that the final result heavily depends on the initialization as well as the contour evolution energy functional. Therefore, in the proposed work, the atlas based segmentation provides a probability map, which not only supplies the initial contour position, but also defines the contour evolution energy in an on-line fashion. Afterward, the active contour further converges to the desired object boundary. Finally, the method is tested on various 3D medical images to demonstrate its robustness as well as accuracy.

  14. Gallbladder Boundary Segmentation from Ultrasound Images Using Active Contour Model

    NASA Astrophysics Data System (ADS)

    Ciecholewski, Marcin

    Extracting the shape of the gallbladder from an ultrasonography (US) image allows superfluous information which is immaterial in the diagnostic process to be eliminated. In this project an active contour model was used to extract the shape of the gallbladder, both for cases free of lesions, and for those showing specific disease units, namely: lithiasis, polyps and changes in the shape of the organ, such as folds or turns of the gallbladder. The approximate shape of the gallbladder was found by applying the motion equation model. The tests conducted have shown that for the 220 US images of the gallbladder, the area error rate (AER) amounted to 18.15%.

  15. Convolutional virtual electric field for image segmentation using active contours.

    PubMed

    Wang, Yuanquan; Zhu, Ce; Zhang, Jiawan; Jian, Yuden

    2014-01-01

    Gradient vector flow (GVF) is an effective external force for active contours; however, it suffers from heavy computation load. The virtual electric field (VEF) model, which can be implemented in real time using fast Fourier transform (FFT), has been proposed later as a remedy for the GVF model. In this work, we present an extension of the VEF model, which is referred to as CONvolutional Virtual Electric Field, CONVEF for short. This proposed CONVEF model takes the VEF model as a convolution operation and employs a modified distance in the convolution kernel. The CONVEF model is also closely related to the vector field convolution (VFC) model. Compared with the GVF, VEF and VFC models, the CONVEF model possesses not only some desirable properties of these models, such as enlarged capture range, u-shape concavity convergence, subject contour convergence and initialization insensitivity, but also some other interesting properties such as G-shape concavity convergence, neighboring objects separation, and noise suppression and simultaneously weak edge preserving. Meanwhile, the CONVEF model can also be implemented in real-time by using FFT. Experimental results illustrate these advantages of the CONVEF model on both synthetic and natural images. PMID:25360586

  16. Comparison of segmentation using fast marching and geodesic active contours methods for bone

    NASA Astrophysics Data System (ADS)

    Bilqis, A.; Widita, R.

    2016-03-01

    Image processing is important in diagnosing diseases or damages of human organs. One of the important stages of image processing is segmentation process. Segmentation is a separation process of the image into regions of certain similar characteristics. It is used to simplify the image to make an analysis easier. The case raised in this study is image segmentation of bones. Bone's image segmentation is a way to get bone dimensions, which is needed in order to make prosthesis that is used to treat broken or cracked bones. Segmentation methods chosen in this study are fast marching and geodesic active contours. This study uses ITK (Insight Segmentation and Registration Toolkit) software. The success of the segmentation was then determined by calculating its accuracy, sensitivity, and specificity. Based on the results, the Active Contours method has slightly higher accuracy and sensitivity values than the fast marching method. As for the value of specificity, fast marching has produced three image results that have higher specificity values compared to those of geodesic active contour's. The result also indicates that both methods have succeeded in performing bone's image segmentation. Overall, geodesic active contours method is quite better than fast marching in segmenting bone images.

  17. Multiple Active Contours Guided by Differential Evolution for Medical Image Segmentation

    PubMed Central

    Cruz-Aceves, I.; Avina-Cervantes, J. G.; Lopez-Hernandez, J. M.; Rostro-Gonzalez, H.; Garcia-Capulin, C. H.; Torres-Cisneros, M.; Guzman-Cabrera, R.

    2013-01-01

    This paper presents a new image segmentation method based on multiple active contours guided by differential evolution, called MACDE. The segmentation method uses differential evolution over a polar coordinate system to increase the exploration and exploitation capabilities regarding the classical active contour model. To evaluate the performance of the proposed method, a set of synthetic images with complex objects, Gaussian noise, and deep concavities is introduced. Subsequently, MACDE is applied on datasets of sequential computed tomography and magnetic resonance images which contain the human heart and the human left ventricle, respectively. Finally, to obtain a quantitative and qualitative evaluation of the medical image segmentations compared to regions outlined by experts, a set of distance and similarity metrics has been adopted. According to the experimental results, MACDE outperforms the classical active contour model and the interactive Tseng method in terms of efficiency and robustness for obtaining the optimal control points and attains a high accuracy segmentation. PMID:23983809

  18. Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model

    PubMed Central

    Liu, Tingting; Xu, Haiyong; Liu, Zhen; Zhao, Yiming; Tian, Wenzhe

    2014-01-01

    A novel hybrid region-based active contour model is presented to segment medical images with intensity inhomogeneity. The energy functional for the proposed model consists of three weighted terms: global term, local term, and regularization term. The total energy is incorporated into a level set formulation with a level set regularization term, from which a curve evolution equation is derived for energy minimization. Experiments on some synthetic and real images demonstrate that our model is more efficient compared with the localizing region-based active contours (LRBAC) method, proposed by Lankton, and more robust compared with the Chan-Vese (C-V) active contour model. PMID:25028593

  19. 3D Filament Network Segmentation with Multiple Active Contours

    NASA Astrophysics Data System (ADS)

    Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

    2014-03-01

    Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

  20. [Segmentation of medical images based on dyadic wavelet transform and active contour model].

    PubMed

    Li, Hong; Wang, Huinan; Chang, Linfeng; Shao, Xiaoli

    2008-12-01

    The interference of noise and the weak edge characteristic of symptom information on medical images prevent the traditional methods of segmentation from having good effects. In this paper is proposed a boundary detection method of focus which is based on dyadic wavelet transform and active contour model. In this method, the true edge points are detected by dyadic wavelet transform and linked by improved fast active contour model algorithm. The result of experiment on MRI of brain shows that the method can remove the influence of noise effective and detect the contour of brain tumor actually. PMID:19166191

  1. Segmentation and tracking in echocardiographic sequences: active contours guided by optical flow estimates

    NASA Technical Reports Server (NTRS)

    Mikic, I.; Krucinski, S.; Thomas, J. D.

    1998-01-01

    This paper presents a method for segmentation and tracking of cardiac structures in ultrasound image sequences. The developed algorithm is based on the active contour framework. This approach requires initial placement of the contour close to the desired position in the image, usually an object outline. Best contour shape and position are then calculated, assuming that at this configuration a global energy function, associated with a contour, attains its minimum. Active contours can be used for tracking by selecting a solution from a previous frame as an initial position in a present frame. Such an approach, however, fails for large displacements of the object of interest. This paper presents a technique that incorporates the information on pixel velocities (optical flow) into the estimate of initial contour to enable tracking of fast-moving objects. The algorithm was tested on several ultrasound image sequences, each covering one complete cardiac cycle. The contour successfully tracked boundaries of mitral valve leaflets, aortic root and endocardial borders of the left ventricle. The algorithm-generated outlines were compared against manual tracings by expert physicians. The automated method resulted in contours that were within the boundaries of intraobserver variability.

  2. Brain MR image segmentation using local and global intensity fitting active contours/surfaces.

    PubMed

    Wang, Li; Li, Chunming; Sun, Quansen; Xia, Deshen; Kao, Chiu-Yen

    2008-01-01

    In this paper, we present an improved region-based active contour/surface model for 2D/3D brain MR image segmentation. Our model combines the advantages of both local and global intensity information, which enable the model to cope with intensity inhomogeneity. We define an energy functional with a local intensity fitting term and an auxiliary global intensity fitting term. In the associated curve evolution, the motion of the contour is driven by a local intensity fitting force and a global intensity fitting force, induced by the local and global terms in the proposed energy functional, respectively. The influence of these two forces on the curve evolution is complementary. When the contour is close to object boundaries, the local intensity fitting force became dominant, which attracts the contour toward object boundaries and finally stops the contour there. The global intensity fitting force is dominant when the contour is far away from object boundaries, and it allows more flexible initialization of contours by using global image information. The proposed model has been applied to both 2D and 3D brain MR image segmentation with promising results.

  3. Interactive Medical Image Segmentation using PDE Control of Active Contours

    PubMed Central

    Karasev, Peter; Kolesov, Ivan; Fritscher, Karl; Vela, Patricio; Mitchell, Phillip; Tannenbaum, Allen

    2014-01-01

    Segmentation of injured or unusual anatomic structures in medical imagery is a problem that has continued to elude fully automated solutions. In this paper, the goal of easy-to-use and consistent interactive segmentation is transformed into a control synthesis problem. A nominal level set PDE is assumed to be given; this open-loop system achieves correct segmentation under ideal conditions, but does not agree with a human expert's ideal boundary for real image data. Perturbing the state and dynamics of a level set PDE via the accumulated user input and an observer-like system leads to desirable closed-loop behavior. The input structure is designed such that a user can stabilize the boundary in some desired state without needing to understand any mathematical parameters. Effectiveness of the technique is illustrated with applications to the challenging segmentations of a patellar tendon in MR and a shattered femur in CT. PMID:23893712

  4. Soft-tissues Image Processing: Comparison of Traditional Segmentation Methods with 2D active Contour Methods

    NASA Astrophysics Data System (ADS)

    Mikulka, J.; Gescheidtova, E.; Bartusek, K.

    2012-01-01

    The paper deals with modern methods of image processing, especially image segmentation, classification and evaluation of parameters. It focuses primarily on processing medical images of soft tissues obtained by magnetic resonance tomography (MR). It is easy to describe edges of the sought objects using segmented images. The edges found can be useful for further processing of monitored object such as calculating the perimeter, surface and volume evaluation or even three-dimensional shape reconstruction. The proposed solutions can be used for the classification of healthy/unhealthy tissues in MR or other imaging. Application examples of the proposed segmentation methods are shown. Research in the area of image segmentation focuses on methods based on solving partial differential equations. This is a modern method for image processing, often called the active contour method. It is of great advantage in the segmentation of real images degraded by noise with fuzzy edges and transitions between objects. In the paper, results of the segmentation of medical images by the active contour method are compared with results of the segmentation by other existing methods. Experimental applications which demonstrate the very good properties of the active contour method are given.

  5. Active-contour-model-based edge restriction and attraction field regularization for brain MRI segmentation

    NASA Astrophysics Data System (ADS)

    Luan, H.; Qi, Feihu

    2004-11-01

    Constructing 3D models of the object of interest from brain MRI is useful in numerous biomedical imaging application. In general, the construction of the 3D models is generally carried out according to the contours obtained from a 2D segmentation of each MR slice, so the equality of the 3D model strongly depends on the precision of the segmentation process. Active contour model is an effective edge-based method in segmenting an object of interest. However, its application, which segment boundary of anatomical structure of brain MRI, encounters many difficulties due to undesirable properties of brain MRI, for example complex background, intensity inhomogeneity and discontinuous edges. This paper proposes an active contour model to solve the problems of automatically segmenting the object of interest from a brain MRI. In this proposed algorithm, a new method of calculating attraction field has been developed. This method is based on edge restriction and attraction field regularization. Edge restriction introduces prior knowledge about the object of interest to free contours of being affected by edges of other anatomical structures or spurious edges, while attraction field regularization enables our algorithm to extract boundary correctly even at the place, where the edge of object of interest is discontinuous, by diffusing the edge information gotten after edge restriction. When we apply this proposed algorithm to brain MRI, the result shows this proposed algorithm could overcome those difficulties we mentioned above and convergence to object boundary quickly and accurately.

  6. Liver segmentation with new supervised method to create initial curve for active contour.

    PubMed

    Zareei, Abouzar; Karimi, Abbas

    2016-08-01

    The liver performs a critical task in the human body; therefore, detecting liver diseases and preparing a robust plan for treating them are both crucial. Liver diseases kill nearly 25,000 Americans every year. A variety of image segmentation methods are available to determine the liver's position and to detect possible liver tumors. Among these is the Active Contour Model (ACM), a framework which has proven very sensitive to initial contour delineation and control parameters. In the proposed method based on image energy, we attempted to obtain an initial segmentation close to the liver's boundary, and then implemented an ACM to improve the initial segmentation. The ACM used in this work incorporates gradient vector flow (GVF) and balloon energy in order to overcome ACM limitations, such as local minima entrapment and initial contour dependency. Additionally, in order to adjust active contour control parameters, we applied a genetic algorithm to produce a proper parameter set close to the optimal solution. The pre-processing method has a better ability to segment the liver tissue during a short time with respect to other mentioned methods in this paper. The proposed method was performed using Sliver CT image datasets. The results show high accuracy, precision, sensitivity, specificity and low overlap error, MSD and runtime with few ACM iterations. PMID:27286186

  7. Liver segmentation with new supervised method to create initial curve for active contour.

    PubMed

    Zareei, Abouzar; Karimi, Abbas

    2016-08-01

    The liver performs a critical task in the human body; therefore, detecting liver diseases and preparing a robust plan for treating them are both crucial. Liver diseases kill nearly 25,000 Americans every year. A variety of image segmentation methods are available to determine the liver's position and to detect possible liver tumors. Among these is the Active Contour Model (ACM), a framework which has proven very sensitive to initial contour delineation and control parameters. In the proposed method based on image energy, we attempted to obtain an initial segmentation close to the liver's boundary, and then implemented an ACM to improve the initial segmentation. The ACM used in this work incorporates gradient vector flow (GVF) and balloon energy in order to overcome ACM limitations, such as local minima entrapment and initial contour dependency. Additionally, in order to adjust active contour control parameters, we applied a genetic algorithm to produce a proper parameter set close to the optimal solution. The pre-processing method has a better ability to segment the liver tissue during a short time with respect to other mentioned methods in this paper. The proposed method was performed using Sliver CT image datasets. The results show high accuracy, precision, sensitivity, specificity and low overlap error, MSD and runtime with few ACM iterations.

  8. Image Segmentation Using Active Contours Driven by the Bhattacharyya Gradient Flow

    PubMed Central

    Michailovich, Oleg; Rathi, Yogesh; Tannenbaum, Allen

    2013-01-01

    This paper addresses the problem of image segmentation by means of active contours, whose evolution is driven by the gradient flow derived from an energy functional that is based on the Bhattacharyya distance. In particular, given the values of a photometric variable (or of a set thereof), which is to be used for classifying the image pixels, the active contours are designed to converge to the shape that results in maximal discrepancy between the empirical distributions of the photometric variable inside and outside of the contours. The above discrepancy is measured by means of the Bhattacharyya distance that proves to be an extremely useful tool for solving the problem at hand. The proposed methodology can be viewed as a generalization of the segmentation methods, in which active contours maximize the difference between a finite number of empirical moments of the “inside” and “outside” distributions. Furthermore, it is shown that the proposed methodology is very versatile and flexible in the sense that it allows one to easily accommodate a diversity of the image features based on which the segmentation should be performed. As an additional contribution, a method for automatically adjusting the smoothness properties of the empirical distributions is proposed. Such a procedure is crucial in situations when the number of data samples (supporting a certain segmentation class) varies considerably in the course of the evolution of the active contour. In this case, the smoothness properties of the empirical distributions have to be properly adjusted to avoid either over- or underestimation artifacts. Finally, a number of relevant segmentation results are demonstrated and some further research directions are discussed. PMID:17990755

  9. A novel content-based active contour model for brain tumor segmentation.

    PubMed

    Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

    2012-06-01

    Brain tumor segmentation is a crucial step in surgical and treatment planning. Intensity-based active contour models such as gradient vector flow (GVF), magneto static active contour (MAC) and fluid vector flow (FVF) have been proposed to segment homogeneous objects/tumors in medical images. In this study, extensive experiments are done to analyze the performance of intensity-based techniques for homogeneous tumors on brain magnetic resonance (MR) images. The analysis shows that the state-of-art methods fail to segment homogeneous tumors against similar background or when these tumors show partial diversity toward the background. They also have preconvergence problem in case of false edges/saddle points. However, the presence of weak edges and diffused edges (due to edema around the tumor) leads to oversegmentation by intensity-based techniques. Therefore, the proposed method content-based active contour (CBAC) uses both intensity and texture information present within the active contour to overcome above-stated problems capturing large range in an image. It also proposes a novel use of Gray-Level Co-occurrence Matrix to define texture space for tumor segmentation. The effectiveness of this method is tested on two different real data sets (55 patients - more than 600 images) containing five different types of homogeneous, heterogeneous, diffused tumors and synthetic images (non-MR benchmark images). Remarkable results are obtained in segmenting homogeneous tumors of uniform intensity, complex content heterogeneous, diffused tumors on MR images (T1-weighted, postcontrast T1-weighted and T2-weighted) and synthetic images (non-MR benchmark images of varying intensity, texture, noise content and false edges). Further, tumor volume is efficiently extracted from 2-dimensional slices and is named as 2.5-dimensional segmentation. PMID:22459443

  10. A partition-based active contour model incorporating local information for image segmentation.

    PubMed

    Shi, Jiao; Wu, Jiaji; Paul, Anand; Jiao, Licheng; Gong, Maoguo

    2014-01-01

    Active contour models are always designed on the assumption that images are approximated by regions with piecewise-constant intensities. This assumption, however, cannot be satisfied when describing intensity inhomogeneous images which frequently occur in real world images and induced considerable difficulties in image segmentation. A milder assumption that the image is statistically homogeneous within different local regions may better suit real world images. By taking local image information into consideration, an enhanced active contour model is proposed to overcome difficulties caused by intensity inhomogeneity. In addition, according to curve evolution theory, only the region near contour boundaries is supposed to be evolved in each iteration. We try to detect the regions near contour boundaries adaptively for satisfying the requirement of curve evolution theory. In the proposed method, pixels within a selected region near contour boundaries have the opportunity to be updated in each iteration, which enables the contour to be evolved gradually. Experimental results on synthetic and real world images demonstrate the advantages of the proposed model when dealing with intensity inhomogeneity images.

  11. Segmentation of Bone with Region Based Active Contour Model in PD Weighted MR Images of Shoulder

    PubMed Central

    Sezer, Aysun; Sezer, Hasan Basri; Albayrak, Songul

    2015-01-01

    Proton density (PD) weighted MR images present inhomogeneity problem, low signal to noise ratio (SNR) and cannot define bone borders clearly. Segmentation of PD weighted images is hampered with these properties of PD weighted images which even limit the visual inspection. The purpose of this study is to determine the effectiveness of segmentation of humeral head from axial PD MR images with active contour without edge (ACWE) model. We included 219 images from our original data set. We extended the use of speckle reducing anisotropic diffusion (SRAD) in PD MR images by estimation of standard deviation of noise (SDN) from ROI. To overcome the problem of initialization of the initial contour of these region based methods, the location of the initial contour was automatically determined with use of circular Hough transform. For comparison, signed pressure force (SPF), fuzzy C-means, and Gaussian mixture models were applied and segmentation results of all four methods were also compared with the manual segmentation results of an expert. Experimental results on our own database show promising results. This is the first study in the literature to segment normal and pathological humeral heads from PD weighted MR images. PMID:26064185

  12. Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation

    PubMed Central

    Soomro, Shafiullah; Kim, Jeong Heon; Soomro, Toufique Ahmed

    2016-01-01

    This paper introduces an improved region based active contour method with a level set formulation. The proposed energy functional integrates both local and global intensity fitting terms in an additive formulation. Local intensity fitting term influences local force to pull the contour and confine it to object boundaries. In turn, the global intensity fitting term drives the movement of contour at a distance from the object boundaries. The global intensity term is based on the global division algorithm, which can better capture intensity information of an image than Chan-Vese (CV) model. Both local and global terms are mutually assimilated to construct an energy function based on a level set formulation to segment images with intensity inhomogeneity. Experimental results show that the proposed method performs better both qualitatively and quantitatively compared to other state-of-the-art-methods. PMID:27800011

  13. Contour Completion Without Region Segmentation.

    PubMed

    Ming, Yansheng; Li, Hongdong; He, Xuming

    2016-08-01

    Contour completion plays an important role in visual perception, where the goal is to group fragmented low-level edge elements into perceptually coherent and salient contours. Most existing methods for contour completion have focused on pixelwise detection accuracy. In contrast, fewer methods have addressed the global contour closure effect, despite psychological evidences for its importance. This paper proposes a purely contour-based higher order CRF model to achieve contour closure, through local connectedness approximation. This leads to a simplified problem structure, where our higher order inference problem can be transformed into an integer linear program and be solved efficiently. Compared with the methods based on the same bottom-up edge detector, our method achieves a superior contour grouping ability (measured by Rand index), a comparable precision-recall performance, and more visually pleasing results. Our results suggest that contour closure can be effectively achieved in contour domain, in contrast to a popular view that segmentation is essential for this purpose.

  14. An efficient topology adaptation system for parametric active contour segmentation of 3D images

    NASA Astrophysics Data System (ADS)

    Abhau, Jochen; Scherzer, Otmar

    2008-03-01

    Active contour models have already been used succesfully for segmentation of organs from medical images in 3D. In implicit models, the contour is given as the isosurface of a scalar function, and therefore topology adaptations are handled naturally during a contour evolution. Nevertheless, explicit or parametric models are often preferred since user interaction and special geometric constraints are usually easier to incorporate. Although many researchers have studied topology adaptation algorithms in explicit mesh evolutions, no stable algorithm is known for interactive applications. In this paper, we present a topology adaptation system, which consists of two novel ingredients: A spatial hashing technique is used to detect self-colliding triangles of the mesh whose expected running time is linear with respect to the number of mesh vertices. For the topology change procedure, we have developed formulas by homology theory. During a contour evolution, we just have to choose between a few possible mesh retriangulations by local triangle-triangle intersection tests. Our algorithm has several advantages compared to existing ones: Since the new algorithm does not require any global mesh reparametrizations, it is very efficient. Since the topology adaptation system does not require constant sampling density of the mesh vertices nor especially smooth meshes, mesh evolution steps can be performed in a stable way with a rather coarse mesh. We apply our algorithm to 3D ultrasonic data, showing that accurate segmentation is obtained in some seconds.

  15. Lung nodule segmentation and recognition using SVM classifier and active contour modeling: a complete intelligent system.

    PubMed

    Keshani, Mohsen; Azimifar, Zohreh; Tajeripour, Farshad; Boostani, Reza

    2013-05-01

    In this paper, a novel method for lung nodule detection, segmentation and recognition using computed tomography (CT) images is presented. Our contribution consists of several steps. First, the lung area is segmented by active contour modeling followed by some masking techniques to transfer non-isolated nodules into isolated ones. Then, nodules are detected by the support vector machine (SVM) classifier using efficient 2D stochastic and 3D anatomical features. Contours of detected nodules are then extracted by active contour modeling. In this step all solid and cavitary nodules are accurately segmented. Finally, lung tissues are classified into four classes: namely lung wall, parenchyma, bronchioles and nodules. This classification helps us to distinguish a nodule connected to the lung wall and/or bronchioles (attached nodule) from the one covered by parenchyma (solitary nodule). At the end, performance of our proposed method is examined and compared with other efficient methods through experiments using clinical CT images and two groups of public datasets from Lung Image Database Consortium (LIDC) and ANODE09. Solid, non-solid and cavitary nodules are detected with an overall detection rate of 89%; the number of false positive is 7.3/scan and the location of all detected nodules are recognized correctly. PMID:23369568

  16. TWO NOVEL ACM (ACTIVE CONTOUR MODEL) METHODS FOR INTRAVASCULAR ULTRASOUND IMAGE SEGMENTATION

    SciTech Connect

    Chen, Chi Hau; Potdat, Labhesh; Chittineni, Rakesh

    2010-02-22

    One of the attractive image segmentation methods is the Active Contour Model (ACM) which has been widely used in medical imaging as it always produces sub-regions with continuous boundaries. Intravascular ultrasound (IVUS) is a catheter based medical imaging technique which is used for quantitative assessment of atherosclerotic disease. Two methods of ACM realizations are presented in this paper. The gradient descent flow based on minimizing energy functional can be used for segmentation of IVUS images. However this local operation alone may not be adequate to work with the complex IVUS images. The first method presented consists of basically combining the local geodesic active contours and global region-based active contours. The advantage of combining the local and global operations is to allow curves deforming under the energy to find only significant local minima and delineate object borders despite noise, poor edge information and heterogeneous intensity profiles. Results for this algorithm are compared to standard techniques to demonstrate the method's robustness and accuracy. In the second method, the energy function is appropriately modified and minimized using a Hopfield neural network. Proper modifications in the definition of the bias of the neurons have been introduced to incorporate image characteristics. The method overcomes distortions in the expected image pattern, such as due to the presence of calcium, and employs a specialized structure of the neural network and boundary correction schemes which are based on a priori knowledge about the vessel geometry. The presented method is very fast and has been evaluated using sequences of IVUS frames.

  17. Automatic active contour-based segmentation and classification of carotid artery ultrasound images.

    PubMed

    Chaudhry, Asmatullah; Hassan, Mehdi; Khan, Asifullah; Kim, Jin Young

    2013-12-01

    In this paper, we present automatic image segmentation and classification technique for carotid artery ultrasound images based on active contour approach. For early detection of the plaque in carotid artery to avoid serious brain strokes, active contour-based techniques have been applied successfully to segment out the carotid artery ultrasound images. Further, ultrasound images might be affected due to rotation, scaling, or translational factors during acquisition process. Keeping in view these facts, image alignment is used as a preprocessing step to align the carotid artery ultrasound images. In our experimental study, we exploit intima-media thickness (IMT) measurement to detect the presence of plaque in the artery. Support vector machine (SVM) classification is employed using these segmented images to distinguish the normal and diseased artery images. IMT measurement is used to form the feature vector. Our proposed approach segments the carotid artery images in an automatic way and further classifies them using SVM. Experimental results show the learning capability of SVM classifier and validate the usefulness of our proposed approach. Further, the proposed approach needs minimum interaction from a user for an early detection of plaque in carotid artery. Regarding the usefulness of the proposed approach in healthcare, it can be effectively used in remote areas as a preliminary clinical step even in the absence of highly skilled radiologists.

  18. An active contour framework based on the Hermite transform for shape segmentation of cardiac MR images

    NASA Astrophysics Data System (ADS)

    Barba-J, Leiner; Escalante-Ramírez, Boris

    2016-04-01

    Early detection of cardiac affections is fundamental to address a correct treatment that allows preserving the patient's life. Since heart disease is one of the main causes of death in most countries, analysis of cardiac images is of great value for cardiac assessment. Cardiac MR has become essential for heart evaluation. In this work we present a segmentation framework for shape analysis in cardiac magnetic resonance (MR) images. The method consists of an active contour model which is guided by the spectral coefficients obtained from the Hermite transform (HT) of the data. The HT is used as model to code image features of the analyzed images. Region and boundary based energies are coded using the zero and first order coefficients. An additional shape constraint based on an elliptical function is used for controlling the active contour deformations. The proposed framework is applied to the segmentation of the endocardial and epicardial boundaries of the left ventricle using MR images with short axis view. The segmentation is sequential for both regions: the endocardium is segmented followed by the epicardium. The algorithm is evaluated with several MR images at different phases of the cardiac cycle demonstrating the effectiveness of the proposed method. Several metrics are used for performance evaluation.

  19. Active Geodesics: Region-based Active Contour Segmentation with a Global Edge-based Constraint.

    PubMed

    Appia, Vikram; Yezzi, Anthony

    2011-11-01

    We present an active geodesic contour model in which we constrain the evolving active contour to be a geodesic with respect to a weighted edge-based energy through its entire evolution rather than just at its final state (as in the traditional geodesic active contour models). Since the contour is always a geodesic throughout the evolution, we automatically get local optimality with respect to an edge fitting criterion. This enables us to construct a purely region-based energy minimization model without having to devise arbitrary weights in the combination of our energy function to balance edge-based terms with the region-based terms. We show that this novel approach of combining edge information as the geodesic constraint in optimizing a purely region-based energy yields a new class of active contours which exhibit both local and global behaviors that are naturally responsive to intuitive types of user interaction. We also show the relationship of this new class of globally constrained active contours with traditional minimal path methods, which seek global minimizers of purely edge-based energies without incorporating region-based criteria. Finally, we present some numerical examples to illustrate the benefits of this approach over traditional active contour models.

  20. Locally constrained active contour: a region-based level set for ovarian cancer metastasis segmentation

    NASA Astrophysics Data System (ADS)

    Liu, Jianfei; Yao, Jianhua; Wang, Shijun; Linguraru, Marius George; Summers, Ronald M.

    2014-03-01

    Accurate segmentation of ovarian cancer metastases is clinically useful to evaluate tumor growth and determine follow-up treatment. We present a region-based level set algorithm with localization constraints to segment ovarian cancer metastases. Our approach is established on a representative region-based level set, Chan-Vese model, in which an active contour is driven by region competition. To reduce over-segmentation, we constrain the level set propagation within a narrow image band by embedding a dynamic localization function. The metastasis intensity prior is also estimated from image regions within the level set initialization. The localization function and intensity prior force the level set to stop at the desired metastasis boundaries. Our approach was validated on 19 ovarian cancer metastases with radiologist-labeled ground-truth on contrast-enhanced CT scans from 15 patients. The comparison between our algorithm and geodesic active contour indicated that the volume overlap was 75+/-10% vs. 56+/-6%, the Dice coefficient was 83+/-8% vs. 63+/-8%, and the average surface distance was 2.2+/-0.6mm vs. 4.4+/-0.9mm. Experimental results demonstrated that our algorithm outperformed traditional level set algorithms.

  1. Automatic corpus callosum segmentation using a deformable active Fourier contour model

    NASA Astrophysics Data System (ADS)

    Vachet, Clement; Yvernault, Benjamin; Bhatt, Kshamta; Smith, Rachel G.; Gerig, Guido; Cody Hazlett, Heather; Styner, Martin

    2012-03-01

    The corpus callosum (CC) is a structure of interest in many neuroimaging studies of neuro-developmental pathology such as autism. It plays an integral role in relaying sensory, motor and cognitive information from homologous regions in both hemispheres. We have developed a framework that allows automatic segmentation of the corpus callosum and its lobar subdivisions. Our approach employs constrained elastic deformation of flexible Fourier contour model, and is an extension of Szekely's 2D Fourier descriptor based Active Shape Model. The shape and appearance model, derived from a large mixed population of 150+ subjects, is described with complex Fourier descriptors in a principal component shape space. Using MNI space aligned T1w MRI data, the CC segmentation is initialized on the mid-sagittal plane using the tissue segmentation. A multi-step optimization strategy, with two constrained steps and a final unconstrained step, is then applied. If needed, interactive segmentation can be performed via contour repulsion points. Lobar connectivity based parcellation of the corpus callosum can finally be computed via the use of a probabilistic CC subdivision model. Our analysis framework has been integrated in an open-source, end-to-end application called CCSeg both with a command line and Qt-based graphical user interface (available on NITRC). A study has been performed to quantify the reliability of the semi-automatic segmentation on a small pediatric dataset. Using 5 subjects randomly segmented 3 times by two experts, the intra-class correlation coefficient showed a superb reliability (0.99). CCSeg is currently applied to a large longitudinal pediatric study of brain development in autism.

  2. Brachial artery vasomotion and transducer pressure effect on measurements by active contour segmentation on ultrasound

    SciTech Connect

    Cary, Theodore W.; Sultan, Laith R.; Sehgal, Chandra M.; Reamer, Courtney B.; Mohler, Emile R.

    2014-02-15

    Purpose: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Methods: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. Results: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. Conclusions: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.

  3. SEGMENTATION OF ELASTOGRAPHIC IMAGES USING A COARSE-TO-FINE ACTIVE CONTOUR MODEL

    PubMed Central

    Liu, Wu; Zagzebski, James A.; Varghese, Tomy; Dyer, Charles R.; Techavipoo, Udomchai; Hall, Timothy J.

    2006-01-01

    Delineation of radiofrequency-ablation-induced coagulation (thermal lesion) boundaries is an important clinical problem that is not well addressed by conventional imaging modalities. Elastography, which produces images of the local strain after small, externally applied compressions, can be used for visualization of thermal coagulations. This paper presents an automated segmentation approach for thermal coagulations on 3-D elastographic data to obtain both area and volume information rapidly. The approach consists of a coarse-to-fine method for active contour initialization and a gradient vector flow, active contour model for deformable contour optimization with the help of prior knowledge of the geometry of general thermal coagulations. The performance of the algorithm has been shown to be comparable to manual delineation of coagulations on elastograms by medical physicists (r = 0.99 for volumes of 36 radiofrequency-induced coagulations). Furthermore, the automatic algorithm applied to elastograms yielded results that agreed with manual delineation of coagulations on pathology images (r = 0.96 for the same 36 lesions). This algorithm has also been successfully applied on in vivo elastograms. PMID:16530098

  4. Real-time 3D medical structure segmentation using fast evolving active contours

    NASA Astrophysics Data System (ADS)

    Wang, Xiaotao; Wang, Qiang; Hao, Zhihui; Xu, Kuanhong; Guo, Ping; Ren, Haibing; Jang, Wooyoung; Kim, Jung-bae

    2014-03-01

    Segmentation of 3D medical structures in real-time is an important as well as intractable problem for clinical applications due to the high computation and memory cost. We propose a novel fast evolving active contour model in this paper to reduce the requirements of computation and memory. The basic idea is to evolve the brief represented dynamic contour interface as far as possible per iteration. Our method encodes zero level set via a single unordered list, and evolves the list recursively by adding activated adjacent neighbors to its end, resulting in active parts of the zero level set moves far enough per iteration along with list scanning. To guarantee the robustness of this process, a new approximation of curvature for integer valued level set is proposed as the internal force to penalize the list smoothness and restrain the list continual growth. Besides, list scanning times are also used as an upper hard constraint to control the list growing. Together with the internal force, efficient regional and constrained external forces, whose computations are only performed along the unordered list, are also provided to attract the list toward object boundaries. Specially, our model calculates regional force only in a narrowband outside the zero level set and can efficiently segment multiple regions simultaneously as well as handle the background with multiple components. Compared with state-of-the-art algorithms, our algorithm is one-order of magnitude faster with similar segmentation accuracy and can achieve real-time performance for the segmentation of 3D medical structures on a standard PC.

  5. AUTOMATED ACTIN FILAMENT SEGMENTATION, TRACKING AND TIP ELONGATION MEASUREMENTS BASED ON OPEN ACTIVE CONTOUR MODELS.

    PubMed

    Li, Hongsheng; Shen, Tian; Smith, Matthew B; Fujiwara, Ikuko; Vavylonis, Dimitrios; Huang, Xiaolei

    2009-06-28

    This paper presents an automated method for actin filament segmentation and tracking for measuring tip elongation rates in Total Internal Reflection Fluorescence Microscopy (TIRFM) images. The main contributions of the paper are: (i) we use a novel open active contour model for filament segmentation and tracking, which is fast and robust against noise; (ii) different strategies are proposed to solve the filament intersection problem, which is shown to be the main difficulty in filament tracking; and (iii) this fully automated method avoids the need of human interaction and thus reduces required time for the entire elongation measurement process on an image sequence. Application to experimental results demonstrated the robustness and effectiveness of this method.

  6. Spectral embedding based active contour (SEAC): application to breast lesion segmentation on DCE-MRI

    NASA Astrophysics Data System (ADS)

    Agner, Shannon C.; Xu, Jun; Rosen, Mark; Karthigeyan, Sudha; Englander, Sarah; Madabhushi, Anant

    2011-03-01

    Spectral embedding (SE), a graph-based manifold learning method, has previously been shown to be useful in high dimensional data classification. In this work, we present a novel SE based active contour (SEAC) segmentation scheme and demonstrate its applications in lesion segmentation on breast dynamic contrast enhance magnetic resonance imaging (DCE-MRI). In this work, we employ SE on DCE-MRI on a per voxel basis to embed the high dimensional time series intensity vector into a reduced dimensional space, where the reduced embedding space is characterized by the principal eigenvectors. The orthogonal eigenvector-based data representation allows for computation of strong tensor gradients in the spectrally embedded space and also yields improved region statistics that serve as optimal stopping criteria for SEAC. We demonstrate both analytically and empirically that the tensor gradients in the spectrally embedded space are stronger than the corresponding gradients in the original grayscale intensity space. On a total of 50 breast DCE-MRI studies, SEAC yielded a mean absolute difference (MAD) of 3.2+/-2.1 pixels and mean Dice similarity coefficient (DSC) of 0.74+/-0.13 compared to manual ground truth segmentation. An active contour in conjunction with fuzzy c-means (FCM+AC), a commonly used segmentation method for breast DCE-MRI, produced a corresponding MAD of 7.2+/-7.4 pixels and mean DSC of 0.58+/-0.32. In conjunction with a set of 6 quantitative morphological features automatically extracted from the SEAC derived lesion boundary, a support vector machine (SVM) classifier yielded an area under the curve (AUC) of 0.73, for discriminating between 10 benign and 30 malignant lesions; the corresponding SVM classifier with the FCM+AC derived morphological features yielded an AUC of 0.65.

  7. Integrating multiscale polar active contours and region growing for microcalcifications segmentation in mammography

    NASA Astrophysics Data System (ADS)

    Arikidis, N. S.; Karahaliou, A.; Skiadopoulos, S.; Likaki, E.; Panagiotakis, G.; Costaridou, L.

    2009-07-01

    Morphology of individual microcalcifications is an important clinical factor in microcalcification clusters diagnosis. Accurate segmentation remains a difficult task due to microcalcifications small size, low contrast, fuzzy nature and low distinguishability from surrounding tissue. A novel application of active rays (polar transformed active contours) on B-spline wavelet representation is employed, to provide initial estimates of microcalcification boundary. Then, a region growing method is used with pixel aggregation constrained by the microcalcification boundary estimates, to obtain the final microcalcification boundary. The method was tested on dataset of 49 microcalcification clusters (30 benign, 19 malignant), originating from the DDSM database. An observer study was conducted to evaluate segmentation accuracy of the proposed method, on a 5-point rating scale (from 5:excellent to 1:very poor). The average accuracy rating was 3.98±0.81 when multiscale active rays were combined to region growing and 2.93±0.92 when combined to linear polynomial fitting, while the difference in rating of segmentation accuracy was statistically significant (p < 0.05).

  8. CT liver volumetry using geodesic active contour segmentation with a level-set algorithm

    NASA Astrophysics Data System (ADS)

    Suzuki, Kenji; Epstein, Mark L.; Kohlbrenner, Ryan; Obajuluwa, Ademola; Xu, Jianwu; Hori, Masatoshi; Baron, Richard

    2010-03-01

    Automatic liver segmentation on CT images is challenging because the liver often abuts other organs of a similar density. Our purpose was to develop an accurate automated liver segmentation scheme for measuring liver volumes. We developed an automated volumetry scheme for the liver in CT based on a 5 step schema. First, an anisotropic smoothing filter was applied to portal-venous phase CT images to remove noise while preserving the liver structure, followed by an edge enhancer to enhance the liver boundary. By using the boundary-enhanced image as a speed function, a fastmarching algorithm generated an initial surface that roughly estimated the liver shape. A geodesic-active-contour segmentation algorithm coupled with level-set contour-evolution refined the initial surface so as to more precisely fit the liver boundary. The liver volume was calculated based on the refined liver surface. Hepatic CT scans of eighteen prospective liver donors were obtained under a liver transplant protocol with a multi-detector CT system. Automated liver volumes obtained were compared with those manually traced by a radiologist, used as "gold standard." The mean liver volume obtained with our scheme was 1,520 cc, whereas the mean manual volume was 1,486 cc, with the mean absolute difference of 104 cc (7.0%). CT liver volumetrics based on an automated scheme agreed excellently with "goldstandard" manual volumetrics (intra-class correlation coefficient was 0.95) with no statistically significant difference (p(F<=f)=0.32), and required substantially less completion time. Our automated scheme provides an efficient and accurate way of measuring liver volumes.

  9. Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours.

    PubMed

    Molnar, Csaba; Jermyn, Ian H; Kato, Zoltan; Rahkama, Vesa; Östling, Päivi; Mikkonen, Piia; Pietiäinen, Vilja; Horvath, Peter

    2016-01-01

    The identification of fluorescently stained cell nuclei is the basis of cell detection, segmentation, and feature extraction in high content microscopy experiments. The nuclear morphology of single cells is also one of the essential indicators of phenotypic variation. However, the cells used in experiments can lose their contact inhibition, and can therefore pile up on top of each other, making the detection of single cells extremely challenging using current segmentation methods. The model we present here can detect cell nuclei and their morphology even in high-confluency cell cultures with many overlapping cell nuclei. We combine the "gas of near circles" active contour model, which favors circular shapes but allows slight variations around them, with a new data model. This captures a common property of many microscopic imaging techniques: the intensities from superposed nuclei are additive, so that two overlapping nuclei, for example, have a total intensity that is approximately double the intensity of a single nucleus. We demonstrate the power of our method on microscopic images of cells, comparing the results with those obtained from a widely used approach, and with manual image segmentations by experts. PMID:27561654

  10. Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours

    PubMed Central

    Molnar, Csaba; Jermyn, Ian H.; Kato, Zoltan; Rahkama, Vesa; Östling, Päivi; Mikkonen, Piia; Pietiäinen, Vilja; Horvath, Peter

    2016-01-01

    The identification of fluorescently stained cell nuclei is the basis of cell detection, segmentation, and feature extraction in high content microscopy experiments. The nuclear morphology of single cells is also one of the essential indicators of phenotypic variation. However, the cells used in experiments can lose their contact inhibition, and can therefore pile up on top of each other, making the detection of single cells extremely challenging using current segmentation methods. The model we present here can detect cell nuclei and their morphology even in high-confluency cell cultures with many overlapping cell nuclei. We combine the “gas of near circles” active contour model, which favors circular shapes but allows slight variations around them, with a new data model. This captures a common property of many microscopic imaging techniques: the intensities from superposed nuclei are additive, so that two overlapping nuclei, for example, have a total intensity that is approximately double the intensity of a single nucleus. We demonstrate the power of our method on microscopic images of cells, comparing the results with those obtained from a widely used approach, and with manual image segmentations by experts. PMID:27561654

  11. A validated active contour method driven by parabolic arc model for detection and segmentation of mitochondria.

    PubMed

    Tasel, Serdar F; Mumcuoglu, Erkan U; Hassanpour, Reza Z; Perkins, Guy

    2016-06-01

    Recent studies reveal that mitochondria take substantial responsibility in cellular functions that are closely related to aging diseases caused by degeneration of neurons. These studies emphasize that the membrane and crista morphology of a mitochondrion should receive attention in order to investigate the link between mitochondrial function and its physical structure. Electron microscope tomography (EMT) allows analysis of the inner structures of mitochondria by providing highly detailed visual data from large volumes. Computerized segmentation of mitochondria with minimum manual effort is essential to accelerate the study of mitochondrial structure/function relationships. In this work, we improved and extended our previous attempts to detect and segment mitochondria from transmission electron microcopy (TEM) images. A parabolic arc model was utilized to extract membrane structures. Then, curve energy based active contours were employed to obtain roughly outlined candidate mitochondrial regions. Finally, a validation process was applied to obtain the final segmentation data. 3D extension of the algorithm is also presented in this paper. Our method achieved an average F-score performance of 0.84. Average Dice Similarity Coefficient and boundary error were measured as 0.87 and 14nm respectively.

  12. Harmonic active contours.

    PubMed

    Estellers, Virginia; Zosso, Dominique; Bresson, Xavier; Thiran, Jean-Philippe

    2014-01-01

    We propose a segmentation method based on the geometric representation of images as 2-D manifolds embedded in a higher dimensional space. The segmentation is formulated as a minimization problem, where the contours are described by a level set function and the objective functional corresponds to the surface of the image manifold. In this geometric framework, both data-fidelity and regularity terms of the segmentation are represented by a single functional that intrinsically aligns the gradients of the level set function with the gradients of the image and results in a segmentation criterion that exploits the directional information of image gradients to overcome image inhomogeneities and fragmented contours. The proposed formulation combines this robust alignment of gradients with attractive properties of previous methods developed in the same geometric framework: 1) the natural coupling of image channels proposed for anisotropic diffusion and 2) the ability of subjective surfaces to detect weak edges and close fragmented boundaries. The potential of such a geometric approach lies in the general definition of Riemannian manifolds, which naturally generalizes existing segmentation methods (the geodesic active contours, the active contours without edges, and the robust edge integrator) to higher dimensional spaces, non-flat images, and feature spaces. Our experiments show that the proposed technique improves the segmentation of multi-channel images, images subject to inhomogeneities, and images characterized by geometric structures like ridges or valleys.

  13. An automated approach for segmentation of intravascular ultrasound images based on parametric active contour models.

    PubMed

    Vard, Alireza; Jamshidi, Kamal; Movahhedinia, Naser

    2012-06-01

    This paper presents a fully automated approach to detect the intima and media-adventitia borders in intravascular ultrasound images based on parametric active contour models. To detect the intima border, we compute a new image feature applying a combination of short-term autocorrelations calculated for the contour pixels. These feature values are employed to define an energy function of the active contour called normalized cumulative short-term autocorrelation. Exploiting this energy function, the intima border is separated accurately from the blood region contaminated by high speckle noise. To extract media-adventitia boundary, we define a new form of energy function based on edge, texture and spring forces for the active contour. Utilizing this active contour, the media-adventitia border is identified correctly even in presence of branch openings and calcifications. Experimental results indicate accuracy of the proposed methods. In addition, statistical analysis demonstrates high conformity between manual tracing and the results obtained by the proposed approaches.

  14. Active contours driven by local and global intensity fitting energy with application to brain MR image segmentation.

    PubMed

    Wang, Li; Li, Chunming; Sun, Quansen; Xia, Deshen; Kao, Chiu-Yen

    2009-10-01

    In this paper, we propose an improved region-based active contour model in a variational level set formulation. We define an energy functional with a local intensity fitting term, which induces a local force to attract the contour and stops it at object boundaries, and an auxiliary global intensity fitting term, which drives the motion of the contour far away from object boundaries. Therefore, the combination of these two forces allows for flexible initialization of the contours. This energy is then incorporated into a level set formulation with a level set regularization term that is necessary for accurate computation in the corresponding level set method. The proposed model is first presented as a two-phase level set formulation and then extended to a multi-phase formulation. Experimental results show the advantages of our method in terms of accuracy and robustness. In particular, our method has been applied to brain MR image segmentation with desirable results.

  15. Markov random field driven region-based active contour model (MaRACel): application to medical image segmentation.

    PubMed

    Xu, Jun; Monaco, James P; Madabhushi, Anant

    2010-01-01

    In this paper we present a Markov random field (MRF) driven region-based active contour model (MaRACel) for medical image segmentation. State-of-the-art region-based active contour (RAC) models assume that every spatial location in the image is statistically independent of the others, thereby ignoring valuable contextual information. To address this shortcoming we incorporate a MRF prior into the AC model, further generalizing Chan & Vese's (CV) and Rousson and Deriche's (RD) AC models. This incorporation requires a Markov prior that is consistent with the continuous variational framework characteristic of active contours; consequently, we introduce a continuous analogue to the discrete Potts model. To demonstrate the effectiveness of MaRACel, we compare its performance to those of the CV and RD AC models in the following scenarios: (1) the qualitative segmentation of a cancerous lesion in a breast DCE-MR image and (2) the qualitative and quantitative segmentations of prostatic acini (glands) in 200 histopathology images. Across the 200 prostate needle core biopsy histology images, MaRACel yielded an average sensitivity, specificity, and positive predictive value of 71%, 95%, 74% with respect to the segmented gland boundaries; the CV and RD models have corresponding values of 19%, 81%, 20% and 53%, 88%, 56%, respectively.

  16. Finsler Active Contours

    PubMed Central

    Melonakos, John; Pichon, Eric; Angenent, Sigurd; Tannenbaum, Allen

    2009-01-01

    In this paper, we propose an image segmentation technique based on augmenting the conformal (or geodesic) active contour framework with directional information. In the isotropic case, the euclidean metric is locally multiplied by a scalar conformal factor based on image information such that the weighted length of curves lying on points of interest (typically edges) is small. The conformal factor that is chosen depends only upon position and is in this sense isotropic. Although directional information has been studied previously for other segmentation frameworks, here, we show that if one desires to add directionality in the conformal active contour framework, then one gets a well-defined minimization problem in the case that the factor defines a Finsler metric. Optimal curves may be obtained using the calculus of variations or dynamic programming-based schemes. Finally, we demonstrate the technique by extracting roads from aerial imagery, blood vessels from medical angiograms, and neural tracts from diffusion-weighted magnetic resonance imagery. PMID:18195436

  17. Segmentation of Uterus Using Laparoscopic Ultrasound by an Image-Based Active Contour Approach for Guiding Gynecological Diagnosis and Surgery.

    PubMed

    Gong, Xue-Hao; Lu, Jun; Liu, Jin; Deng, Ying-Yuan; Liu, Wei-Zong; Huang, Xian; Yang, Yong-Heng; Xu, Qin; Yu, Zhi-Ying

    2015-01-01

    In laparoscopic gynecologic surgery, ultrasound has been typically implemented to diagnose urological and gynecological conditions. We applied laparoscopic ultrasonography (using Esaote 7.5~10MHz laparoscopic transducer) on the retrospective analyses of 42 women subjects during laparoscopic extirpation and excision of gynecological tumors in our hospital from August 2011 to August 2013. The objective of our research is to develop robust segmentation technique for isolation and identification of the uterus from the ultrasound images, so as to assess, locate and guide in removing the lesions during laparoscopic operations. Our method enables segmentation of the uterus by the active contour algorithm. We evaluated 42 in-vivo laparoscopic images acquired from the 42 patients (age 39.1 ± 7.2 years old) and selected images pertaining to 4 cases of congenital uterine malformations and 2 cases of pelvic adhesions masses. These cases (n = 6) were used for our uterus segmentation experiments. Based on them, the active contour method was compared with the manual segmentation method by a medical expert using linear regression and the Bland-Altman analysis (used to measure the correlation and the agreement). Then, the Dice and Jaccard indices are computed for measuring the similarity of uterus segmented between computational and manual methods. Good correlation was achieved whereby 84%-92% results fall within the 95% confidence interval in the Student t-test) and we demonstrate that the proposed segmentation method of uterus using laparoscopic images is effective.

  18. Segmentation of follicular regions on H&E slides using a matching filter and active contour model

    NASA Astrophysics Data System (ADS)

    Belkacem-Boussaid, Kamel; Prescott, Jeffrey; Lozanski, Gerard; Gurcan, Metin N.

    2010-03-01

    Follicular Lymphoma (FL) accounts for 20-25% of non-Hodgkin lymphomas in the United States. The first step in follicular lymphoma grading is the identification of follicles. The goal of this paper is to develop a technique to segment follicular regions in H&E stained images. The method is based on a robust active contour model, which is initialized by a seed point selected inside the follicle manually by the user. The novel aspect of this method is the introduction of a matched filter for the flattening of background in the L channel of the Lab color space. The performance of the algorithm was tested by comparing it against the manual segmentations of trained readers using the Zijbendos similarity index. The mean accuracy of the final segmentation compared to the manual ground truth was 0.71 with a standard deviation of 0.12.

  19. A new background distribution-based active contour model for three-dimensional lesion segmentation in breast DCE-MRI

    SciTech Connect

    Liu, Hui; Liu, Yiping; Qiu, Tianshuang; Zhao, Zuowei; Zhang, Lina

    2014-08-15

    Purpose: To develop and evaluate a computerized semiautomatic segmentation method for accurate extraction of three-dimensional lesions from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) of the breast. Methods: The authors propose a new background distribution-based active contour model using level set (BDACMLS) to segment lesions in breast DCE-MRIs. The method starts with manual selection of a region of interest (ROI) that contains the entire lesion in a single slice where the lesion is enhanced. Then the lesion volume from the volume data of interest, which is captured automatically, is separated. The core idea of BDACMLS is a new signed pressure function which is based solely on the intensity distribution combined with pathophysiological basis. To compare the algorithm results, two experienced radiologists delineated all lesions jointly to obtain the ground truth. In addition, results generated by other different methods based on level set (LS) are also compared with the authors’ method. Finally, the performance of the proposed method is evaluated by several region-based metrics such as the overlap ratio. Results: Forty-two studies with 46 lesions that contain 29 benign and 17 malignant lesions are evaluated. The dataset includes various typical pathologies of the breast such as invasive ductal carcinoma, ductal carcinomain situ, scar carcinoma, phyllodes tumor, breast cysts, fibroadenoma, etc. The overlap ratio for BDACMLS with respect to manual segmentation is 79.55% ± 12.60% (mean ± s.d.). Conclusions: A new active contour model method has been developed and shown to successfully segment breast DCE-MRI three-dimensional lesions. The results from this model correspond more closely to manual segmentation, solve the weak-edge-passed problem, and improve the robustness in segmenting different lesions.

  20. Myocardial Iron Loading Assessment by Automatic Left Ventricle Segmentation with Morphological Operations and Geodesic Active Contour on T2* images

    NASA Astrophysics Data System (ADS)

    Luo, Yun-Gang; Ko, Jacky Kl; Shi, Lin; Guan, Yuefeng; Li, Linong; Qin, Jing; Heng, Pheng-Ann; Chu, Winnie Cw; Wang, Defeng

    2015-07-01

    Myocardial iron loading thalassemia patients could be identified using T2* magnetic resonance images (MRI). To quantitatively assess cardiac iron loading, we proposed an effective algorithm to segment aligned free induction decay sequential myocardium images based on morphological operations and geodesic active contour (GAC). Nine patients with thalassemia major were recruited (10 male and 16 female) to undergo a thoracic MRI scan in the short axis view. Free induction decay images were registered for T2* mapping. The GAC were utilized to segment aligned MR images with a robust initialization. Segmented myocardium regions were divided into sectors for a region-based quantification of cardiac iron loading. Our proposed automatic segmentation approach achieve a true positive rate at 84.6% and false positive rate at 53.8%. The area difference between manual and automatic segmentation was 25.5% after 1000 iterations. Results from T2* analysis indicated that regions with intensity lower than 20 ms were suffered from heavy iron loading in thalassemia major patients. The proposed method benefited from abundant edge information of the free induction decay sequential MRI. Experiment results demonstrated that the proposed method is feasible in myocardium segmentation and was clinically applicable to measure myocardium iron loading.

  1. Myocardial Iron Loading Assessment by Automatic Left Ventricle Segmentation with Morphological Operations and Geodesic Active Contour on T2* images

    PubMed Central

    Luo, Yun-gang; Ko, Jacky KL; Shi, Lin; Guan, Yuefeng; Li, Linong; Qin, Jing; Heng, Pheng-Ann; Chu, Winnie CW; Wang, Defeng

    2015-01-01

    Myocardial iron loading thalassemia patients could be identified using T2* magnetic resonance images (MRI). To quantitatively assess cardiac iron loading, we proposed an effective algorithm to segment aligned free induction decay sequential myocardium images based on morphological operations and geodesic active contour (GAC). Nine patients with thalassemia major were recruited (10 male and 16 female) to undergo a thoracic MRI scan in the short axis view. Free induction decay images were registered for T2* mapping. The GAC were utilized to segment aligned MR images with a robust initialization. Segmented myocardium regions were divided into sectors for a region-based quantification of cardiac iron loading. Our proposed automatic segmentation approach achieve a true positive rate at 84.6% and false positive rate at 53.8%. The area difference between manual and automatic segmentation was 25.5% after 1000 iterations. Results from T2* analysis indicated that regions with intensity lower than 20 ms were suffered from heavy iron loading in thalassemia major patients. The proposed method benefited from abundant edge information of the free induction decay sequential MRI. Experiment results demonstrated that the proposed method is feasible in myocardium segmentation and was clinically applicable to measure myocardium iron loading. PMID:26215336

  2. Computer-aided diagnosis of pulmonary nodules on CT scans: Segmentation and classification using 3D active contours

    PubMed Central

    Way, Ted W.; Hadjiiski, Lubomir M.; Sahiner, Berkman; Chan, Heang-Ping; Cascade, Philip N.; Kazerooni, Ella A.; Bogot, Naama; Zhou, Chuan

    2009-01-01

    We are developing a computer-aided diagnosis (CAD) system to classify malignant and benign lung nodules found on CT scans. A fully automated system was designed to segment the nodule from its surrounding structured background in a local volume of interest (VOI) and to extract image features for classification. Image segmentation was performed with a three-dimensional (3D) active contour (AC) method. A data set of 96 lung nodules (44 malignant, 52 benign) from 58 patients was used in this study. The 3D AC model is based on two-dimensional AC with the addition of three new energy components to take advantage of 3D information: (1) 3D gradient, which guides the active contour to seek the object surface, (2) 3D curvature, which imposes a smoothness constraint in the z direction, and (3) mask energy, which penalizes contours that grow beyond the pleura or thoracic wall. The search for the best energy weights in the 3D AC model was guided by a simplex optimization method. Morphological and gray-level features were extracted from the segmented nodule. The rubber band straightening transform (RBST) was applied to the shell of voxels surrounding the nodule. Texture features based on run-length statistics were extracted from the RBST image. A linear discriminant analysis classifier with stepwise feature selection was designed using a second simplex optimization to select the most effective features. Leave-one-case-out resampling was used to train and test the CAD system. The system achieved a test area under the receiver operating characteristic curve (Az) of 0.83±0.04. Our preliminary results indicate that use of the 3D AC model and the 3D texture features surrounding the nodule is a promising approach to the segmentation and classification of lung nodules with CAD. The segmentation performance of the 3D AC model trained with our data set was evaluated with 23 nodules available in the Lung Image Database Consortium (LIDC). The lung nodule volumes segmented by the 3D AC

  3. A weighted mean shift, normalized cuts initialized color gradient based geodesic active contour model: applications to histopathology image segmentation

    NASA Astrophysics Data System (ADS)

    Xu, Jun; Janowczyk, Andrew; Chandran, Sharat; Madabhushi, Anant

    2010-03-01

    While geodesic active contours (GAC) have become very popular tools for image segmentation, they are sensitive to model initialization. In order to get an accurate segmentation, the model typically needs to be initialized very close to the true object boundary. Apart from accuracy, automated initialization of the objects of interest is an important pre-requisite to being able to run the active contour model on very large images (such as those found in digitized histopathology). A second limitation of GAC model is that the edge detector function is based on gray scale gradients; color images typically being converted to gray scale prior to computing the gradient. For color images, however, the gray scale gradient results in broken edges and weak boundaries, since the other channels are not exploited for the gradient determination. In this paper we present a new geodesic active contour model that is driven by an accurate and rapid object initialization scheme-weighted mean shift normalized cuts (WNCut). WNCut draws its strength from the integration of two powerful segmentation strategies-mean shift clustering and normalized cuts. WNCut involves first defining a color swatch (typically a few pixels) from the object of interest. A multi-scale mean shift coupled normalized cuts algorithm then rapidly yields an initial accurate detection of all objects in the scene corresponding to the colors in the swatch. This detection result provides the initial boundary for GAC model. The edge-detector function of the GAC model employs a local structure tensor based color gradient, obtained by calculating the local min/max variations contributed from each color channel (e.g. R,G,B or H,S,V). Our color gradient based edge-detector function results in more prominent boundaries compared to classical gray scale gradient based function. We evaluate segmentation results of our new WNCut initialized color gradient based GAC (WNCut-CGAC) model against a popular region-based model (Chan

  4. Segmentation of solid subregion of high grade gliomas in MRI images based on active contour model (ACM)

    NASA Astrophysics Data System (ADS)

    Seow, P.; Win, M. T.; Wong, J. H. D.; Abdullah, N. A.; Ramli, N.

    2016-03-01

    Gliomas are tumours arising from the interstitial tissue of the brain which are heterogeneous, infiltrative and possess ill-defined borders. Tumour subregions (e.g. solid enhancing part, edema and necrosis) are often used for tumour characterisation. Tumour demarcation into substructures facilitates glioma staging and provides essential information. Manual segmentation had several drawbacks that include laborious, time consuming, subjected to intra and inter-rater variability and hindered by diversity in the appearance of tumour tissues. In this work, active contour model (ACM) was used to segment the solid enhancing subregion of the tumour. 2D brain image acquisition data using 3T MRI fast spoiled gradient echo sequence in post gadolinium of four histologically proven high-grade glioma patients were obtained. Preprocessing of the images which includes subtraction and skull stripping were performed and then followed by ACM segmentation. The results of the automatic segmentation method were compared against the manual delineation of the tumour by a trainee radiologist. Both results were further validated by an experienced neuroradiologist and a brief quantitative evaluations (pixel area and difference ratio) were performed. Preliminary results of the clinical data showed the potential of ACM model in the application of fast and large scale tumour segmentation in medical imaging.

  5. New Region-Scalable Discriminant and Fitting Energy Functional for Driving Geometric Active Contours in Medical Image Segmentation

    PubMed Central

    Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

    2014-01-01

    We propose a novel region-based geometric active contour model that uses region-scalable discriminant and fitting energy functional for handling the intensity inhomogeneity and weak boundary problems in medical image segmentation. The region-scalable discriminant and fitting energy functional is defined to capture the image intensity characteristics in local and global regions for driving the evolution of active contour. The discriminant term in the model aims at separating background and foreground in scalable regions while the fitting term tends to fit the intensity in these regions. This model is then transformed into a variational level set formulation with a level set regularization term for accurate computation. The new model utilizes intensity information in the local and global regions as much as possible; so it not only handles better intensity inhomogeneity, but also allows more robustness to noise and more flexible initialization in comparison to the original global region and regional-scalable based models. Experimental results for synthetic and real medical image segmentation show the advantages of the proposed method in terms of accuracy and robustness. PMID:25110513

  6. pSnakes: a new radial active contour model and its application in the segmentation of the left ventricle from echocardiographic images.

    PubMed

    de Alexandria, Auzuir Ripardo; Cortez, Paulo César; Bessa, Jessyca Almeida; da Silva Félix, John Hebert; de Abreu, José Sebastião; de Albuquerque, Victor Hugo C

    2014-10-01

    Active contours are image segmentation methods that minimize the total energy of the contour to be segmented. Among the active contour methods, the radial methods have lower computational complexity and can be applied in real time. This work aims to present a new radial active contour technique, called pSnakes, using the 1D Hilbert transform as external energy. The pSnakes method is based on the fact that the beams in ultrasound equipment diverge from a single point of the probe, thus enabling the use of polar coordinates in the segmentation. The control points or nodes of the active contour are obtained in pairs and are called twin nodes. The internal energies as well as the external one, Hilbertian energy, are redefined. The results showed that pSnakes can be used in image segmentation of short-axis echocardiogram images and that they were effective in image segmentation of the left ventricle. The echo-cardiologist's golden standard showed that the pSnakes was the best method when compared with other methods. The main contributions of this work are the use of pSnakes and Hilbertian energy, as the external energy, in image segmentation. The Hilbertian energy is calculated by the 1D Hilbert transform. Compared with traditional methods, the pSnakes method is more suitable for ultrasound images because it is not affected by variations in image contrast, such as noise. The experimental results obtained by the left ventricle segmentation of echocardiographic images demonstrated the advantages of the proposed model. The results presented in this paper are justified due to an improved performance of the Hilbert energy in the presence of speckle noise.

  7. Automatic segmentation of head and neck CT images for radiotherapy treatment planning using multiple atlases, statistical appearance models, and geodesic active contours

    SciTech Connect

    Fritscher, Karl D. Sharp, Gregory; Peroni, Marta; Zaffino, Paolo; Spadea, Maria Francesca; Schubert, Rainer

    2014-05-15

    Purpose: Accurate delineation of organs at risk (OARs) is a precondition for intensity modulated radiation therapy. However, manual delineation of OARs is time consuming and prone to high interobserver variability. Because of image artifacts and low image contrast between different structures, however, the number of available approaches for autosegmentation of structures in the head-neck area is still rather low. In this project, a new approach for automated segmentation of head-neck CT images that combine the robustness of multiatlas-based segmentation with the flexibility of geodesic active contours and the prior knowledge provided by statistical appearance models is presented. Methods: The presented approach is using an atlas-based segmentation approach in combination with label fusion in order to initialize a segmentation pipeline that is based on using statistical appearance models and geodesic active contours. An anatomically correct approximation of the segmentation result provided by atlas-based segmentation acts as a starting point for an iterative refinement of this approximation. The final segmentation result is based on using model to image registration and geodesic active contours, which are mutually influencing each other. Results: 18 CT images in combination with manually segmented labels of parotid glands and brainstem were used in a leave-one-out cross validation scheme in order to evaluate the presented approach. For this purpose, 50 different statistical appearance models have been created and used for segmentation. Dice coefficient (DC), mean absolute distance and max. Hausdorff distance between the autosegmentation results and expert segmentations were calculated. An average Dice coefficient of DC = 0.81 (right parotid gland), DC = 0.84 (left parotid gland), and DC = 0.86 (brainstem) could be achieved. Conclusions: The presented framework provides accurate segmentation results for three important structures in the head neck area. Compared to a

  8. Concurrent multimodality image segmentation by active contours for radiotherapy treatment planning

    SciTech Connect

    El Naqa, Issam; Yang Deshan; Apte, Aditya; Khullar, Divya; Mutic, Sasa; Zheng Jie; Bradley, Jeffrey D.; Grigsby, Perry; Deasy, Joseph O.

    2007-12-15

    Multimodality imaging information is regularly used now in radiotherapy treatment planning for cancer patients. The authors are investigating methods to take advantage of all the imaging information available for joint target registration and segmentation, including multimodality images or multiple image sets from the same modality. In particular, the authors have developed variational methods based on multivalued level set deformable models for simultaneous 2D or 3D segmentation of multimodality images consisting of combinations of coregistered PET, CT, or MR data sets. The combined information is integrated to define the overall biophysical structure volume. The authors demonstrate the methods on three patient data sets, including a nonsmall cell lung cancer case with PET/CT, a cervix cancer case with PET/CT, and a prostate patient case with CT and MRI. CT, PET, and MR phantom data were also used for quantitative validation of the proposed multimodality segmentation approach. The corresponding Dice similarity coefficient (DSC) was 0.90{+-}0.02 (p<0.0001) with an estimated target volume error of 1.28{+-}1.23% volume. Preliminary results indicate that concurrent multimodality segmentation methods can provide a feasible and accurate framework for combining imaging data from different modalities and are potentially useful tools for the delineation of biophysical structure volumes in radiotherapy treatment planning.

  9. Region-based Active Contour Model based on Markov Random Field to Segment Images with Intensity Non-Uniformity and Noise.

    PubMed

    Shahvaran, Zahra; Kazemi, Kamran; Helfroush, Mohammad Sadegh; Jafarian, Nassim

    2012-01-01

    This paper represents a new region-based active contour model that can be used to segment images with intensity non-uniformity and high-level noise. The main idea of our proposed method is to use Gaussian distributions with different means and variances with incorporation of intensity non-uniformity model for image segmentation. In order to integrate the spatial information between neighboring pixels in our proposed method, we use Markov Random Field. Our experiments on synthetic images and cerebral magnetic resonance images show the advantages of the proposed method over state-of-art methods, i.e. local Gaussian distribution fitting.

  10. Inner and outer coronary vessel wall segmentation from CCTA using an active contour model with machine learning-based 3D voxel context-aware image force

    NASA Astrophysics Data System (ADS)

    Sivalingam, Udhayaraj; Wels, Michael; Rempfler, Markus; Grosskopf, Stefan; Suehling, Michael; Menze, Bjoern H.

    2016-03-01

    In this paper, we present a fully automated approach to coronary vessel segmentation, which involves calcification or soft plaque delineation in addition to accurate lumen delineation, from 3D Cardiac Computed Tomography Angiography data. Adequately virtualizing the coronary lumen plays a crucial role for simulating blood ow by means of fluid dynamics while additionally identifying the outer vessel wall in the case of arteriosclerosis is a prerequisite for further plaque compartment analysis. Our method is a hybrid approach complementing Active Contour Model-based segmentation with an external image force that relies on a Random Forest Regression model generated off-line. The regression model provides a strong estimate of the distance to the true vessel surface for every surface candidate point taking into account 3D wavelet-encoded contextual image features, which are aligned with the current surface hypothesis. The associated external image force is integrated in the objective function of the active contour model, such that the overall segmentation approach benefits from the advantages associated with snakes and from the ones associated with machine learning-based regression alike. This yields an integrated approach achieving competitive results on a publicly available benchmark data collection (Rotterdam segmentation challenge).

  11. Computer-aided measurement of liver volumes in CT by means of geodesic active contour segmentation coupled with level-set algorithms

    SciTech Connect

    Suzuki, Kenji; Kohlbrenner, Ryan; Epstein, Mark L.; Obajuluwa, Ademola M.; Xu Jianwu; Hori, Masatoshi

    2010-05-15

    Purpose: Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT. Methods: The authors developed a computerized liver extraction scheme based on geodesic active contour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic active contour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as ''gold standard.''Results: The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F=0.77; p(F{<=}f)=0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less completion time

  12. An Automatic Segmentation Method Combining an Active Contour Model and a Classification Technique for Detecting Polycomb-group Proteinsin High-Throughput Microscopy Images.

    PubMed

    Gregoretti, Francesco; Cesarini, Elisa; Lanzuolo, Chiara; Oliva, Gennaro; Antonelli, Laura

    2016-01-01

    The large amount of data generated in biological experiments that rely on advanced microscopy can be handled only with automated image analysis. Most analyses require a reliable cell image segmentation eventually capable of detecting subcellular structures.We present an automatic segmentation method to detect Polycomb group (PcG) proteins areas isolated from nuclei regions in high-resolution fluorescent cell image stacks. It combines two segmentation algorithms that use an active contour model and a classification technique serving as a tool to better understand the subcellular three-dimensional distribution of PcG proteins in live cell image sequences. We obtained accurate results throughout several cell image datasets, coming from different cell types and corresponding to different fluorescent labels, without requiring elaborate adjustments to each dataset. PMID:27659985

  13. Computer-Assisted Segmentation of Videocapsule Images Using Alpha-Divergence-Based Active Contour in the Framework of Intestinal Pathologies Detection

    PubMed Central

    Meziou, L.; Histace, A.; Precioso, F.; Romain, O.; Dray, X.; Granado, B.; Matuszewski, B. J.

    2014-01-01

    Visualization of the entire length of the gastrointestinal tract through natural orifices is a challenge for endoscopists. Videoendoscopy is currently the “gold standard” technique for diagnosis of different pathologies of the intestinal tract. Wireless capsule endoscopy (WCE) has been developed in the 1990s as an alternative to videoendoscopy to allow direct examination of the gastrointestinal tract without any need for sedation. Nevertheless, the systematic postexamination by the specialist of the 50,000 (for the small bowel) to 150,000 images (for the colon) of a complete acquisition using WCE remains time-consuming and challenging due to the poor quality of WCE images. In this paper, a semiautomatic segmentation for analysis of WCE images is proposed. Based on active contour segmentation, the proposed method introduces alpha-divergences, a flexible statistical similarity measure that gives a real flexibility to different types of gastrointestinal pathologies. Results of segmentation using the proposed approach are shown on different types of real-case examinations, from (multi)polyp(s) segmentation, to radiation enteritis delineation. PMID:25587264

  14. Accurate and Fully Automatic Hippocampus Segmentation Using Subject-Specific 3D Optimal Local Maps Into a Hybrid Active Contour Model

    PubMed Central

    Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

    2014-01-01

    Assessing the structural integrity of the hippocampus (HC) is an essential step toward prevention, diagnosis, and follow-up of various brain disorders due to the implication of the structural changes of the HC in those disorders. In this respect, the development of automatic segmentation methods that can accurately, reliably, and reproducibly segment the HC has attracted considerable attention over the past decades. This paper presents an innovative 3-D fully automatic method to be used on top of the multiatlas concept for the HC segmentation. The method is based on a subject-specific set of 3-D optimal local maps (OLMs) that locally control the influence of each energy term of a hybrid active contour model (ACM). The complete set of the OLMs for a set of training images is defined simultaneously via an optimization scheme. At the same time, the optimal ACM parameters are also calculated. Therefore, heuristic parameter fine-tuning is not required. Training OLMs are subsequently combined, by applying an extended multiatlas concept, to produce the OLMs that are anatomically more suitable to the test image. The proposed algorithm was tested on three different and publicly available data sets. Its accuracy was compared with that of state-of-the-art methods demonstrating the efficacy and robustness of the proposed method. PMID:27170866

  15. Segmentation of the common carotid artery walls based on a frequency implementation of active contours: segmentation of the common carotid artery walls.

    PubMed

    Bastida-Jumilla, M Consuelo; Menchón-Lara, Rosa M; Morales-Sánchez, Juan; Verdú-Monedero, Rafael; Larrey-Ruiz, Jorge; Sancho-Gómez, José Luis

    2013-02-01

    Atherosclerosis is one of the most extended cardiovascular diseases nowadays. Although it may be unnoticed during years, it also may suddenly trigger severe illnesses such as stroke, embolisms or ischemia. Therefore, an early detection of atherosclerosis can prevent adult population from suffering more serious pathologies. The intima-media thickness (IMT) of the common carotid artery (CCA) has been used as an early and reliable indicator of atherosclerosis for years. The IMT is manually computed from ultrasound images, a process that can be repeated as many times as necessary (over different ultrasound images of the same patient), but also prone to errors. With the aim to reduce the inter-observer variability and the subjectivity of the measurement, a fully automatic computer-based method based on ultrasound image processing and a frequency-domain implementation of active contours is proposed. The images used in this work were obtained with the same ultrasound scanner (Philips iU22 Ultrasound System) but with different spatial resolutions. The proposed solution does not extract only the IMT but also the CCA diameter, which is not as relevant as the IMT to predict future atherosclerosis evolution but it is a statistically interesting piece of information for the doctors to determine the cardiovascular risk. The results of the proposed method have been validated by doctors, and these results are visually and numerically satisfactory when considering the medical measurements as ground truth, with a maximum deviation of only 3.4 pixels (0.0248 mm) for IMT. PMID:22552539

  16. Combining prior day contours to improve automated prostate segmentation

    SciTech Connect

    Godley, Andrew; Sheplan Olsen, Lawrence J.; Stephans, Kevin; Zhao Anzi

    2013-02-15

    Purpose: To improve the accuracy of automatically segmented prostate, rectum, and bladder contours required for online adaptive therapy. The contouring accuracy on the current image guidance [image guided radiation therapy (IGRT)] scan is improved by combining contours from earlier IGRT scans via the simultaneous truth and performance level estimation (STAPLE) algorithm. Methods: Six IGRT prostate patients treated with daily kilo-voltage (kV) cone-beam CT (CBCT) had their original plan CT and nine CBCTs contoured by the same physician. Three types of automated contours were produced for analysis. (1) Plan: By deformably registering the plan CT to each CBCT and then using the resulting deformation field to morph the plan contours to match the CBCT anatomy. (2) Previous: The contour set drawn by the physician on the previous day CBCT is similarly deformed to match the current CBCT anatomy. (3) STAPLE: The contours drawn by the physician, on each prior CBCT and the plan CT, are deformed to match the CBCT anatomy to produce multiple contour sets. These sets are combined using the STAPLE algorithm into one optimal set. Results: Compared to plan and previous, STAPLE improved the average Dice's coefficient (DC) with the original physician drawn CBCT contours to a DC as follows: Bladder: 0.81 {+-} 0.13, 0.91 {+-} 0.06, and 0.92 {+-} 0.06; Prostate: 0.75 {+-} 0.08, 0.82 {+-} 0.05, and 0.84 {+-} 0.05; and Rectum: 0.79 {+-} 0.06, 0.81 {+-} 0.06, and 0.85 {+-} 0.04, respectively. The STAPLE results are within intraobserver consistency, determined by the physician blindly recontouring a subset of CBCTs. Comparing plans recalculated using the physician and STAPLE contours showed an average disagreement less than 1% for prostate D98 and mean dose, and 5% and 3% for bladder and rectum mean dose, respectively. One scan takes an average of 19 s to contour. Using five scans plus STAPLE takes less than 110 s on a 288 core graphics processor unit. Conclusions: Combining the plan and

  17. Contour tracking and probabilistic segmentation of tissue phase mapping MRI

    NASA Astrophysics Data System (ADS)

    Chitiboi, Teodora; Hennemuth, Anja; Schnell, Susanne; Chowdhary, Varun; Honarmand, Amir; Markl, Michael; Linsen, Lars; Hahn, Horst

    2016-03-01

    Many cardiovascular diseases manifest as an abnormal motion pattern of the heart muscle (myocardium). Local cardiac motion can be non-invasively quantified with magnetic resonance imaging (MRI), using methods such as tissue phase mapping (TPM), which directly measures the local myocardial velocities over time with high temporal and spatial resolution. The challenges for routine clinical use of TPM for the diagnosis and monitoring of cardiac function lie in providing a fast and accurate myocardium segmentation and a robust quantitative analysis of the velocity field. Both of these tasks are difficult to automate on routine clinical data because of the reduced contrast in the presence of noise. In this work, we propose to address these challenges with a segmentation approach that combines smooth, iterative contour displacement and probabilistic segmentation using particle tracing, based on the underlying velocity field. The proposed solution enabled the efficient and reproducible segmentation of TPM datasets from 27 patients and 14 volunteers, showing good potential for routine use in clinical studies. Our method allows for a more reliable quantitative analysis of local myocardial velocities, by giving a higher weight to velocity vectors corresponding to pixels more likely to belong to the myocardium. The accuracy of the contour propagation was evaluated on nine subjects, showing an average error smaller than the spatial resolution of the image data. Statistical analysis concluded that the difference between the segmented contours and the ground truths was not significantly higher than the variability between the manual ground truth segmentations.

  18. Automatic segmentation of vertebral contours from CT images using fuzzy corners.

    PubMed

    Athertya, Jiyo S; Saravana Kumar, G

    2016-05-01

    Automatic segmentation of bone in computed tomography (CT) images is critical for the implementation of computer-assisted diagnosis which has increasing potential in the evaluation of various spine disorders. Of the many techniques available for delineating the region of interest (ROI), active contour methods (ACM) are well-established techniques that are used to segment medical images. The initialization for these methods is either through manual intervention or by applying a global threshold, thus making them semi-automatic in nature. The paper presents a methodology for automatic contour initialization in ACM and demonstrates the applicability of the method for medical image segmentation from spinal CT images. Initially, a set of feature markers from the image is extracted to construct an initial contour for the ACM. A fuzzified corner metric, based on image intensity, is proposed to identify the feature markers to be enclosed by the contour. A concave hull based on α shape, is constructed using these fuzzy corners to give the initial contour. The proposed method was evaluated against conventional feature detectors and other initialization methods. The results show the method׳s robust performance in the presence of simulated Gaussian noise levels. The method enables the ACM to efficiently converge to the ground truth segmentation. The reference standard for comparison was the annotated images from a radiologist, and the Dice coefficient and Hausdorff distance measures were used to evaluate the segmentation. PMID:27017068

  19. Application of centerline detection and deformable contours algorithms to segmenting the carotid lumen

    NASA Astrophysics Data System (ADS)

    Hachaj, Tomasz; Ogiela, Marek R.

    2014-03-01

    The main contribution of this article is to evaluate the utility of different state-of-the-art deformable contour models for segmenting carotid lumen walls from computed tomography angiography images. We have also proposed and tested a new tracking-based lumen segmentation method based on our evaluation results. The deformable contour algorithm (snake) is used to detect the outer wall of the vessel. We have examined four different snakes: with a balloon, distance, and a gradient vector flow force and the method of active contours without edges. The algorithms were evaluated on a set of 32 artery lumens-16 from the common carotid artery (CCA)-the internal carotid artery section and 16 from the CCA-the external carotid artery section-in order to find the optimum deformable contour model for this task. Later, we evaluated different values of energy terms in the method of active contours without edges, which turned out to be the best for our dataset, in order to find the optimal values for this particular segmentation task. The choice of particular weights in the energy term was evaluated statistically. The final Dice's coefficient at the level of 0.939±0.049 puts our algorithm among the best state-of-the-art methods for these solutions.

  20. Group average difference: a termination criterion for active contour.

    PubMed

    Chuah, Tong Kuan; Lim, Jun Hong; Poh, Chueh Loo

    2012-04-01

    This paper presents a termination criterion for active contour that does not involve alteration of the energy functional. The criterion is based on the area difference of the contour during evolution. In this criterion, the evolution of the contour terminates when the area difference fluctuates around a constant. The termination criterion is tested using parametric gradient vector flow active contour with contour resampling and normal force selection. The usefulness of the criterion is shown through its trend, speed, accuracy, shape insensitivity, and insensitivity to contour resampling. The metric used in the proposed criterion demonstrated a steadily decreasing trend. For automatic implementation in which different shapes need to be segmented, the proposed criterion demonstrated almost 50% and 60% total time reduction while achieving similar accuracy as compared with the pixel movement-based method in the segmentation of synthetic and real medical images, respectively. Our results also show that the proposed termination criterion is insensitive to shape variation and contour resampling. The criterion also possesses potential to be used for other kinds of snakes.

  1. SU-E-J-129: Atlas Development for Cardiac Automatic Contouring Using Multi-Atlas Segmentation

    SciTech Connect

    Zhou, R; Yang, J; Pan, T; Milgrom, S; Pinnix, C; Shi, A; Yang, J; Liu, Y; Nguyen, Q; Gomez, D; Dabaja, B; Balter, P; Court, L; Liao, Z

    2015-06-15

    Purpose: To develop a set of atlases for automatic contouring of cardiac structures to determine heart radiation dose and the associated toxicity. Methods: Six thoracic cancer patients with both contrast and non-contrast CT images were acquired for this study. Eight radiation oncologists manually and independently delineated cardiac contours on the non-contrast CT by referring to the fused contrast CT and following the RTOG 1106 atlas contouring guideline. Fifteen regions of interest (ROIs) were delineated, including heart, four chambers, four coronary arteries, pulmonary artery and vein, inferior and superior vena cava, and ascending and descending aorta. Individual expert contours were fused using the simultaneous truth and performance level estimation (STAPLE) algorithm for each ROI and each patient. The fused contours became atlases for an in-house multi-atlas segmentation. Using leave-one-out test, we generated auto-segmented contours for each ROI and each patient. The auto-segmented contours were compared with the fused contours using the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Results: Inter-observer variability was not obvious for heart, chambers, and aorta but was large for other structures that were not clearly distinguishable on CT image. The average DSC between individual expert contours and the fused contours were less than 50% for coronary arteries and pulmonary vein, and the average MSD were greater than 4.0 mm. The largest MSD of expert contours deviating from the fused contours was 2.5 cm. The mean DSC and MSD of auto-segmented contours were within one standard deviation of expert contouring variability except the right coronary artery. The coronary arteries, vena cava, and pulmonary vein had DSC<70% and MSD>3.0 mm. Conclusion: A set of cardiac atlases was created for cardiac automatic contouring, the accuracy of which was comparable to the variability in expert contouring. However, substantial modification may need

  2. Interactive segmentation of tongue contours in ultrasound video sequences using quality maps

    NASA Astrophysics Data System (ADS)

    Ghrenassia, Sarah; Ménard, Lucie; Laporte, Catherine

    2014-03-01

    Ultrasound (US) imaging is an effective and non invasive way of studying the tongue motions involved in normal and pathological speech, and the results of US studies are of interest for the development of new strategies in speech therapy. State-of-the-art tongue shape analysis techniques based on US images depend on semi-automated tongue segmentation and tracking techniques. Recent work has mostly focused on improving the accuracy of the tracking techniques themselves. However, occasional errors remain inevitable, regardless of the technique used, and the tongue tracking process must thus be supervised by a speech scientist who will correct these errors manually or semi-automatically. This paper proposes an interactive framework to facilitate this process. In this framework, the user is guided towards potentially problematic portions of the US image sequence by a segmentation quality map that is based on the normalized energy of an active contour model and automatically produced during tracking. When a problematic segmentation is identified, corrections to the segmented contour can be made on one image and propagated both forward and backward in the problematic subsequence, thereby improving the user experience. The interactive tools were tested in combination with two different tracking algorithms. Preliminary results illustrate the potential of the proposed framework, suggesting that the proposed framework generally improves user interaction time, with little change in segmentation repeatability.

  3. Binding and segmentation of multiple objects through neural oscillators inhibited by contour information.

    PubMed

    Ursino, Mauro; La Cara, Giuseppe-Emiliano; Sarti, Alessandro

    2003-07-01

    Temporal correlation of neuronal activity has been suggested as a criterion for multiple object recognition. In this work, a two-dimensional network of simplified Wilson-Cowan oscillators is used to manage the binding and segmentation problem of a visual scene according to the connectedness Gestalt criterion. Binding is achieved via original coupling terms that link excitatory units to both excitatory and inhibitory units of adjacent neurons. These local coupling terms are time independent, i.e., they do not require Hebbian learning during the simulations. Segmentation is realized by a two-layer processing of the visual image. The first layer extracts all object contours from the image by means of "retinal cells" with an "on-center" receptive field. Information on contour is used to selectively inhibit Wilson-Cowan oscillators in the second layer, thus realizing a strong separation among neurons in different objects. Accidental synchronism between oscillations in different objects is prevented with the use of a global inhibitor, i.e., a global neuron that computes the overall activity in the Wilson-Cowan network and sends back an inhibitory signal. Simulations performed in a 50 x 50 neural grid with 21 different visual scenes (containing up to eight objects + background) with random initial conditions demonstrate that the network can correctly segment objects in almost 100% of cases using a single set of parameters, i.e., without the need to adjust parameters from one visual scene to the next. The network is robust with reference to dynamical noise superimposed on oscillatory neurons. Moreover, the network can segment both black objects on white background and vice versa and is able to deal with the problem of "fragmentation."The main limitation of the network is its sensitivity to static noise superimposed on the objects. Overcoming this problem requires implementation of more robust mechanisms for contour enhancement in the first layer in agreement with

  4. Contour integration and segmentation with a new lateral connections model

    NASA Astrophysics Data System (ADS)

    Cai, Chao

    2011-11-01

    Automatically target contour detection from cluttered scenes is a very difficult task for computer vision. Humans, however, have a much better background suppress ability. The preceding models could not implement such a task very well. In this letter, an effective contour integration method based on human visual perception mechanism is proposed. The algorithm combines the properties of primary visual cortex and psychology researching results to simulate the contour perception of the V1 cortex. The new lateral connection based computational model have a better texture suppress ability, while, target's contour is enhanced. Compared with traditional methods, experiments show that the new method implement a more reasonable simulation of the V1 function structure, availably enhance the target's contour while suppress the cluttered background, obtain a balance between over and lose detection, besides, it has better accuracy with less computational complexity and time-consuming.

  5. Active contours for localizing polyps in colonoscopic NBI image data

    NASA Astrophysics Data System (ADS)

    Breier, Matthias; Gross, Sebastian; Behrens, Alexander; Stehle, Thomas; Aach, Til

    2011-03-01

    Colon cancer is the third most common type of cancer in the United States of America. Every year about 140,000 people are newly diagnosed with colon cancer. Early detection is crucial for a successful therapy. The standard screening procedure is called colonoscopy. Using this endoscopic examination physicians can find colon polyps and remove them if necessary. Adenomatous colon polyps are deemed a preliminary stage of colon cancer. The removal of a polyp, though, can lead to complications like severe bleedings or colon perforation. Thus, only polyps diagnosed as adenomatous should be removed. To decide whether a polyp is adenomatous the polyp's surface structure including vascular patterns has to be inspected. Narrow-Band imaging (NBI) is a new tool to improve visibility of vascular patterns of the polyps. The first step for an automatic polyp classification system is the localization of the polyp. We investigate active contours for the localization of colon polyps in NBI image data. The shape of polyps, though roughly approximated by an elliptic form, is highly variable. Active contours offer the flexibility to adapt to polyp variation well. To avoid clustering of contour polygon points we propose the application of active rays. The quality of the results was evaluated based on manually segmented polyps as ground truth data. The results were compared to a template matching approach and to the Generalized Hough Transform. Active contours are superior to the Hough transform and perform equally well as the template matching approach.

  6. CONTOUR

    SciTech Connect

    Pelessone, D. )

    1993-11-01

    CONTOUR is an in-house computer program which is used at General Atomics to generate contour plots of analysis results obtained from various finite element codes used in stress and thermal analysis of core fuel blocks. The program provides contour and fringe plots of the results in either black and white or color. The input data for CONTOUR is CONDRUM, a word addressable file generated by codes which contain element stresses and nodal displacements such as TWOD and PRINT2. TWOD is a finite element program for linear and nonlinear stress analysis of two-dimensional and axisymetric solids. PRINT2 is an output processor code for printing data.

  7. Multiple contour sequences' segmentation and entity recognition methods in vision measurement

    NASA Astrophysics Data System (ADS)

    Yang, Feng; Liu, Shoubin

    2012-01-01

    In this paper, an approach is proposed for segmentation of multiple contour sequences and recognition of entities for vision measurement of small precision parts. The approach includes several steps as follows. All contour sequences of the part are detected at the first place. Secondly, a circle identification method is used to find circular contours in contour sequences. The identified circular contours are further fitted as individual circles. Then, curvature method is selected to detect dominant points in the rest contours and height projection method is adopted to classify them as line or arc entities. In the end, the least-squares method is used to merge and add dominant points. Experimental results show lines, arcs and circles can be recognized satisfactorily by using the approach presented.

  8. Segmentation of urinary bladder in CT urography (CTU) using CLASS with enhanced contour conjoint procedure

    NASA Astrophysics Data System (ADS)

    Cha, Kenny; Hadjiiski, Lubomir; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.; Zhou, Chuan

    2014-03-01

    We are developing a computerized method for bladder segmentation in CT urography (CTU) for computeraided diagnosis of bladder cancer. A challenge for computerized bladder segmentation in CTU is that the bladder often contains regions filled with intravenous (IV) contrast and without contrast. Previously, we proposed a Conjoint Level set Analysis and Segmentation System (CLASS) consisting of four stages: preprocessing and initial segmentation, 3D and 2D level set segmentation, and post-processing. In case the bladder is partially filled with contrast, CLASS segments the non-contrast (NC) region and the contrast (C) filled region separately and conjoins the contours with a Contour Conjoint Procedure (CCP). The CCP is not trivial. Inaccuracies in the NC and C contours may cause CCP to exclude portions of the bladder. To alleviate this problem, we implemented model-guided refinement to propagate the C contour if the level set propagation in the region stops prematurely due to substantial non-uniformity of the contrast. An enhanced CCP with regularized energies further propagates the conjoint contours to the correct bladder boundary. Segmentation performance was evaluated using 70 cases. For all cases, 3D hand segmented contours were obtained as reference standard, and computerized segmentation accuracy was evaluated in terms of average volume intersection %, average % volume error, and average minimum distance. With enhanced CCP, those values were 84.4±10.6%, 8.3±16.1%, 3.4±1.8 mm, respectively. With CLASS, those values were 74.6±13.1%, 19.6±18.6%, 4.4±2.2 mm, respectively. The enhanced CCP improved bladder segmentation significantly (p<0.001) for all three performance measures.

  9. Active contour approach for accurate quantitative airway analysis

    NASA Astrophysics Data System (ADS)

    Odry, Benjamin L.; Kiraly, Atilla P.; Slabaugh, Greg G.; Novak, Carol L.; Naidich, David P.; Lerallut, Jean-Francois

    2008-03-01

    Chronic airway disease causes structural changes in the lungs including peribronchial thickening and airway dilatation. Multi-detector computed tomography (CT) yields detailed near-isotropic images of the lungs, and thus the potential to obtain quantitative measurements of lumen diameter and airway wall thickness. Such measurements would allow standardized assessment, and physicians to diagnose and locate airway abnormalities, adapt treatment, and monitor progress over time. However, due to the sheer number of airways per patient, systematic analysis is infeasible in routine clinical practice without automation. We have developed an automated and real-time method based on active contours to estimate both airway lumen and wall dimensions; the method does not require manual contour initialization but only a starting point on the targeted airway. While the lumen contour segmentation is purely region-based, the estimation of the outer diameter considers the inner wall segmentation as well as local intensity variation, in order anticipate the presence of nearby arteries and exclude them. These properties make the method more robust than the Full-Width Half Maximum (FWHM) approach. Results are demonstrated on a phantom dataset with known dimensions and on a human dataset where the automated measurements are compared against two human operators. The average error on the phantom measurements was 0.10mm and 0.14mm for inner and outer diameters, showing sub-voxel accuracy. Similarly, the mean variation from the average manual measurement was 0.14mm and 0.18mm for inner and outer diameters respectively.

  10. Validation of bone segmentation and improved 3-D registration using contour coherency in CT data.

    PubMed

    Wang, Liping Ingrid; Greenspan, Michael; Ellis, Randy

    2006-03-01

    A method is presented to validate the segmentation of computed tomography (CT) image sequences, and improve the accuracy and efficiency of the subsequent registration of the three-dimensional surfaces that are reconstructed from the segmented slices. The method compares the shapes of contours extracted from neighborhoods of slices in CT stacks of tibias. The bone is first segmented by an automatic segmentation technique, and the bone contour for each slice is parameterized as a one-dimensional function of normalized arc length versus inscribed angle. These functions are represented as vectors within a K-dimensional space comprising the first K amplitude coefficients of their Fourier Descriptors. The similarity or coherency of neighboring contours is measured by comparing statistical properties of their vector representations within this space. Experimentation has demonstrated this technique to be very effective at identifying low-coherency segmentations. Compared with experienced human operators, in a set of 23 CT stacks (1,633 slices), the method correctly detected 87.5% and 80% of the low-coherency and 97.7% and 95.5% of the high coherency segmentations, respectively from two different automatic segmentation techniques. Removal of the automatically detected low-coherency segmentations also significantly improved the accuracy and time efficiency of the registration of 3-D bone surface models. The registration error was reduced by over 500% (i.e., a factor of 5) and 280%, and the computational performance was improved by 540% and 791% for the two respective segmentation methods. PMID:16524088

  11. Human body contour data based activity recognition.

    PubMed

    Myagmarbayar, Nergui; Yuki, Yoshida; Imamoglu, Nevrez; Gonzalez, Jose; Otake, Mihoko; Yu, Wenwei

    2013-01-01

    This research work is aimed to develop autonomous bio-monitoring mobile robots, which are capable of tracking and measuring patients' motions, recognizing the patients' behavior based on observation data, and providing calling for medical personnel in emergency situations in home environment. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs). In our previous research, a full framework was established towards this research goal. In this research, we aimed at improving the human activity recognition by using contour data of the tracked human subject extracted from the depth images as the signal source, instead of the lower limb joint angle data used in the previous research, which are more likely to be affected by the motion of the robot and human subjects. Several geometric parameters, such as, the ratio of height to weight of the tracked human subject, and distance (pixels) between centroid points of upper and lower parts of human body, were calculated from the contour data, and used as the features for the activity recognition. A Hidden Markov Model (HMM) is employed to classify different human activities from the features. Experimental results showed that the human activity recognition could be achieved with a high correct rate. PMID:24111015

  12. Human body contour data based activity recognition.

    PubMed

    Myagmarbayar, Nergui; Yuki, Yoshida; Imamoglu, Nevrez; Gonzalez, Jose; Otake, Mihoko; Yu, Wenwei

    2013-01-01

    This research work is aimed to develop autonomous bio-monitoring mobile robots, which are capable of tracking and measuring patients' motions, recognizing the patients' behavior based on observation data, and providing calling for medical personnel in emergency situations in home environment. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs). In our previous research, a full framework was established towards this research goal. In this research, we aimed at improving the human activity recognition by using contour data of the tracked human subject extracted from the depth images as the signal source, instead of the lower limb joint angle data used in the previous research, which are more likely to be affected by the motion of the robot and human subjects. Several geometric parameters, such as, the ratio of height to weight of the tracked human subject, and distance (pixels) between centroid points of upper and lower parts of human body, were calculated from the contour data, and used as the features for the activity recognition. A Hidden Markov Model (HMM) is employed to classify different human activities from the features. Experimental results showed that the human activity recognition could be achieved with a high correct rate.

  13. A shape constrained parametric active contour model for breast contour detection.

    PubMed

    Lee, Juhun; Muralidhar, Gautam S; Reece, Gregory P; Markey, Mia K

    2012-01-01

    Quantitative measures of breast morphology can help a breast cancer survivor to understand outcomes of reconstructive surgeries. One bottleneck of quantifying breast morphology is that there are only a few reliable automation algorithms for detecting the breast contour. This study proposes a novel approach for detecting the breast contour, which is based on a parametric active contour model. In addition to employing the traditional parametric active contour model, the proposed approach enforces a mathematical shape constraint based on the catenary curve, which has been previously shown to capture the overall shape of the breast contour reliably. The mathematical shape constraint regulates the evolution of the active contour and helps the contour evolve towards the breast, while minimizing the undesired effects of other structures such as, the nipple/areola and scars. The efficacy of the proposed approach was evaluated on anterior posterior photographs of women who underwent or were scheduled for breast reconstruction surgery including autologous tissue reconstruction. The proposed algorithm shows promising results for detecting the breast contour.

  14. Accurate segmentation of partially overlapping cervical cells based on dynamic sparse contour searching and GVF snake model.

    PubMed

    Guan, Tao; Zhou, Dongxiang; Liu, Yunhui

    2015-07-01

    Overlapping cells segmentation is one of the challenging topics in medical image processing. In this paper, we propose to approximately represent the cell contour as a set of sparse contour points, which can be further partitioned into two parts: the strong contour points and the weak contour points. We consider the cell contour extraction as a contour points locating problem and propose an effective and robust framework for segmentation of partially overlapping cells in cervical smear images. First, the cell nucleus and the background are extracted by a morphological filtering-based K-means clustering algorithm. Second, a gradient decomposition-based edge enhancement method is developed for enhancing the true edges belonging to the center cell. Then, a dynamic sparse contour searching algorithm is proposed to gradually locate the weak contour points in the cell overlapping regions based on the strong contour points. This algorithm involves the least squares estimation and a dynamic searching principle, and is thus effective to cope with the cell overlapping problem. Using the located contour points, the Gradient Vector Flow Snake model is finally employed to extract the accurate cell contour. Experiments have been performed on two cervical smear image datasets containing both single cells and partially overlapping cells. The high accuracy of the cell contour extraction result validates the effectiveness of the proposed method.

  15. CT urography: segmentation of urinary bladder using CLASS with local contour refinement

    NASA Astrophysics Data System (ADS)

    Cha, Kenny; Hadjiiski, Lubomir; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Zhou, Chuan

    2014-06-01

    We are developing a computerized system for bladder segmentation on CT urography (CTU), as a critical component for computer-aided detection of bladder cancer. The presence of regions filled with intravenous contrast and without contrast presents a challenge for bladder segmentation. Previously, we proposed a conjoint level set analysis and segmentation system (CLASS). In case the bladder is partially filled with contrast, CLASS segments the non-contrast (NC) region and the contrast-filled (C) region separately and automatically conjoins the NC and C region contours; however, inaccuracies in the NC and C region contours may cause the conjoint contour to exclude portions of the bladder. To alleviate this problem, we implemented a local contour refinement (LCR) method that exploits model-guided refinement (MGR) and energy-driven wavefront propagation (EDWP). MGR propagates the C region contours if the level set propagation in the C region stops prematurely due to substantial non-uniformity of the contrast. EDWP with regularized energies further propagates the conjoint contours to the correct bladder boundary. EDWP uses changes in energies, smoothness criteria of the contour, and previous slice contour to determine when to stop the propagation, following decision rules derived from training. A data set of 173 cases was collected for this study: 81 cases in the training set (42 lesions, 21 wall thickenings, 18 normal bladders) and 92 cases in the test set (43 lesions, 36 wall thickenings, 13 normal bladders). For all cases, 3D hand segmented contours were obtained as reference standard and used for the evaluation of the computerized segmentation accuracy. For CLASS with LCR, the average volume intersection ratio, average volume error, absolute average volume error, average minimum distance and Jaccard index were 84.2 ± 11.4%, 8.2 ± 17.4%, 13.0 ± 14.1%, 3.5 ± 1.9 mm, 78.8 ± 11.6%, respectively, for the training set and 78.0 ± 14.7%, 16.4 ± 16.9%, 18.2 ± 15.0%, 3

  16. CT Urography: Segmentation of Urinary Bladder using CLASS with Local Contour Refinement

    PubMed Central

    Cha, Kenny; Hadjiiski, Lubomir; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Zhou, Chuan

    2016-01-01

    Purpose We are developing a computerized system for bladder segmentation on CT urography (CTU), as a critical component for computer-aided detection of bladder cancer. Methods The presence of regions filled with intravenous contrast and without contrast presents a challenge for bladder segmentation. Previously, we proposed a Conjoint Level set Analysis and Segmentation System (CLASS). In case the bladder is partially filled with contrast, CLASS segments the non-contrast (NC) region and the contrast-filled (C) region separately and automatically conjoins the NC and C region contours; however, inaccuracies in the NC and C region contours may cause the conjoint contour to exclude portions of the bladder. To alleviate this problem, we implemented a local contour refinement (LCR) method that exploits model-guided refinement (MGR) and energy-driven wavefront propagation (EDWP). MGR propagates the C region contours if the level set propagation in the C region stops prematurely due to substantial non-uniformity of the contrast. EDWP with regularized energies further propagates the conjoint contours to the correct bladder boundary. EDWP uses changes in energies, smoothness criteria of the contour, and previous slice contour to determine when to stop the propagation, following decision rules derived from training. A data set of 173 cases was collected for this study: 81 cases in the training set (42 lesions, 21 wall thickenings, 18 normal bladders) and 92 cases in the test set (43 lesions, 36 wall thickenings, 13 normal bladders). For all cases, 3D hand segmented contours were obtained as reference standard and used for the evaluation of the computerized segmentation accuracy. Results For CLASS with LCR, the average volume intersection ratio, average volume error, absolute average volume error, average minimum distance and Jaccard index were 84.2±11.4%, 8.2±17.4%, 13.0±14.1%, 3.5±1.9 mm, 78.8±11.6%, respectively, for the training set and 78.0±14.7%, 16.4±16.9%, 18.2

  17. Cavity contour segmentation in chest radiographs using supervised learning and dynamic programming

    SciTech Connect

    Maduskar, Pragnya Hogeweg, Laurens; Sánchez, Clara I.; Ginneken, Bram van; Jong, Pim A. de; Peters-Bax, Liesbeth; Dawson, Rodney; Ayles, Helen

    2014-07-15

    Purpose: Efficacy of tuberculosis (TB) treatment is often monitored using chest radiography. Monitoring size of cavities in pulmonary tuberculosis is important as the size predicts severity of the disease and its persistence under therapy predicts relapse. The authors present a method for automatic cavity segmentation in chest radiographs. Methods: A two stage method is proposed to segment the cavity borders, given a user defined seed point close to the center of the cavity. First, a supervised learning approach is employed to train a pixel classifier using texture and radial features to identify the border pixels of the cavity. A likelihood value of belonging to the cavity border is assigned to each pixel by the classifier. The authors experimented with four different classifiers:k-nearest neighbor (kNN), linear discriminant analysis (LDA), GentleBoost (GB), and random forest (RF). Next, the constructed likelihood map was used as an input cost image in the polar transformed image space for dynamic programming to trace the optimal maximum cost path. This constructed path corresponds to the segmented cavity contour in image space. Results: The method was evaluated on 100 chest radiographs (CXRs) containing 126 cavities. The reference segmentation was manually delineated by an experienced chest radiologist. An independent observer (a chest radiologist) also delineated all cavities to estimate interobserver variability. Jaccard overlap measure Ω was computed between the reference segmentation and the automatic segmentation; and between the reference segmentation and the independent observer's segmentation for all cavities. A median overlap Ω of 0.81 (0.76 ± 0.16), and 0.85 (0.82 ± 0.11) was achieved between the reference segmentation and the automatic segmentation, and between the segmentations by the two radiologists, respectively. The best reported mean contour distance and Hausdorff distance between the reference and the automatic segmentation were

  18. Identification of breast contour for nipple segmentation in breast magnetic resonance images

    SciTech Connect

    Gwo, Chih-Ying; Gwo, Allen; Wei, Chia-Hung; Huang, Pai Jung

    2014-02-15

    Purpose: The purpose of this study is to develop a method to simulate the breast contour and segment the nipple in breast magnetic resonance images. Methods: This study first identifies the chest wall and removes the chest part from the breast MR images. Subsequently, the cleavage and its motion artifacts are removed, distinguishing the separate breasts, where the edge points are sampled for curve fitting. Next, a region growing method is applied to find the potential nipple region. Finally, the potential nipple region above the simulated curve can be removed in order to retain the original smooth contour. Results: The simulation methods can achieve the least root mean square error (RMSE) for certain cases. The proposed YBnd and (Dmin+Dmax)/2 methods are significant due toP = 0.000. The breast contour curve detected by the two proposed methods is closer than that determined by the edge detection method. The (Dmin+Dmax)/2 method can achieve the lowest RMSE of 1.1029 on average, while the edge detection method results in the highest RMSE of 6.5655. This is only slighter better than the comparison methods, which implies that the performance of these methods depends upon the conditions of the cases themselves. Under this method, the maximal Dice coefficient is 0.881, and the centroid difference is 0.36 pixels. Conclusions: The contributions of this study are twofold. First, a method was proposed to identify and segment the nipple in breast MR images. Second, a curve-fitting method was used to simulate the breast contour, allowing the breast to retain its original smooth shape.

  19. From snakes to region-based active contours defined by region-dependent parameters.

    PubMed

    Jehan-Besson, Stéphanie; Gastaud, Muriel; Precioso, Frédéric; Barlaud, Michel; Aubert, Gilles; Debreuve, Eric

    2004-01-10

    Image and sequence segmentation of a the segmentation task are discussed from the point of view of optimizing the segmentation criterion. Such a segmentation criterion involves so-called (boundary and region) descriptors, which, in general, may depend on their respective boundaries or regions. This dependency must be taken into account when one is computing the criterion derivative with respect to the unknown object domain (defined by its boundary). If this dependency not considered, some correctional terms may be omitted. Computing the derivative of the segmentation criterion with a dynamic scheme is described. The scheme is general enough to provide a framework for a wide variety of applications in segmentation. It also provides a theoretical meaning to the philosophy of active contours.

  20. On the Relationship between Variational Level Set-Based and SOM-Based Active Contours.

    PubMed

    Abdelsamea, Mohammed M; Gnecco, Giorgio; Gaber, Mohamed Medhat; Elyan, Eyad

    2015-01-01

    Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods have been used to build an active contour with the aim of modeling arbitrarily complex shapes. Moreover, they can handle also topological changes of the contours. Self-Organizing Maps (SOMs) have attracted the attention of many computer vision scientists, particularly in modeling an active contour based on the idea of utilizing the prototypes (weights) of a SOM to control the evolution of the contour. SOM-based models have been proposed in general with the aim of exploiting the specific ability of SOMs to learn the edge-map information via their topology preservation property and overcoming some drawbacks of other ACMs, such as trapping into local minima of the image energy functional to be minimized in such models. In this survey, we illustrate the main concepts of variational level set-based ACMs, SOM-based ACMs, and their relationship and review in a comprehensive fashion the development of their state-of-the-art models from a machine learning perspective, with a focus on their strengths and weaknesses. PMID:25960736

  1. On the Relationship between Variational Level Set-Based and SOM-Based Active Contours

    PubMed Central

    Abdelsamea, Mohammed M.; Gnecco, Giorgio; Gaber, Mohamed Medhat; Elyan, Eyad

    2015-01-01

    Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods have been used to build an active contour with the aim of modeling arbitrarily complex shapes. Moreover, they can handle also topological changes of the contours. Self-Organizing Maps (SOMs) have attracted the attention of many computer vision scientists, particularly in modeling an active contour based on the idea of utilizing the prototypes (weights) of a SOM to control the evolution of the contour. SOM-based models have been proposed in general with the aim of exploiting the specific ability of SOMs to learn the edge-map information via their topology preservation property and overcoming some drawbacks of other ACMs, such as trapping into local minima of the image energy functional to be minimized in such models. In this survey, we illustrate the main concepts of variational level set-based ACMs, SOM-based ACMs, and their relationship and review in a comprehensive fashion the development of their state-of-the-art models from a machine learning perspective, with a focus on their strengths and weaknesses. PMID:25960736

  2. Automated optic disk boundary detection by modified active contour model.

    PubMed

    Xu, Juan; Chutatape, Opas; Chew, Paul

    2007-03-01

    This paper presents a novel deformable-model-based algorithm for fully automated detection of optic disk boundary in fundus images. The proposed method improves and extends the original snake (deforming-only technique) in two aspects: clustering and smoothing update. The contour points are first self-separated into edge-point group or uncertain-point group by clustering after each deformation, and these contour points are then updated by different criteria based on different groups. The updating process combines both the local and global information of the contour to achieve the balance of contour stability and accuracy. The modifications make the proposed algorithm more accurate and robust to blood vessel occlusions, noises, ill-defined edges and fuzzy contour shapes. The comparative results show that the proposed method can estimate the disk boundaries of 100 test images closer to the groundtruth, as measured by mean distance to closest point (MDCP) <3 pixels, with the better success rate when compared to those obtained by gradient vector flow snake (GVF-snake) and modified active shape models (ASM).

  3. SU-E-J-131: Augmenting Atlas-Based Segmentation by Incorporating Image Features Proximal to the Atlas Contours

    SciTech Connect

    Li, Dengwang; Liu, Li; Kapp, Daniel S.; Xing, Lei

    2015-06-15

    Purpose: For facilitating the current automatic segmentation, in this work we propose a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. Methods: In setting up an atlas-based library, we include not only the coordinates of contour points, but also the image features adjacent to the contour. 139 planning CT scans with normal appearing livers obtained during their radiotherapy treatment planning were used to construct the library. The CT images within the library were registered each other using affine registration. A nonlinear narrow shell with the regional thickness determined by the distance between two vertices alongside the contour. The narrow shell was automatically constructed both inside and outside of the liver contours. The common image features within narrow shell between a new case and a library case were first selected by a Speed-up Robust Features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the images of the new patient by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy function within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by a physician. Results: Application of the technique to 30 liver cases suggested that the technique was capable of reliably segment organs such as the liver with little human intervention. Compared with the manual segmentation results by a physician, the average and discrepancies of the volumetric overlap percentage (VOP) was found to be 92.43%+2.14%. Conclusion: Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically

  4. A Model for Diagnosing Breast Cancerous Tissue from Thermal Images Using Active Contour and Lyapunov Exponent

    PubMed Central

    GHAYOUMI ZADEH, Hossein; HADDADNIA, Javad; MONTAZERI, Alimohammad

    2016-01-01

    Background: The segmentation of cancerous areas in breast images is important for the early detection of disease. Thermal imaging has advantages, such as being non-invasive, non-radiation, passive, quick, painless, inexpensive, and non-contact. Imaging technique is the focus of this research. Methods: The proposed model in this paper is a combination of surf and corners that are very resistant. Obtained features are resistant to changes in rotation and revolution then with the help of active contours, this feature has been used for segmenting cancerous areas. Results: Comparing the obtained results from the proposed method and mammogram show that proposed method is Accurate and appropriate. Benign and malignance of segmented areas are detected by Lyapunov exponent. Values obtained include TP=91.31%, FN=8.69%, FP=7.26%. Conclusion: The proposed method can classify those abnormally segmented areas of the breast, to the Benign and malignant cancer. PMID:27398339

  5. Atlas-Based Segmentation Improves Consistency and Decreases Time Required for Contouring Postoperative Endometrial Cancer Nodal Volumes

    SciTech Connect

    Young, Amy V.; Wortham, Angela; Wernick, Iddo; Evans, Andrew; Ennis, Ronald D.

    2011-03-01

    Purpose: Accurate target delineation of the nodal volumes is essential for three-dimensional conformal and intensity-modulated radiotherapy planning for endometrial cancer adjuvant therapy. We hypothesized that atlas-based segmentation ('autocontouring') would lead to time savings and more consistent contours among physicians. Methods and Materials: A reference anatomy atlas was constructed using the data from 15 postoperative endometrial cancer patients by contouring the pelvic nodal clinical target volume on the simulation computed tomography scan according to the Radiation Therapy Oncology Group 0418 trial using commercially available software. On the simulation computed tomography scans from 10 additional endometrial cancer patients, the nodal clinical target volume autocontours were generated. Three radiation oncologists corrected the autocontours and delineated the manual nodal contours under timed conditions while unaware of the other contours. The time difference was determined, and the overlap of the contours was calculated using Dice's coefficient. Results: For all physicians, manual contouring of the pelvic nodal target volumes and editing the autocontours required a mean {+-} standard deviation of 32 {+-} 9 vs. 23 {+-} 7 minutes, respectively (p = .000001), a 26% time savings. For each physician, the time required to delineate the manual contours vs. correcting the autocontours was 30 {+-} 3 vs. 21 {+-} 5 min (p = .003), 39 {+-} 12 vs. 30 {+-} 5 min (p = .055), and 29 {+-} 5 vs. 20 {+-} 5 min (p = .0002). The mean overlap increased from manual contouring (0.77) to correcting the autocontours (0.79; p = .038). Conclusion: The results of our study have shown that autocontouring leads to increased consistency and time savings when contouring the nodal target volumes for adjuvant treatment of endometrial cancer, although the autocontours still required careful editing to ensure that the lymph nodes at risk of recurrence are properly included in the target

  6. A fast region-based active contour model for boundary detection of echocardiographic images.

    PubMed

    Saini, Kalpana; Dewal, M L; Rohit, Manojkumar

    2012-04-01

    This paper presents the boundary detection of atrium and ventricle in echocardiographic images. In case of mitral regurgitation, atrium and ventricle may get dilated. To examine this, doctors draw the boundary manually. Here the aim of this paper is to evolve the automatic boundary detection for carrying out segmentation of echocardiography images. Active contour method is selected for this purpose. There is an enhancement of Chan-Vese paper on active contours without edges. Our algorithm is based on Chan-Vese paper active contours without edges, but it is much faster than Chan-Vese model. Here we have developed a method by which it is possible to detect much faster the echocardiographic boundaries. The method is based on the region information of an image. The region-based force provides a global segmentation with variational flow robust to noise. Implementation is based on level set theory so it easy to deal with topological changes. In this paper, Newton-Raphson method is used which makes possible the fast boundary detection.

  7. Tracking Epithelial Cell Junctions in C. elegans Embryogenesis With Active Contours Guided by SIFT Flow

    PubMed Central

    Lee, Chen-Yu; Gonçalves, Monira; Chisholm, Andrew D.; Cosman, Pamela C.

    2015-01-01

    Quantitative analysis of cell shape in live samples is an important goal in developmental biology. Automated or semiautomated segmentation and tracking of cell nuclei has been successfully implemented in several biological systems. Segmentation and tracking of cell surfaces has been more challenging. Here, we present a new approach to tracking cell junctions in the developing epidermis of C. elegans embryos. Epithelial junctions as visualized with DLG-1::GFP form lines at the subapical circumference of differentiated epidermal cells and delineate changes in epidermal cell shape and position. We develop and compare two approaches for junction segmentation. For the first method (projection approach), 3-D cell boundaries are projected into 2D for segmentation using active contours with a nonintersecting force, and subsequently tracked using scale-invariant feature transform (SIFT) flow. The resulting 2-D tracked boundaries are then back-projected into 3-D space. The second method (volumetric approach) uses a 3-D extended version of active contours guided by SIFT flow in 3-D space. In both methods, cell junctions are manually located at the first time point and tracked in a fully automated way for the remainder of the video. Using these methods, we have generated the first quantitative description of ventral epidermal cell movements and shape changes during epidermal enclosure. PMID:24771564

  8. Automatic brain cropping enhancement using active contours initialized by a PCNN

    NASA Astrophysics Data System (ADS)

    Swathanthira Kumar, Murali Murugavel; Sullivan, John M., Jr.

    2009-02-01

    Active contours are a popular medical image segmentation strategy. However in practice, its accuracy is dependent on the initialization of the process. The PCNN (Pulse Coupled Neural Network) algorithm developed by Eckhorn to model the observed synchronization of neural assemblies in small mammals such as cats allows for segmenting regions of similar intensity but it lacks a convergence criterion. In this paper we report a novel PCNN based strategy to initialize the zero level contour for automatic brain cropping of T2 weighted MRI image volumes of Long-Evans rats. Individual 2D anatomy slices of the rat brain volume were processed by means of a PCNN and a surrogate image 'signature' was constructed for each slice. By employing a previously trained artificial neural network (ANN) an approximate PCNN iteration (binary mask) was selected. This mask was then used to initialize a region based active contour model to crop the brain region. We tested this hybrid algorithm on 30 rat brain (256*256*12) volumes and compared the results against manually cropped gold standard. The Dice and Jaccard similarity indices were used for numerical evaluation of the proposed hybrid model. The highly successful system yielded an average of 0.97 and 0.94 respectively.

  9. An active contour model algorithm for tracking endocardiac boundaries in echocardiographic sequences.

    PubMed

    Sánchez, P J; Zapata, J; Ruiz, R

    2000-01-01

    The use of active contour models to track the boundaries of anatomic structures in medical images is a technique that has attracted a great number of efforts during the last decade. Segmentation techniques based in deformable active contours were proposed first by Kass et al. Because of the problems appearing using these models, some solutions have been introduced, such as balloon force or Gradient Vector Flow force (GVF), derived from the Gradient Vector Flow vectorial field. Results obtained with these forces in the tracking endocardiac task in echocardiographic sequences were not adequate. We have designed a new external force called hybrid force, which, by combining both forces, joins the main features of each one.

  10. An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures.

    PubMed

    Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Tian, Yun; Duan, Fuqing; Pan, Yutong

    2016-01-01

    Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels. PMID:27597878

  11. An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures

    PubMed Central

    Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Duan, Fuqing; Pan, Yutong

    2016-01-01

    Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels.

  12. Flux Tensor Constrained Geodesic Active Contours with Sensor Fusion for Persistent Object Tracking

    PubMed Central

    Bunyak, Filiz; Palaniappan, Kannappan; Nath, Sumit Kumar; Seetharaman, Gunasekaran

    2007-01-01

    This paper makes new contributions in motion detection, object segmentation and trajectory estimation to create a successful object tracking system. A new efficient motion detection algorithm referred to as the flux tensor is used to detect moving objects in infrared video without requiring background modeling or contour extraction. The flux tensor-based motion detector when applied to infrared video is more accurate than thresholding ”hot-spots”, and is insensitive to shadows as well as illumination changes in the visible channel. In real world monitoring tasks fusing scene information from multiple sensors and sources is a useful core mechanism to deal with complex scenes, lighting conditions and environmental variables. The object segmentation algorithm uses level set-based geodesic active contour evolution that incorporates the fusion of visible color and infrared edge informations in a novel manner. Touching or overlapping objects are further refined during the segmentation process using an appropriate shape-based model. Multiple object tracking using correspondence graphs is extended to handle groups of objects and occlusion events by Kalman filter-based cluster trajectory analysis and watershed segmentation. The proposed object tracking algorithm was successfully tested on several difficult outdoor multispectral videos from stationary sensors and is not confounded by shadows or illumination variations. PMID:19096530

  13. An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures

    PubMed Central

    Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Duan, Fuqing; Pan, Yutong

    2016-01-01

    Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels. PMID:27597878

  14. A circumscribing active contour model for delineation of nuclei and membranes of megakaryocytes in bone marrow trephine biopsy images

    NASA Astrophysics Data System (ADS)

    Song, Tzu-Hsi; Sanchez, Victor; EIDaly, Hesham; Rajpoot, Nasir M.

    2015-03-01

    The assessment of megakaryocytes (MKs) in bone marrow trephine images is an important step in the classification of different subtypes of myeloproliferative neoplasms (MPNs). In general, bone marrow trephine images include several types of cells mixed together, which make it quite difficult to visually identify MKs. In order to aid hematopathologists in the identification and study of MKs, we develop an image processing framework with supervised machine learning approaches and a novel circumscribing active contour model to identify potential MKs and then to accurately delineate the corresponding nucleus and membrane. Specifically, a number of color and texture features are used in a nave Bayesian classifier and an Adaboost classifier to locate the regions with a high probability of depicting MKs. A region-based active contour is used on the candidate MKs to accurately delineate the boundaries of nucleus and membrane. The proposed circumscribing active contour model employs external forces not only based on pixel intensities, but also on the probabilities of depicting MKs as computed by the classifiers. Experimental results suggest that the machine learning approach can detect potential MKs with an accuracy of more than 75%. When our circumscribing active contour model is employed on the candidate MKs, the nucleus and membrane boundaries are segmented with an accuracy of more than 80% as measured by the Dice similarity coefficient. Compared to traditional region-based active contours, the use of additional external forces based on the probability of depicting MKs improves segmentation performance and computational time by an average 5%.

  15. Gallbladder shape extraction from ultrasound images using active contour models.

    PubMed

    Ciecholewski, Marcin; Chochołowicz, Jakub

    2013-12-01

    Gallbladder function is routinely assessed using ultrasonographic (USG) examinations. In clinical practice, doctors very often analyse the gallbladder shape when diagnosing selected disorders, e.g. if there are turns or folds of the gallbladder, so extracting its shape from USG images using supporting software can simplify a diagnosis that is often difficult to make. The paper describes two active contour models: the edge-based model and the region-based model making use of a morphological approach, both designed for extracting the gallbladder shape from USG images. The active contour models were applied to USG images without lesions and to those showing specific disease units, namely, anatomical changes like folds and turns of the gallbladder as well as polyps and gallstones. This paper also presents modifications of the edge-based model, such as the method for removing self-crossings and loops or the method of dampening the inflation force which moves nodes if they approach the edge being determined. The user is also able to add a fragment of the approximated edge beyond which neither active contour model will move if this edge is incomplete in the USG image. The modifications of the edge-based model presented here allow more precise results to be obtained when extracting the shape of the gallbladder from USG images than if the morphological model is used.

  16. Semi-automated identification of white blood cell using active contour technique

    NASA Astrophysics Data System (ADS)

    Marzuki, Nurhanis Izzati Binti Che; Mahmood, Nasrul Humaimi Bin; Razak, Mohd Azhar Bin Abdul

    2015-05-01

    Manual and automated diagnosis can be used to identify the morphology of blood cells. However, the manual diagnosis of the blood cells is time consuming and need hematologist and pathologist experts in order to diagnose diseases. Recently, the automated diagnosis which is require image processing technique are often been used in this area. This paper focuses on image processing technique to do segmentation on the nucleus of white blood cells (WBC). To identify the nucleus region, there are several image processing techniques applied besides the active contour method. The results obtained show that the detection on the edge of the nucleus is almost same as the original image of the nucleus.

  17. Iterative weighted average diffusion as a novel external force in the active contour model

    NASA Astrophysics Data System (ADS)

    Mirov, Ilya S.; Nakhmani, Arie

    2016-03-01

    The active contour model has good performance in boundary extraction for medical images; particularly, Gradient Vector Flow (GVF) active contour model shows good performance at concavity convergence and insensitivity to initialization, yet it is susceptible to edge leaking, deep and narrow concavities, and has some issues handling noisy images. This paper proposes a novel external force, called Iterative Weighted Average Diffusion (IWAD), which used in tandem with parametric active contours, provides superior performance in images with high values of concavity. The image gradient is first turned into an edge image, smoothed, and modified with enhanced corner detection, then the IWAD algorithm diffuses the force at a given pixel based on its 3x3 pixel neighborhood. A forgetting factor, φ, is employed to ensure that forces being spread away from the boundary of the image will attenuate. The experimental results show better behavior in high curvature regions, faster convergence, and less edge leaking than GVF when both are compared to expert manual segmentation of the images.

  18. Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

    NASA Astrophysics Data System (ADS)

    Nabizadeh, Nooshin; John, Nigel

    2014-03-01

    Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

  19. Active contour-based visual tracking by integrating colors, shapes, and motions.

    PubMed

    Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen

    2013-05-01

    In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame.

  20. Active contour-based visual tracking by integrating colors, shapes, and motions.

    PubMed

    Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen

    2013-05-01

    In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame. PMID:23288333

  1. A Method for Lung Boundary Correction Using Split Bregman Method and Geometric Active Contour Model

    PubMed Central

    Zhang, Jianxun; Liang, Rui

    2015-01-01

    In order to get the extracted lung region from CT images more accurately, a model that contains lung region extraction and edge boundary correction is proposed. Firstly, a new edge detection function is presented with the help of the classic structure tensor theory. Secondly, the initial lung mask is automatically extracted by an improved active contour model which combines the global intensity information, local intensity information, the new edge information, and an adaptive weight. It is worth noting that the objective function of the improved model is converted to a convex model, which makes the proposed model get the global minimum. Then, the central airway was excluded according to the spatial context messages and the position relationship between every segmented region and the rib. Thirdly, a mesh and the fractal theory are used to detect the boundary that surrounds the juxtapleural nodule. Finally, the geometric active contour model is employed to correct the detected boundary and reinclude juxtapleural nodules. We also evaluated the performance of the proposed segmentation and correction model by comparing with their popular counterparts. Efficient computing capability and robustness property prove that our model can correct the lung boundary reliably and reproducibly. PMID:26089976

  2. A Method for Lung Boundary Correction Using Split Bregman Method and Geometric Active Contour Model.

    PubMed

    Feng, Changli; Zhang, Jianxun; Liang, Rui

    2015-01-01

    In order to get the extracted lung region from CT images more accurately, a model that contains lung region extraction and edge boundary correction is proposed. Firstly, a new edge detection function is presented with the help of the classic structure tensor theory. Secondly, the initial lung mask is automatically extracted by an improved active contour model which combines the global intensity information, local intensity information, the new edge information, and an adaptive weight. It is worth noting that the objective function of the improved model is converted to a convex model, which makes the proposed model get the global minimum. Then, the central airway was excluded according to the spatial context messages and the position relationship between every segmented region and the rib. Thirdly, a mesh and the fractal theory are used to detect the boundary that surrounds the juxtapleural nodule. Finally, the geometric active contour model is employed to correct the detected boundary and reinclude juxtapleural nodules. We also evaluated the performance of the proposed segmentation and correction model by comparing with their popular counterparts. Efficient computing capability and robustness property prove that our model can correct the lung boundary reliably and reproducibly. PMID:26089976

  3. Prostate volume contouring: A 3D analysis of segmentation using 3DTRUS, CT, and MR

    SciTech Connect

    Smith, Wendy L. . E-mail: wendy.smith@cancerboard.ab.ca; Lewis, Craig |; Bauman, Glenn ||; Rodrigues, George ||; D'Souza, David |; Ash, Robert |; Ho, Derek; Venkatesan, Varagur |; Downey, Donal; Fenster, Aaron

    2007-03-15

    Purpose: This study evaluated the reproducibility and modality differences of prostate contouring after brachytherapy implant using three-dimensional (3D) transrectal ultrasound (3DTRUS), T2-weighted magnetic resonance (MR), and computed tomography (CT) imaging. Methods and Materials: Seven blinded observers contoured 10 patients' prostates, 30 day postimplant, on 3DTRUS, MR, and CT images to assess interobserver variability. Randomized images were contoured twice by each observer. We analyzed length and volume measurements and performed a 3D analysis of intra- and intermodality variation. Results: Average volume ratios were 1.16 for CT/MR, 0.90 for 3DTRUS/MR, and 1.30 for CT/3DTRUS. Overall contouring variability was largest for CT and similar for MR and 3DTRUS. The greatest variability of CT contours occurred at the posterior and anterior portions of the midgland. On MR, overall variability was smaller, with a maximum in the anterior region. On 3DTRUS, high variability occurred in anterior regions of the apex and base, whereas the prostate-rectum interface had the smallest variability. The shape of the prostate on MR was rounder, with the base and apex of similar size, whereas CT contours had broad, flat bases narrowing toward the apex. The average percent of surface area that was significantly different (95% confidence interval) for CT/MR was 4.1%; 3DTRUS/MR, 10.7%; and CT/3DTRUS, 6.3%. The larger variability of CT measurements made significant differences more difficult to detect. Conclusions: The contouring of prostates on CT, MR, and 3DTRUS results in systematic differences in the locations of and variability in prostate boundary definition between modalities. MR and 3DTRUS display the smallest variability and the closest correspondence.

  4. Fast Virtual Stenting with Active Contour Models in Intracranical Aneurysm.

    PubMed

    Zhong, Jingru; Long, Yunling; Yan, Huagang; Meng, Qianqian; Zhao, Jing; Zhang, Ying; Yang, Xinjian; Li, Haiyun

    2016-02-15

    Intracranial stents are becoming increasingly a useful option in the treatment of intracranial aneurysms (IAs). Image simulation of the releasing stent configuration together with computational fluid dynamics (CFD) simulation prior to intervention will help surgeons optimize intervention scheme. This paper proposed a fast virtual stenting of IAs based on active contour model (ACM) which was able to virtually release stents within any patient-specific shaped vessel and aneurysm models built on real medical image data. In this method, an initial stent mesh was generated along the centerline of the parent artery without the need for registration between the stent contour and the vessel. Additionally, the diameter of the initial stent volumetric mesh was set to the maximum inscribed sphere diameter of the parent artery to improve the stenting accuracy and save computational cost. At last, a novel criterion for terminating virtual stent expanding that was based on the collision detection of the axis aligned bounding boxes was applied, making the stent expansion free of edge effect. The experiment results of the virtual stenting and the corresponding CFD simulations exhibited the efficacy and accuracy of the ACM based method, which are valuable to intervention scheme selection and therapy plan confirmation.

  5. Fast Virtual Stenting with Active Contour Models in Intracranical Aneurysm

    PubMed Central

    Zhong, Jingru; Long, Yunling; Yan, Huagang; Meng, Qianqian; Zhao, Jing; Zhang, Ying; Yang, Xinjian; Li, Haiyun

    2016-01-01

    Intracranial stents are becoming increasingly a useful option in the treatment of intracranial aneurysms (IAs). Image simulation of the releasing stent configuration together with computational fluid dynamics (CFD) simulation prior to intervention will help surgeons optimize intervention scheme. This paper proposed a fast virtual stenting of IAs based on active contour model (ACM) which was able to virtually release stents within any patient-specific shaped vessel and aneurysm models built on real medical image data. In this method, an initial stent mesh was generated along the centerline of the parent artery without the need for registration between the stent contour and the vessel. Additionally, the diameter of the initial stent volumetric mesh was set to the maximum inscribed sphere diameter of the parent artery to improve the stenting accuracy and save computational cost. At last, a novel criterion for terminating virtual stent expanding that was based on the collision detection of the axis aligned bounding boxes was applied, making the stent expansion free of edge effect. The experiment results of the virtual stenting and the corresponding CFD simulations exhibited the efficacy and accuracy of the ACM based method, which are valuable to intervention scheme selection and therapy plan confirmation. PMID:26876026

  6. A self-calibrating approach for the segmentation of retinal vessels by template matching and contour reconstruction.

    PubMed

    Kovács, György; Hajdu, András

    2016-04-01

    The automated processing of retinal images is a widely researched area in medical image analysis. Screening systems based on the automated and accurate recognition of retinopathies enable the earlier diagnosis of diseases like diabetic retinopathy, hypertension and their complications. The segmentation of the vascular system is a crucial task in the field: on the one hand, the accurate extraction of the vessel pixels aids the detection of other anatomical parts (like the optic disc Hoover and Goldbaum, 2003) and lesions (like microaneurysms Sopharak et al., 2013); on the other hand, the geometrical features of the vascular system and their temporal changes are shown to be related to diseases, like the vessel tortuosity to Fabry disease Sodi et al., 2013 and the arteriolar-to-venus (A/V) ratio to hypertension (Pakter et al., 2005). In this study, a novel technique based on template matching and contour reconstruction is proposed for the segmentation of the vasculature. In the template matching step generalized Gabor function based templates are used to extract the center lines of vessels. Then, the intensity characteristics of vessel contours measured in training databases are reconstructed. The method was trained and tested on two publicly available databases, DRIVE and STARE; and reached an average accuracy of 0.9494 and 0.9610, respectively. We have also carried out cross-database tests and found that the accuracy scores are higher than that of any previous technique trained and tested on the same database.

  7. Structural stereo matching of Laplacian-of-Gaussian contour segments for 3D perception

    NASA Technical Reports Server (NTRS)

    Boyer, K. L.; Sotak, G. E., Jr.

    1989-01-01

    The stereo correspondence problem is solved using Laplacian-of-Gaussian zero-crossing contours as a source of primitives for structural stereopsis, as opposed to traditional point-based algorithms. Up to 74 percent matching of candidate zero crossing points are being achieved on 240 x 246 images at small scales and large ranges of disparity, without coarse-to-fine tracking and without precise knowledge of the epipolar geometry. This approach should prove particularly useful in recovering the epipolar geometry automatically for stereo pairs for which it is unavailable a priori. Such situations occur in the extraction of terrain models from stereo aerial photographs.

  8. 3D Actin Network Centerline Extraction with Multiple Active Contours

    PubMed Central

    Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

    2013-01-01

    Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and actin cables. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we propose a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D Total Internal Reflection Fluorescence Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy. Quantitative evaluation of the method using synthetic images shows that for images with SNR above 5.0, the average vertex error measured by the distance between our result and ground truth is 1 voxel, and the average Hausdorff distance is below 10 voxels. PMID:24316442

  9. Rapid Activation of Motor Responses by Illusory Contours

    ERIC Educational Resources Information Center

    Seydell-Greenwald, Anna; Schmidt, Thomas

    2012-01-01

    Whereas physiological studies indicate that illusory contours (ICs) are signaled in early visual areas at short latencies, behavioral studies are divided as to whether IC processing can proceed in a fast, automatic, bottom-up manner or whether it requires extensive top-down intracortical feedback or even awareness and cognition. Here, we employ a…

  10. EXTRACTION AND ANALYSIS OF ACTIN NETWORKS BASED ON OPEN ACTIVE CONTOUR MODELS.

    PubMed

    Xu, Ting; Li, Hongsheng; Shen, Tian; Ojkic, Nikola; Vavylonis, Dimitrios; Huang, Xiaolei

    2011-03-30

    Network structures formed by actin filaments are present in many kinds of fluorescence microscopy images. In order to quantify the conformations and dynamics of such actin filaments, we propose a fully automated method to extract actin networks from images and analyze network topology. The method handles well intersecting filaments and, to some extent, overlapping filaments. First we automatically initialize a large number of Stretching Open Active Contours (SOACs) from ridge points detected by searching for plus-to-minus sign changes in the gradient map of the image. These initial SOACs then elongate simultaneously along the bright center-lines of filaments by minimizing an energy function. During their evolution, they may merge or stop growing, thus forming a network that represents the topology of the filament ensemble. We further detect junction points in the network and break the SOACs at junctions to obtain "SOAC segments". These segments are then re-grouped using a graph-cut spectral clustering method to represent the configuration of actin filaments. The proposed approach is generally applicable to extracting intersecting curvilinear structures in noisy images. We demonstrate its potential using two kinds of data: (1) actin filaments imaged by Total Internal Reflection Fluorescence Microscopy (TIRFM) in vitro; (2) actin cytoskeleton networks in fission yeast imaged by spinning disk confocal microscopy. PMID:21822463

  11. Automated detection of the carotid artery wall in longitudinal B-mode images using active contours initialized by the Hough transform.

    PubMed

    Matsakou, A I; Golemati, S; Stoitsis, J S; Nikita, K S

    2011-01-01

    In this paper, a fully automatic active-contour-based segmentation method is presented, for detecting the carotid artery wall in longitudinal B-mode ultrasound images. A Hough-transform-based methodology is used for the definition of the initial snake, followed by a gradient vector flow (GVF) snake deformation for the final contour detection. The GVF snake is based on the calculation of the image edge map and the calculation of GVF field which guides its deformation for the estimation of the real arterial wall boundaries. In twenty cases there was no significant difference between the automated segmentation and the manual diameter measurements. The sensitivity, specificity and accuracy were 0.97, 0.99 and 0.98, respectively, for both diastolic and systolic cases. In conclusion, the proposed methodology provides an accurate and reliable way to segment ultrasound images of the carotid artery.

  12. Phase retrieval in digital speckle pattern interferometry by application of two-dimensional active contours called snakes.

    PubMed

    Federico, Alejandro; Kaufmann, Guillermo H

    2006-03-20

    We propose a novel approach to retrieving the phase map coded by a single closed-fringe pattern in digital speckle pattern interferometry, which is based on the estimation of the local sign of the quadrature component. We obtain the estimate by calculating the local orientation of the fringes that have previously been denoised by a weighted smoothing spline method. We carry out the procedure of sign estimation by determining the local abrupt jumps of size pi in the orientation field of the fringes and by segmenting the regions defined by these jumps. The segmentation method is based on the application of two-dimensional active contours (snakes), with which one can also estimate absent jumps, i.e., those that cannot be detected from the local orientation of the fringes. The performance of the proposed phase-retrieval technique is evaluated for synthetic and experimental fringes and compared with the results obtained with the spiral-phase- and Fourier-transform methods.

  13. EXTRACTION AND ANALYSIS OF ACTIN NETWORKS BASED ON OPEN ACTIVE CONTOUR MODELS

    PubMed Central

    Xu, Ting; Li, Hongsheng; Shen, Tian; Ojkic, Nikola; Vavylonis, Dimitrios; Huang, Xiaolei

    2011-01-01

    Network structures formed by actin filaments are present in many kinds of fluorescence microscopy images. In order to quantify the conformations and dynamics of such actin filaments, we propose a fully automated method to extract actin networks from images and analyze network topology. The method handles well intersecting filaments and, to some extent, overlapping filaments. First we automatically initialize a large number of Stretching Open Active Contours (SOACs) from ridge points detected by searching for plus-to-minus sign changes in the gradient map of the image. These initial SOACs then elongate simultaneously along the bright center-lines of filaments by minimizing an energy function. During their evolution, they may merge or stop growing, thus forming a network that represents the topology of the filament ensemble. We further detect junction points in the network and break the SOACs at junctions to obtain “SOAC segments”. These segments are then re-grouped using a graph-cut spectral clustering method to represent the configuration of actin filaments. The proposed approach is generally applicable to extracting intersecting curvilinear structures in noisy images. We demonstrate its potential using two kinds of data: (1) actin filaments imaged by Total Internal Reflection Fluorescence Microscopy (TIRFM) in vitro; (2) actin cytoskeleton networks in fission yeast imaged by spinning disk confocal microscopy. PMID:21822463

  14. Region-based geometric active contour for classification using hyperspectral remote sensing images

    NASA Astrophysics Data System (ADS)

    Yan, Lin

    2011-12-01

    The high spectral resolution of hyperspectral imaging (HSI) systems greatly enhances the capabilities of discrimination, identification and quantification of objects of different materials from remote sensing images, but they also bring challenges to the processing and analysis of HSI data. One issue is the high computation cost and the curse of dimensionality associated with the high dimensions of HSI data. A second issue is how to effectively utilize the information including spectral and spatial information embedded in HSI data. Geometric Active Contour (GAC) is a widely used image segmentation method that utilizes the geometric information of objects within images. One category of GAC models, the region-based GAC models (RGAC), have good potential for remote sensing image processing because they use both spectral and geometry information in images are robust to initial contour placement. These models have been introduced to target extractions and classifications on remote sensing images. However, there are some restrictions on the applications of the RGAC models on remote sensing. First, the heavy involvement of iterative contour evolutions makes GAC applications time-consuming and inconvenient to use. Second, the current RGAC models must be based on a certain distance metric and the performance of RGAC classifiers are restricted by the performance of the employed distance metrics. According to the key features of the RGAC models analyzed in this dissertation, a classification framework is developed for remote sensing image classifications using the RGAC models. This framework allows the RGAC models to be combined with conventional pixel-based classifiers to promote them to spectral-spatial classifiers and also greatly reduces the iterations of contour evolutions. An extended Chan-Vese (ECV) model is proposed that is able to incorporate the widely used distance metrics in remote sensing image processing. A new type of RGAC model, the edge-oriented RGAC model

  15. A Cell Derived Active Contour (CDAC) Method for Robust Tracking in Low Frame Rate, Low Contrast Phase Microscopy - an Example: The Human hNT Astrocyte

    PubMed Central

    Nejati Javaremi, Alireza; Unsworth, Charles P.; Graham, E. Scott

    2013-01-01

    The problem of automated segmenting and tracking of the outlines of cells in microscope images is the subject of active research. While great progress has been made on recognizing cells that are of high contrast and of predictable shape, many situations arise in practice where these properties do not exist and thus many interesting potential studies - such as the migration patterns of astrocytes to scratch wounds - have been relegated to being largely qualitative in nature. Here we analyse a select number of recent developments in this area, and offer an algorithm based on parametric active contours and formulated by taking into account cell movement dynamics. This Cell-Derived Active Contour (CDAC) method is compared with two state-of-the-art segmentation methods for phase-contrast microscopy. Specifically, we tackle a very difficult segmentation problem: human astrocytes that are very large, thin, and irregularly-shaped. We demonstrate quantitatively better results for CDAC as compared to similar segmentation methods, and we also demonstrate the reliable segmentation of qualitatively different data sets that were not possible using existing methods. We believe this new method will enable new and improved automatic cell migration and movement studies to be made. PMID:24358233

  16. Method for non-referential defect characterization using fractal encoding and active contours

    DOEpatents

    Gleason, Shaun S.; Sari-Sarraf, Hamed

    2007-05-15

    A method for identification of anomalous structures, such as defects, includes the steps of providing a digital image and applying fractal encoding to identify a location of at least one anomalous portion of the image. The method does not require a reference image to identify the location of the anomalous portion. The method can further include the step of initializing an active contour based on the location information obtained from the fractal encoding step and deforming an active contour to enhance the boundary delineation of the anomalous portion.

  17. Reconstruction of surfaces from planar contours through contour interpolation

    NASA Astrophysics Data System (ADS)

    Sunderland, Kyle; Woo, Boyeong; Pinter, Csaba; Fichtinger, Gabor

    2015-03-01

    Segmented structures such as targets or organs at risk are typically stored as 2D contours contained on evenly spaced cross sectional images (slices). Contour interpolation algorithms are implemented in radiation oncology treatment planning software to turn 2D contours into a 3D surface, however the results differ between algorithms, causing discrepancies in analysis. Our goal was to create an accurate and consistent contour interpolation algorithm that can handle issues such as keyhole contours, rapid changes, and branching. This was primarily motivated by radiation therapy research using the open source SlicerRT extension for the 3D Slicer platform. The implemented algorithm triangulates the mesh by minimizing the length of edges spanning the contours with dynamic programming. The first step in the algorithm is removing keyholes from contours. Correspondence is then found between contour layers and branching patterns are determined. The final step is triangulating the contours and sealing the external contours. The algorithm was tested on contours segmented on computed tomography (CT) images. Some cases such as inner contours, rapid changes in contour size, and branching were handled well by the algorithm when encountered individually. There were some special cases in which the simultaneous occurrence of several of these problems in the same location could cause the algorithm to produce suboptimal mesh. An open source contour interpolation algorithm was implemented in SlicerRT for reconstructing surfaces from planar contours. The implemented algorithm was able to generate qualitatively good 3D mesh from the set of 2D contours for most tested structures.

  18. Robust x-ray image segmentation by spectral clustering and active shape model.

    PubMed

    Wu, Jing; Mahfouz, Mohamed R

    2016-07-01

    Extraction of bone contours from x-ray radiographs plays an important role in joint space width assessment, preoperative planning, and kinematics analysis. We present a robust segmentation method to accurately extract the distal femur and proximal tibia in knee radiographs of varying image quality. A spectral clustering method based on the eigensolution of an affinity matrix is utilized for x-ray image denoising. An active shape model-based segmentation method is employed for robust and accurate segmentation of the denoised x-ray images. The performance of the proposed method is evaluated with x-ray images from the public-use dataset(s), the osteoarthritis initiative, achieving a root mean square error of [Formula: see text] for femur and [Formula: see text] for tibia. The results demonstrate that this method outperforms previous segmentation methods in capturing anatomical shape variations, accounting for image quality differences and guiding accurate segmentation. PMID:27660806

  19. An approach for contour detection of human kidneys from ultrasound images using Markov random fields and active contours.

    PubMed

    Martín-Fernández, Marcos; Alberola-López, Carlos

    2005-02-01

    In this paper, a novel method for the boundary detection of human kidneys from three dimensional (3D) ultrasound (US) is proposed. The inherent difficulty of interpretation of such images, even by a trained expert, makes the problem unsuitable for classical methods. The method here proposed finds the kidney contours in each slice. It is a probabilistic Bayesian method. The prior defines a Markov field of deformations and imposes the restriction of contour smoothness. The likelihood function imposes a probabilistic behavior to the data, conditioned to the contour position. This second function, which is also Markov, uses an empirical model of distribution of the echographical data and a function of the gradient of the data. The model finally includes, as a volumetric extension of the prior, a term that forces smoothness along the depth coordinate. The experiments that have been carried out on echographies from real patients validate the model here proposed. A sensitivity analysis of the model parameters has also been carried out.

  20. Inter-element orientation and distance influence the duration of persistent contour integration.

    PubMed

    Strother, Lars; Alferov, Danila

    2014-01-01

    Contour integration is a fundamental form of perceptual organization. We introduce a new method of studying the mechanisms responsible for contour integration. This method capitalizes on the perceptual persistence of contours under conditions of impending camouflage. Observers viewed arrays of randomly arranged line segments upon which circular contours comprised of similar line segments were superimposed via abrupt onset. Crucially, these contours remained visible for up to a few seconds following onset, but eventually disappeared due to the camouflaging effects of surrounding background line segments. Our main finding was that the duration of contour visibility depended on the distance and degree of co-alignment between adjacent contour segments such that relatively dense smooth contours persisted longest. The stimulus-related effects reported here parallel similar results from contour detection studies, and complement previous reported top-down influences on contour persistence (Strother et al., 2011). We propose that persistent contour visibility reflects the sustained activity of recurrent processing loops within and between visual cortical areas involved in contour integration and other important stages of visual object recognition.

  1. Prostate segmentation with local binary patterns guided active appearance models

    NASA Astrophysics Data System (ADS)

    Ghose, Soumya; Oliver, Arnau; Martí, Robert; Lladó, Xavier; Freixenet, Jordi; Vilanova, Joan C.; Meriaudeau, Fabrice

    2011-03-01

    Real-time fusion of Magnetic Resonance (MR) and Trans Rectal Ultra Sound (TRUS) images aid in the localization of malignant tissues in TRUS guided prostate biopsy. Registration performed on segmented contours of the prostate reduces computational complexity and improves the multimodal registration accuracy. However, accurate and computationally efficient segmentation of the prostate in TRUS images could be challenging in the presence of heterogeneous intensity distribution inside the prostate gland, and other imaging artifacts like speckle noise, shadow regions and low Signal to Noise Ratio (SNR). In this work, we propose to enhance the texture features of the prostate region using Local Binary Patterns (LBP) for the propagation of a shape and appearance based statistical model to segment the prostate in a multi-resolution framework. A parametric model of the propagating contour is derived from Principal Component Analysis (PCA) of the prior shape and texture information of the prostate from the training data. The estimated parameters are then modified with the prior knowledge of the optimization space to achieve an optimal segmentation. The proposed method achieves a mean Dice Similarity Coefficient (DSC) value of 0.94+/-0.01 and a mean segmentation time of 0.68+/-0.02 seconds when validated with 70 TRUS images of 7 datasets in a leave-one-patient-out validation framework. Our method performs computationally efficient and accurate prostate segmentation in the presence of intensity heterogeneities and imaging artifacts.

  2. Feed-forward active contour analysis for improved brachial artery reactivity testing.

    PubMed

    Pugliese, Daniel N; Sehgal, Chandra M; Sultan, Laith R; Reamer, Courtney B; Mohler, Emile R

    2016-08-01

    The object of this study was to utilize a novel feed-forward active contour (FFAC) algorithm to find a reproducible technique for analysis of brachial artery reactivity. Flow-mediated dilation (FMD) is an important marker of vascular endothelial function but has not been adopted for widespread clinical use given its technical limitations, including inter-observer variability and differences in technique across clinical sites. We developed a novel FFAC algorithm with the goal of validating a more reliable standard. Forty-six healthy volunteers underwent FMD measurement according to the standard technique. Ultrasound videos lasting 5-10 seconds each were obtained pre-cuff inflation and at minutes 1 through 5 post-cuff deflation in longitudinal and transverse views. Automated segmentation using the FFAC algorithm with initial boundary definition from three different observers was used to analyze the images to measure diameter/cross-sectional area over the cardiac cycle. The %FMD was calculated for average, minimum, and maximum diameters/areas. Using the FFAC algorithm, the population-specific coefficient of variation (CV) at end-diastole was 3.24% for transverse compared to 9.96% for longitudinal measurements; the subject-specific CV was 15.03% compared to 57.41%, respectively. For longitudinal measurements made via the conventional method, the population-specific CV was 4.77% and subject-specific CV was 117.79%. The intraclass correlation coefficient (ICC) for transverse measurements was 0.97 (95% CI: 0.95-0.98) compared to 0.90 (95% CI: 0.84-0.94) for longitudinal measurements with FFAC and 0.72 (95% CI: 0.51-0.84) for conventional measurements. In conclusion, transverse views using the novel FFAC method provide less inter-observer variability than traditional longitudinal views. Improved reproducibility may allow adoption of FMD testing in a clinical setting. The FFAC algorithm is a robust technique that should be evaluated further for its ability to replace the

  3. Feed-forward active contour analysis for improved brachial artery reactivity testing.

    PubMed

    Pugliese, Daniel N; Sehgal, Chandra M; Sultan, Laith R; Reamer, Courtney B; Mohler, Emile R

    2016-08-01

    The object of this study was to utilize a novel feed-forward active contour (FFAC) algorithm to find a reproducible technique for analysis of brachial artery reactivity. Flow-mediated dilation (FMD) is an important marker of vascular endothelial function but has not been adopted for widespread clinical use given its technical limitations, including inter-observer variability and differences in technique across clinical sites. We developed a novel FFAC algorithm with the goal of validating a more reliable standard. Forty-six healthy volunteers underwent FMD measurement according to the standard technique. Ultrasound videos lasting 5-10 seconds each were obtained pre-cuff inflation and at minutes 1 through 5 post-cuff deflation in longitudinal and transverse views. Automated segmentation using the FFAC algorithm with initial boundary definition from three different observers was used to analyze the images to measure diameter/cross-sectional area over the cardiac cycle. The %FMD was calculated for average, minimum, and maximum diameters/areas. Using the FFAC algorithm, the population-specific coefficient of variation (CV) at end-diastole was 3.24% for transverse compared to 9.96% for longitudinal measurements; the subject-specific CV was 15.03% compared to 57.41%, respectively. For longitudinal measurements made via the conventional method, the population-specific CV was 4.77% and subject-specific CV was 117.79%. The intraclass correlation coefficient (ICC) for transverse measurements was 0.97 (95% CI: 0.95-0.98) compared to 0.90 (95% CI: 0.84-0.94) for longitudinal measurements with FFAC and 0.72 (95% CI: 0.51-0.84) for conventional measurements. In conclusion, transverse views using the novel FFAC method provide less inter-observer variability than traditional longitudinal views. Improved reproducibility may allow adoption of FMD testing in a clinical setting. The FFAC algorithm is a robust technique that should be evaluated further for its ability to replace the

  4. Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

    PubMed Central

    Srivastava, Anuj

    2010-01-01

    We present a framework for incorporating prior information about high-probability shapes in the process of contour extraction and object recognition in images. Here one studies shapes as elements of an infinite-dimensional, non-linear quotient space, and statistics of shapes are defined and computed intrinsically using differential geometry of this shape space. Prior models on shapes are constructed using probability distributions on tangent bundles of shape spaces. Similar to the past work on active contours, where curves are driven by vector fields based on image gradients and roughness penalties, we incorporate the prior shape knowledge in the form of vector fields on curves. Through experimental results, we demonstrate the use of prior shape models in the estimation of object boundaries, and their success in handling partial obscuration and missing data. Furthermore, we describe the use of this framework in shape-based object recognition or classification. PMID:21076692

  5. Space Adaptation of Active Mirror Segment Concepts

    NASA Technical Reports Server (NTRS)

    Ames, Gregory H.

    1999-01-01

    This report summarizes the results of a three year effort by Blue Line Engineering Co. to advance the state of segmented mirror systems in several separate but related areas. The initial set of tasks were designed to address the issues of system level architecture, digital processing system, cluster level support structures, and advanced mirror fabrication concepts. Later in the project new tasks were added to provide support to the existing segmented mirror testbed at Marshall Space Flight Center (MSFC) in the form of upgrades to the 36 subaperture wavefront sensor. Still later, tasks were added to build and install a new system processor based on the results of the new system architecture. The project was successful in achieving a number of important results. These include the following most notable accomplishments: 1) The creation of a new modular digital processing system that is extremely capable and may be applied to a wide range of segmented mirror systems as well as many classes of Multiple Input Multiple Output (MIMO) control systems such as active structures or industrial automation. 2) A new graphical user interface was created for operation of segmented mirror systems. 3) The development of a high bit rate serial data loop that permits bi-directional flow of data to and from as many as 39 segments daisy-chained to form a single cluster of segments. 4) Upgrade of the 36 subaperture Hartmann type Wave Front Sensor (WFS) of the Phased Array Mirror, Extendible Large Aperture (PAMELA) testbed at MSFC resulting in a 40 to 5OX improvement in SNR which in turn enabled NASA personnel to achieve many significant strides in improved closed-loop system operation in 1998. 5) A new system level processor was built and delivered to MSFC for use with the PAMELA testbed. This new system featured a new graphical user interface to replace the obsolete and non-supported menu system originally delivered with the PAMELA system. The hardware featured Blue Line's new stackable

  6. Infrared active polarimetric imaging system controlled by image segmentation algorithms: application to decamouflage

    NASA Astrophysics Data System (ADS)

    Vannier, Nicolas; Goudail, François; Plassart, Corentin; Boffety, Matthieu; Feneyrou, Patrick; Leviandier, Luc; Galland, Frédéric; Bertaux, Nicolas

    2016-05-01

    We describe an active polarimetric imager with laser illumination at 1.5 µm that can generate any illumination and analysis polarization state on the Poincar sphere. Thanks to its full polarization agility and to image analysis of the scene with an ultrafast active-contour based segmentation algorithm, it can perform adaptive polarimetric contrast optimization. We demonstrate the capacity of this imager to detect manufactured objects in different types of environments for such applications as decamouflage and hazardous object detection. We compare two imaging modes having different number of polarimetric degrees of freedom and underline the characteristics that a polarimetric imager aimed at this type of applications should possess.

  7. Actin filament tracking based on particle filters and stretching open active contour models.

    PubMed

    Li, Hongsheng; Shen, Tian; Vavylonis, Dimitrios; Huang, Xiaolei

    2009-01-01

    We introduce a novel algorithm for actin filament tracking and elongation measurement. Particle Filters (PF) and Stretching Open Active Contours (SOAC) work cooperatively to simplify the modeling of PF in a one-dimensional state space while naturally integrating filament body constraints to tip estimation. Our algorithm reduces the PF state spaces to one-dimensional spaces by tracking filament bodies using SOAC and probabilistically estimating tip locations along the curve length of SOACs. Experimental evaluation on TIRFM image sequences with very low SNRs demonstrates the accuracy and robustness of this approach. PMID:20426170

  8. Dissociable neural correlates of contour completion and contour representation in illusory contour perception.

    PubMed

    Wu, Xiang; He, Sheng; Bushara, Khalaf; Zeng, Feiyan; Liu, Ying; Zhang, Daren

    2012-10-01

    Object recognition occurs even when environmental information is incomplete. Illusory contours (ICs), in which a contour is perceived though the contour edges are incomplete, have been extensively studied as an example of such a visual completion phenomenon. Despite the neural activity in response to ICs in visual cortical areas from low (V1 and V2) to high (LOC: the lateral occipital cortex) levels, the details of the neural processing underlying IC perception are largely not clarified. For example, how do the visual areas function in IC perception and how do they interact to archive the coherent contour perception? IC perception involves the process of completing the local discrete contour edges (contour completion) and the process of representing the global completed contour information (contour representation). Here, functional magnetic resonance imaging was used to dissociate contour completion and contour representation by varying each in opposite directions. The results show that the neural activity was stronger to stimuli with more contour completion than to stimuli with more contour representation in V1 and V2, which was the reverse of that in the LOC. When inspecting the neural activity change across the visual pathway, the activation remained high for the stimuli with more contour completion and increased for the stimuli with more contour representation. These results suggest distinct neural correlates of contour completion and contour representation, and the possible collaboration between the two processes during IC perception, indicating a neural connection between the discrete retinal input and the coherent visual percept.

  9. A Complete System for Automatic Extraction of Left Ventricular Myocardium From CT Images Using Shape Segmentation and Contour Evolution

    PubMed Central

    Zhu, Liangjia; Gao, Yi; Appia, Vikram; Yezzi, Anthony; Arepalli, Chesnal; Faber, Tracy; Stillman, Arthur; Tannenbaum, Allen

    2014-01-01

    The left ventricular myocardium plays a key role in the entire circulation system and an automatic delineation of the myocardium is a prerequisite for most of the subsequent functional analysis. In this paper, we present a complete system for an automatic segmentation of the left ventricular myocardium from cardiac computed tomography (CT) images using the shape information from images to be segmented. The system follows a coarse-to-fine strategy by first localizing the left ventricle and then deforming the myocardial surfaces of the left ventricle to refine the segmentation. In particular, the blood pool of a CT image is extracted and represented as a triangulated surface. Then, the left ventricle is localized as a salient component on this surface using geometric and anatomical characteristics. After that, the myocardial surfaces are initialized from the localization result and evolved by applying forces from the image intensities with a constraint based on the initial myocardial surface locations. The proposed framework has been validated on 34-human and 12-pig CT images, and the robustness and accuracy are demonstrated. PMID:24723531

  10. Creative Contours.

    ERIC Educational Resources Information Center

    Fashing, Edward; Appenbrink, David

    1978-01-01

    Students often have difficulty relating contour lines to the shape of a landform. This article describes the construction of a simple landform model designed to help students better understand contour lines. (MA)

  11. Perceiving Object Shape from Specular Highlight Deformation, Boundary Contour Deformation, and Active Haptic Manipulation

    PubMed Central

    Cheeseman, Jacob R.; Thomason, Kelsey E.; Ronning, Cecilia; Behari, Kriti; Kleinman, Kayla; Calloway, Autum B.; Lamirande, Davora

    2016-01-01

    It is well known that motion facilitates the visual perception of solid object shape, particularly when surface texture or other identifiable features (e.g., corners) are present. Conventional models of structure-from-motion require the presence of texture or identifiable object features in order to recover 3-D structure. Is the facilitation in 3-D shape perception similar in magnitude when surface texture is absent? On any given trial in the current experiments, participants were presented with a single randomly-selected solid object (bell pepper or randomly-shaped “glaven”) for 12 seconds and were required to indicate which of 12 (for bell peppers) or 8 (for glavens) simultaneously visible objects possessed the same shape. The initial single object’s shape was defined either by boundary contours alone (i.e., presented as a silhouette), specular highlights alone, specular highlights combined with boundary contours, or texture. In addition, there was a haptic condition: in this condition, the participants haptically explored with both hands (but could not see) the initial single object for 12 seconds; they then performed the same shape-matching task used in the visual conditions. For both the visual and haptic conditions, motion (rotation in depth or active object manipulation) was present in half of the trials and was not present for the remaining trials. The effect of motion was quantitatively similar for all of the visual and haptic conditions–e.g., the participants’ performance in Experiment 1 was 93.5 percent higher in the motion or active haptic manipulation conditions (when compared to the static conditions). The current results demonstrate that deforming specular highlights or boundary contours facilitate 3-D shape perception as much as the motion of objects that possess texture. The current results also indicate that the improvement with motion that occurs for haptics is similar in magnitude to that which occurs for vision. PMID:26863531

  12. Perceiving Object Shape from Specular Highlight Deformation, Boundary Contour Deformation, and Active Haptic Manipulation.

    PubMed

    Norman, J Farley; Phillips, Flip; Cheeseman, Jacob R; Thomason, Kelsey E; Ronning, Cecilia; Behari, Kriti; Kleinman, Kayla; Calloway, Autum B; Lamirande, Davora

    2016-01-01

    It is well known that motion facilitates the visual perception of solid object shape, particularly when surface texture or other identifiable features (e.g., corners) are present. Conventional models of structure-from-motion require the presence of texture or identifiable object features in order to recover 3-D structure. Is the facilitation in 3-D shape perception similar in magnitude when surface texture is absent? On any given trial in the current experiments, participants were presented with a single randomly-selected solid object (bell pepper or randomly-shaped "glaven") for 12 seconds and were required to indicate which of 12 (for bell peppers) or 8 (for glavens) simultaneously visible objects possessed the same shape. The initial single object's shape was defined either by boundary contours alone (i.e., presented as a silhouette), specular highlights alone, specular highlights combined with boundary contours, or texture. In addition, there was a haptic condition: in this condition, the participants haptically explored with both hands (but could not see) the initial single object for 12 seconds; they then performed the same shape-matching task used in the visual conditions. For both the visual and haptic conditions, motion (rotation in depth or active object manipulation) was present in half of the trials and was not present for the remaining trials. The effect of motion was quantitatively similar for all of the visual and haptic conditions-e.g., the participants' performance in Experiment 1 was 93.5 percent higher in the motion or active haptic manipulation conditions (when compared to the static conditions). The current results demonstrate that deforming specular highlights or boundary contours facilitate 3-D shape perception as much as the motion of objects that possess texture. The current results also indicate that the improvement with motion that occurs for haptics is similar in magnitude to that which occurs for vision. PMID:26863531

  13. Restoration of transpression/transtension by generating the three-dimensional segmented helical loci of deformed lines across structure contour maps

    NASA Astrophysics Data System (ADS)

    McCoss, Angus M.

    In transpression/transtension zones the strain is three-dimensional and rotational. This causes material to move through the plane of cross-section, often invalidating balancing and restoration within this plane. Methods are presented which allow the three-dimensional segmented, irregular, helical locus of an originally straight line to be constructed, in any direction, on a structure contour map of a folded and faulted surface. This construction depends on a knowledge of the kinematics of folding and faulting and can be modified to suit local conditions. The ratio of the length of the cylindrical envelope bounding this helical locus, to the sum of the lengths of the helical fragments between faults, gives the true stretch in the direction of the envelope. When the traces of the segmented helices are constructed in different directions on a deformed surface, the sectional finite-strain ellipse can be found for that surface. Knowledge of the dimensions of this ellipse and its orientation with respect to the kinematic axes of the transpression zone allows the tensor components to be constrained. This permits the three-dimensional boundary conditions to be determined and thus restored. The methods are applied to the Ardross Fault zone in central Scotland. The solutions suggest this fault zone underwent a phase of dextral transpression along a NW zone boundary during Hercynian E-W compression in the Scottish Midland Valley. Contemporaneous E-W dyke swarms and N-S regional flexures support these kinematics.

  14. Texture Guided Active Appearance Model Propagation for Prostate Segmentation

    NASA Astrophysics Data System (ADS)

    Ghose, Soumya; Oliver, Arnau; Martí, Robert; Lladó, Xavier; Freixenet, Jordi; Vilanova, Joan C.; Meriaudeau, Fabrice

    Fusion of Magnetic Resonance Imaging (MRI) and Trans Rectal Ultra Sound (TRUS) images during TRUS guided prostate biopsy improves localization of the malignant tissues. Segmented prostate in TRUS and MRI improve registration accuracy and reduce computational cost of the procedure. However, accurate segmentation of the prostate in TRUS images can be a challenging task due to low signal to noise ratio, heterogeneous intensity distribution inside the prostate, and imaging artifacts like speckle noise and shadow. We propose to use texture features from approximation coefficients of Haar wavelet transform for propagation of a shape and appearance based statistical model to segment the prostate in a multi-resolution framework. A parametric model of the propagating contour is derived from Principal Component Analysis of prior shape and texture informations of the prostate from the training data. The parameters are then modified with prior knowledge of the optimization space to achieve optimal prostate segmentation. The proposed method achieves a mean Dice Similarity Coefficient value of 0.95±0.01, and mean segmentation time of 0.72±0.05 seconds when validated on 25 TRUS images, grabbed from video sequences, in a leave-one-out validation framework. Our proposed model performs computationally efficient accurate prostate segmentation in presence of intensity heterogeneity and imaging artifacts.

  15. Actin Filament Tracking Based on Particle Filters and Stretching Open Active Contour Models

    PubMed Central

    Li, Hongsheng; Shen, Tian; Vavylonis, Dimitrios; Huang, Xiaolei

    2010-01-01

    We introduce a novel algorithm for actin filament tracking and elongation measurement. Particle Filters (PF) and Stretching Open Active Contours (SOAC) work cooperatively to simplify the modeling of PF in a one-dimensional state space while naturally integrating filament body constraints to tip estimation. Existing microtubule (MT) tracking methods track either MT tips or entire bodies in high-dimensional state spaces. In contrast, our algorithm reduces the PF state spaces to one-dimensional spaces by tracking filament bodies using SOAC and probabilistically estimating tip locations along the curve length of SOACs. Experimental evaluation on TIRFM image sequences with very low SNRs demonstrates the accuracy and robustness of the proposed approach. PMID:20426170

  16. Airborne asbestos fibers detection in microscope images using re-initialization free active contours.

    PubMed

    Theodosiou, Zenonas; Tsapatsoulis, Nicolas; Bujak-Pietrek, Stella; Szadkowska-Stanczyk, Irena

    2010-01-01

    Breathing in asbestos fibers can lead to a number of diseases, the fibers become trapped in the lung and cannot be removed by either coughing or the person's immune system. Atmospheric concentrations of carcinogenic asbestos fibers, have traditionally been measured visually using phase contrast microscopy. However, because this measurement method requires great skill, and has poor reproducibility and objectivity, the development of automatic counting methods has been long anticipated. In this paper we proposed an automated fibers detection method based on a variational formulation of geometric active contours that forces the level set function to be close to signed distance function and therefore completely eliminates the need of the costly re-initialization procedure. The method was evaluated using a ground truth of 29 manually annotated images. The results were encouraging for the further development of the proposed method.

  17. Contour complexity and contour detection.

    PubMed

    Wilder, John; Feldman, Jacob; Singh, Manish

    2015-01-01

    Itis well-known that "smooth" chains of oriented elements-contours-are more easily detected amid background noise than more undulating (i.e., "less smooth") chains. Here, we develop a Bayesian framework for contour detection and show that it predicts that contour detection performance should decrease with the contour's complexity, quantified as the description length (DL; i.e., the negative logarithm of probability integrated along the contour). We tested this prediction in two experiments in which subjects were asked to detect simple open contours amid pixel noise. In Experiment 1, we demonstrate a consistent decline in performance with increasingly complex contours, as predicted by the Bayesian model. In Experiment 2, we confirmed that this effect is due to integrated complexity along the contour, and does not seem to depend on local stretches of linear structure. The results corroborate the probabilistic model of contours, and show how contour detection can be understood as a special case of a more general process-the identification of organized patterns in the environment.

  18. Robust contour tracking in ultrasound tongue image sequences.

    PubMed

    Xu, Kele; Yang, Yin; Stone, Maureen; Jaumard-Hakoun, Aurore; Leboullenger, Clémence; Dreyfus, Gérard; Roussel, Pierre; Denby, Bruce

    2016-01-01

    A new contour-tracking algorithm is presented for ultrasound tongue image sequences, which can follow the motion of tongue contours over long durations with good robustness. To cope with missing segments caused by noise, or by the tongue midsagittal surface being parallel to the direction of ultrasound wave propagation, active contours with a contour-similarity constraint are introduced, which can be used to provide 'prior' shape information. Also, in order to address accumulation of tracking errors over long sequences, we present an automatic re-initialization technique, based on the complex wavelet image similarity index. Experiments on synthetic data and on real 60 frame per second (fps) data from different subjects demonstrate that the proposed method gives good contour tracking for ultrasound image sequences even over durations of minutes, which can be useful in applications such as speech recognition where very long sequences must be analyzed in their entirety.

  19. Contour complexity and contour detection

    PubMed Central

    Wilder, John; Feldman, Jacob; Singh, Manish

    2015-01-01

    It is well-known that “smooth” chains of oriented elements—contours—are more easily detected amid background noise than more undulating (i.e., “less smooth”) chains. Here, we develop a Bayesian framework for contour detection and show that it predicts that contour detection performance should decrease with the contour's complexity, quantified as the description length (DL; i.e., the negative logarithm of probability integrated along the contour). We tested this prediction in two experiments in which subjects were asked to detect simple open contours amid pixel noise. In Experiment 1, we demonstrate a consistent decline in performance with increasingly complex contours, as predicted by the Bayesian model. In Experiment 2, we confirmed that this effect is due to integrated complexity along the contour, and does not seem to depend on local stretches of linear structure. The results corroborate the probabilistic model of contours, and show how contour detection can be understood as a special case of a more general process—the identification of organized patterns in the environment. PMID:26024453

  20. SU-E-J-134: Optimizing Technical Parameters for Using Atlas Based Automatic Segmentation for Evaluation of Contour Accuracy Experience with Cardiac Structures From NRG Oncology/RTOG 0617

    SciTech Connect

    Yu, J; Gong, Y; Bar-Ad, V; Giaddui, T; Galvin, J; Xiao, Y; Hu, C; Gore, E; Wheatley, M; Witt, J; Robinson, C; Bradley, J; Kong, F

    2015-06-15

    Purpose: Accurate contour delineation is crucial for radiotherapy. Atlas based automatic segmentation tools can be used to increase the efficiency of contour accuracy evaluation. This study aims to optimize technical parameters utilized in the tool by exploring the impact of library size and atlas number on the accuracy of cardiac contour evaluation. Methods: Patient CT DICOMs from RTOG 0617 were used for this study. Five experienced physicians delineated the cardiac structures including pericardium, atria and ventricles following an atlas guideline. The consistency of cardiac structured delineation using the atlas guideline was verified by a study with four observers and seventeen patients. The CT and cardiac structure DICOM files were then used for the ABAS technique.To study the impact of library size (LS) and atlas number (AN) on automatic contour accuracy, automatic contours were generated with varied technique parameters for five randomly selected patients. Three LS (20, 60, and 100) were studied using commercially available software. The AN was four, recommended by the manufacturer. Using the manual contour as the gold standard, Dice Similarity Coefficient (DSC) was calculated between the manual and automatic contours. Five-patient averaged DSCs were calculated for comparison for each cardiac structure.In order to study the impact of AN, the LS was set 100, and AN was tested from one to five. The five-patient averaged DSCs were also calculated for each cardiac structure. Results: DSC values are highest when LS is 100 and AN is four. The DSC is 0.90±0.02 for pericardium, 0.75±0.06 for atria, and 0.86±0.02 for ventricles. Conclusion: By comparing DSC values, the combination AN=4 and LS=100 gives the best performance. This project was supported by NCI grants U24CA12014, U24CA180803, U10CA180868, U10CA180822, PA CURE grant and Bristol-Myers Squibb and Eli Lilly.

  1. Interactive MRI Segmentation with Controlled Active Vision

    PubMed Central

    Karasev, Peter; Kolesov, Ivan; Chudy, Karol; Muller, Grant; Xerogeanes, John; Tannenbaum, Allen

    2013-01-01

    Partitioning Magnetic-Resonance-Imaging (MRI) data into salient anatomic structures is a problem in medical imaging that has continued to elude fully automated solutions. Implicit functions are a common way to model the boundaries between structures and are amenable to control-theoretic methods. In this paper, the goal of enabling a human to obtain accurate segmentations in a short amount of time and with little effort is transformed into a control synthesis problem. Perturbing the state and dynamics of an implicit function’s driving partial differential equation via the accumulated user inputs and an observer-like system leads to desirable closed-loop behavior. Using a Lyapunov control design, a balance is established between the influence of a data-driven gradient flow and the human’s input over time. Automatic segmentation is thus smoothly coupled with interactivity. An application of the mathematical methods to orthopedic segmentation is shown, demonstrating the expected transient and steady state behavior of the implicit segmentation function and auxiliary observer. PMID:24584213

  2. Algorithm for quantifying advanced carotid artery atherosclerosis in humans using MRI and active contours

    NASA Astrophysics Data System (ADS)

    Adams, Gareth; Vick, G. W., III; Bordelon, Cassius; Insull, William; Morrisett, Joel

    2002-05-01

    A new algorithm for measuring carotid artery volumes and estimating atherosclerotic plaque volumes from MRI images has been developed and validated using pressure-perfusion-fixed cadaveric carotid arteries. Our method uses an active contour algorithm with the generalized gradient vector field force as the external force to localize the boundaries of the artery on each MRI cross-section. Plaque volume is estimated by an automated algorithm based on estimating the normal wall thickness for each branch of the carotid. Triplicate volume measurements were performed by a single observer on thirty-eight pairs of cadaveric carotid arteries. The coefficient of variance (COV) was used to quantify measurement reproducibility. Aggregate volumes were computed for nine contiguous slices bounding the carotid bifurcation. The median (mean +/- SD) COV for the 76 aggregate arterial volumes was 0.93% (1.47% +/- 1.52%) for the lumen volume, 0.95% (1.06% +/- 0.67%) for the total artery volume, and 4.69% (5.39% +/- 3.97%) for the plaque volume. These results indicate that our algorithm provides repeatable measures of arterial volumes and a repeatable estimate of plaque volume of cadaveric carotid specimens through analysis of MRI images. The algorithm also significantly decreases the amount of time necessary to generate these measurements.

  3. Active hexagonally segmented mirror to investigate new optical phasing technologies for segmented telescopes.

    PubMed

    Gonté, Frédéric; Dupuy, Christophe; Luong, Bruno; Frank, Christoph; Brast, Roland; Sedghi, Baback

    2009-11-10

    The primary mirror of the future European Extremely Large Telescope will be equipped with 984 hexagonal segments. The alignment of the segments in piston, tip, and tilt within a few nanometers requires an optical phasing sensor. A test bench has been designed to study four different optical phasing sensor technologies. The core element of the test bench is an active segmented mirror composed of 61 flat hexagonal segments with a size of 17 mm side to side. Each of them can be controlled in piston, tip, and tilt by three piezoactuators with a precision better than 1 nm. The context of this development, the requirements, the design, and the integration of this system are explained. The first results on the final precision obtained in closed-loop control are also presented.

  4. Active hexagonally segmented mirror to investigate new optical phasing technologies for segmented telescopes.

    PubMed

    Gonté, Frédéric; Dupuy, Christophe; Luong, Bruno; Frank, Christoph; Brast, Roland; Sedghi, Baback

    2009-11-10

    The primary mirror of the future European Extremely Large Telescope will be equipped with 984 hexagonal segments. The alignment of the segments in piston, tip, and tilt within a few nanometers requires an optical phasing sensor. A test bench has been designed to study four different optical phasing sensor technologies. The core element of the test bench is an active segmented mirror composed of 61 flat hexagonal segments with a size of 17 mm side to side. Each of them can be controlled in piston, tip, and tilt by three piezoactuators with a precision better than 1 nm. The context of this development, the requirements, the design, and the integration of this system are explained. The first results on the final precision obtained in closed-loop control are also presented. PMID:19904341

  5. Fully automatic contour detection in intravascular ultrasound imaging

    NASA Astrophysics Data System (ADS)

    Brusseau, Elisabeth F.; de Korte, Chris L.; Mastik, Fritz; Schaar, Johannes; van der Steen, Anton F.

    2004-04-01

    Segmentation of deformable structures remains a challenging task in ultrasound imaging especially in low signal-to-noise ratio applications. In this paper a fully automatic method, dedicated to the luminal contour segmentation in intracoronary ultrasound imaging is introduced. The method is based on an active contour with a priori properties that evolves according to the statistics of the ultrasound texture brightness, determined as being mainly Rayleigh distributed. However, contrary to classical snake-based algorithms, the presented technique neither requires from the user the pre-selection of a region of interest tight around the boundary, nor parameter tuning. This fully automatic character is achieved by an initial contour that is not set, but estimated and thus adapted to each image. Its estimation combines two statistical criteria extracted from the a posteriori probability, function of the contour position. These criteria are the location of the function maximum (or maximum a posteriori estimator) and the first zero-crossing of the function derivative. Then starting form the initial contour, a region of interest is automatically selected and the process iterated until the contour evolution can be ignored. In vivo coronary images from 15 patients, acquired with a 20 MHz central frequency Jomed Invision ultrasound scanner were segmented with the developed method. Automatic contours were compared to those manually drawn by two physician in terms of mean absolute difference. Results demonstrate that the error between automatic contours and the average of manual ones (0.099+/-0.032mm) and the inter-expert error (0.097+/-0.027mm) are similar and of small amplitude.

  6. Contour adaptation.

    PubMed

    Anstis, Stuart

    2013-01-01

    It is known that adaptation to a disk that flickers between black and white at 3-8 Hz on a gray surround renders invisible a congruent gray test disk viewed afterwards. This is contrast adaptation. We now report that adapting simply to the flickering circular outline of the disk can have the same effect. We call this "contour adaptation." This adaptation does not transfer interocularly, and apparently applies only to luminance, not color. One can adapt selectively to only some of the contours in a display, making only these contours temporarily invisible. For instance, a plaid comprises a vertical grating superimposed on a horizontal grating. If one first adapts to appropriate flickering vertical lines, the vertical components of the plaid disappears and it looks like a horizontal grating. Also, we simulated a Cornsweet (1970) edge, and we selectively adapted out the subjective and objective contours of a Kanisza (1976) subjective square. By temporarily removing edges, contour adaptation offers a new technique to study the role of visual edges, and it demonstrates how brightness information is concentrated in edges and propagates from them as it fills in surfaces.

  7. Segmentation of knee cartilage by using a hierarchical active shape model based on multi-resolution transforms in magnetic resonance images

    NASA Astrophysics Data System (ADS)

    León, Madeleine; Escalante-Ramirez, Boris

    2013-11-01

    Knee osteoarthritis (OA) is characterized by the morphological degeneration of cartilage. Efficient segmentation of cartilage is important for cartilage damage diagnosis and to support therapeutic responses. We present a method for knee cartilage segmentation in magnetic resonance images (MRI). Our method incorporates the Hermite Transform to obtain a hierarchical decomposition of contours which describe knee cartilage shapes. Then, we compute a statistical model of the contour of interest from a set of training images. Thereby, our Hierarchical Active Shape Model (HASM) captures a large range of shape variability even from a small group of training samples, improving segmentation accuracy. The method was trained with a training set of 16- MRI of knee and tested with leave-one-out method.

  8. Contour Tones.

    ERIC Educational Resources Information Center

    Yip, Moira

    1989-01-01

    Argues that contour tones in East Asian languages behave as melodic units consisting of a root node [upper] dominating a branching specification. It is also argued that, with upper as the tonal root node, no more than two rising or falling tones will contrast underlying. (49 references) (JL)

  9. The origin of segmentation motor activity in the intestine.

    PubMed

    Huizinga, Jan D; Chen, Ji-Hong; Zhu, Yong Fang; Pawelka, Andrew; McGinn, Ryan J; Bardakjian, Berj L; Parsons, Sean P; Kunze, Wolfgang A; Wu, Richard You; Bercik, Premysl; Khoshdel, Amir; Chen, Sifeng; Yin, Sheng; Zhang, Qian; Yu, Yuanjie; Gao, Qingmin; Li, Kongling; Hu, Xinghai; Zarate, Natalia; Collins, Phillip; Pistilli, Marc; Ma, Junling; Zhang, Ruixue; Chen, David

    2014-01-01

    The segmentation motor activity of the gut that facilitates absorption of nutrients was first described in the late 19th century, but the fundamental mechanisms underlying it remain poorly understood. The dominant theory suggests alternate excitation and inhibition from the enteric nervous system. Here we demonstrate that typical segmentation can occur after total nerve blockade. The segmentation motor pattern emerges when the amplitude of the dominant pacemaker, the slow wave generated by interstitial cells of Cajal associated with the myenteric plexus (ICC-MP), is modulated by the phase of induced lower frequency rhythmic transient depolarizations, generated by ICC associated with the deep muscular plexus (ICC-DMP), resulting in a waxing and waning of the amplitude of the slow wave and a rhythmic checkered pattern of segmentation motor activity. Phase-amplitude modulation of the slow waves points to an underlying system of coupled nonlinear oscillators originating in the networks of ICC.

  10. A robust active contour edge detection algorithm based on local Gaussian statistical model for oil slick remote sensing image

    NASA Astrophysics Data System (ADS)

    Jing, Yu; Wang, Yaxuan; Liu, Jianxin; Liu, Zhaoxia

    2015-08-01

    Edge detection is a crucial method for the location and quantity estimation of oil slick when oil spills on the sea. In this paper, we present a robust active contour edge detection algorithm for oil spill remote sensing images. In the proposed algorithm, we define a local Gaussian data fitting energy term with spatially varying means and variances, and this data fitting energy term is introduced into a global minimization active contour (GMAC) framework. The energy function minimization is achieved fast by a dual formulation of the weighted total variation norm. The proposed algorithm avoids the existence of local minima, does not require the definition of initial contour, and is robust to weak boundaries, high noise and severe intensity inhomogeneity exiting in oil slick remote sensing images. Furthermore, the edge detection of oil slick and the correction of intensity inhomogeneity are simultaneously achieved via the proposed algorithm. The experiment results have shown that a superior performance of proposed algorithm over state-of-the-art edge detection algorithms. In addition, the proposed algorithm can also deal with the special images with the object and background of the same intensity means but different variances.

  11. A strategic approach for cardiac MR left ventricle segmentation.

    PubMed

    Dakua, Sarada Prasad; Sahambi, J S

    2010-09-01

    Quantitative evaluation of cardiac function from cardiac magnetic resonance (CMR) images requires the identification of the myocardial walls. This generally requires the clinician to view the image and interactively trace the contours. Especially, detection of myocardial walls of left ventricle is a difficult task in CMR images that are obtained from subjects having serious diseases. An approach to automated outlining the left ventricular contour is proposed. In order to segment the left ventricle, in this paper, a combination of two approaches is suggested. Difference of Gaussian weighting function (DoG) is newly introduced in random walk approach for blood pool (inner contour) extraction. The myocardial wall (outer contour) is segmented out by a modified active contour method that takes blood pool boundary as the initial contour. Promising experimental results in CMR images demonstrate the potentials of our approach.

  12. Activity recognition using Video Event Segmentation with Text (VEST)

    NASA Astrophysics Data System (ADS)

    Holloway, Hillary; Jones, Eric K.; Kaluzniacki, Andrew; Blasch, Erik; Tierno, Jorge

    2014-06-01

    Multi-Intelligence (multi-INT) data includes video, text, and signals that require analysis by operators. Analysis methods include information fusion approaches such as filtering, correlation, and association. In this paper, we discuss the Video Event Segmentation with Text (VEST) method, which provides event boundaries of an activity to compile related message and video clips for future interest. VEST infers meaningful activities by clustering multiple streams of time-sequenced multi-INT intelligence data and derived fusion products. We discuss exemplar results that segment raw full-motion video (FMV) data by using extracted commentary message timestamps, FMV metadata, and user-defined queries.

  13. Abdomen and spinal cord segmentation with augmented active shape models.

    PubMed

    Xu, Zhoubing; Conrad, Benjamin N; Baucom, Rebeccah B; Smith, Seth A; Poulose, Benjamin K; Landman, Bennett A

    2016-07-01

    Active shape models (ASMs) have been widely used for extracting human anatomies in medical images given their capability for shape regularization of topology preservation. However, sensitivity to model initialization and local correspondence search often undermines their performances, especially around highly variable contexts in computed-tomography (CT) and magnetic resonance (MR) images. In this study, we propose an augmented ASM (AASM) by integrating the multiatlas label fusion (MALF) and level set (LS) techniques into the traditional ASM framework. Using AASM, landmark updates are optimized globally via a region-based LS evolution applied on the probability map generated from MALF. This augmentation effectively extends the searching range of correspondent landmarks while reducing sensitivity to the image contexts and improves the segmentation robustness. We propose the AASM framework as a two-dimensional segmentation technique targeting structures with one axis of regularity. We apply AASM approach to abdomen CT and spinal cord (SC) MR segmentation challenges. On 20 CT scans, the AASM segmentation of the whole abdominal wall enables the subcutaneous/visceral fat measurement, with high correlation to the measurement derived from manual segmentation. On 28 3T MR scans, AASM yields better performances than other state-of-the-art approaches in segmenting white/gray matter in SC. PMID:27610400

  14. Application and histology-driven refinement of active contour models to functional region and nerve delineation: towards a digital brainstem atlas

    NASA Astrophysics Data System (ADS)

    Patel, Nirmal; Sultana, Sharmin; Rashid, Tanweer; Krusienski, Dean; Audette, Michel A.

    2015-03-01

    This paper presents a methodology for the digital formatting of a printed atlas of the brainstem and the delineation of cranial nerves from this digital atlas. It also describes on-going work on the 3D resampling and refinement of the 2D functional regions and nerve contours. In MRI-based anatomical modeling for neurosurgery planning and simulation, the complexity of the functional anatomy entails a digital atlas approach, rather than less descriptive voxel or surface-based approaches. However, there is an insufficiency of descriptive digital atlases, in particular of the brainstem. Our approach proceeds from a series of numbered, contour-based sketches coinciding with slices of the brainstem featuring both closed and open contours. The closed contours coincide with functionally relevant regions, whereby our objective is to fill in each corresponding label, which is analogous to painting numbered regions in a paint-by-numbers kit. Any open contour typically coincides with a cranial nerve. This 2D phase is needed in order to produce densely labeled regions that can be stacked to produce 3D regions, as well as identifying the embedded paths and outer attachment points of cranial nerves. Cranial nerves are modeled using an explicit contour based technique called 1-Simplex. The relevance of cranial nerves modeling of this project is two-fold: i) this atlas will fill a void left by the brain segmentation communities, as no suitable digital atlas of the brainstem exists, and ii) this atlas is necessary to make explicit the attachment points of major nerves (except I and II) having a cranial origin. Keywords: digital atlas, contour models, surface models

  15. Contour Mapping

    NASA Technical Reports Server (NTRS)

    1995-01-01

    In the early 1990s, the Ohio State University Center for Mapping, a NASA Center for the Commercial Development of Space (CCDS), developed a system for mobile mapping called the GPSVan. While driving, the users can map an area from the sophisticated mapping van equipped with satellite signal receivers, video cameras and computer systems for collecting and storing mapping data. George J. Igel and Company and the Ohio State University Center for Mapping advanced the technology for use in determining the contours of a construction site. The new system reduces the time required for mapping and staking, and can monitor the amount of soil moved.

  16. Algorithm for Constructing Contour Plots

    NASA Technical Reports Server (NTRS)

    Johnson, W.; Silva, F.

    1984-01-01

    General computer algorithm developed for construction of contour plots. algorithm accepts as input data values at set of points irregularly distributed over plane. Algorithm based on interpolation scheme: points in plane connected by straight-line segments to form set of triangles. Program written in FORTRAN IV.

  17. Magnetic Resonance Imaging-Based Target Volume Delineation in Radiation Therapy Treatment Planning for Brain Tumors Using Localized Region-Based Active Contour

    SciTech Connect

    Aslian, Hossein; Sadeghi, Mahdi; Mahdavi, Seied Rabie; Babapour Mofrad, Farshid; Astarakee, Mahdi; Khaledi, Navid; Fadavi, Pedram

    2013-09-01

    Purpose: To evaluate the clinical application of a robust semiautomatic image segmentation method to determine the brain target volumes in radiation therapy treatment planning. Methods and Materials: A local robust region-based algorithm was used on MRI brain images to study the clinical target volume (CTV) of several patients. First, 3 oncologists delineated CTVs of 10 patients manually, and the process time for each patient was calculated. The averages of the oncologists’ contours were evaluated and considered as reference contours. Then, to determine the CTV through the semiautomatic method, a fourth oncologist who was blind to all manual contours selected 4-8 points around the edema and defined the initial contour. The time to obtain the final contour was calculated again for each patient. Manual and semiautomatic segmentation were compared using 3 different metric criteria: Dice coefficient, Hausdorff distance, and mean absolute distance. A comparison also was performed between volumes obtained from semiautomatic and manual methods. Results: Manual delineation processing time of tumors for each patient was dependent on its size and complexity and had a mean (±SD) of 12.33 ± 2.47 minutes, whereas it was 3.254 ± 1.7507 minutes for the semiautomatic method. Means of Dice coefficient, Hausdorff distance, and mean absolute distance between manual contours were 0.84 ± 0.02, 2.05 ± 0.66 cm, and 0.78 ± 0.15 cm, and they were 0.82 ± 0.03, 1.91 ± 0.65 cm, and 0.7 ± 0.22 cm between manual and semiautomatic contours, respectively. Moreover, the mean volume ratio (=semiautomatic/manual) calculated for all samples was 0.87. Conclusions: Given the deformability of this method, the results showed reasonable accuracy and similarity to the results of manual contouring by the oncologists. This study shows that the localized region-based algorithms can have great ability in determining the CTV and can be appropriate alternatives for manual approaches in brain cancer.

  18. Three-Dimensional Contour Maps

    ERIC Educational Resources Information Center

    Lee, Edward

    2005-01-01

    In summary, this highly conceptual activity helps middle school students understand that the lines on the contour map represent intersections of the surface of the landform with regularly spaced horizontal planes. Building the landform and relating its features to the contour map offer many opportunities for visualization, all grounded in concrete…

  19. Reprogramming the Chemodiversity of Terpenoid Cyclization by Remolding the Active Site Contour of epi-Isozizaene Synthase

    PubMed Central

    2015-01-01

    The class I terpenoid cyclase epi-isozizaene synthase (EIZS) utilizes the universal achiral isoprenoid substrate, farnesyl diphosphate, to generate epi-isozizaene as the predominant sesquiterpene cyclization product and at least five minor sesquiterpene products, making EIZS an ideal platform for the exploration of fidelity and promiscuity in a terpenoid cyclization reaction. The hydrophobic active site contour of EIZS serves as a template that enforces a single substrate conformation, and chaperones subsequently formed carbocation intermediates through a well-defined mechanistic sequence. Here, we have used the crystal structure of EIZS as a guide to systematically remold the hydrophobic active site contour in a library of 26 site-specific mutants. Remolded cyclization templates reprogram the reaction cascade not only by reproportioning products generated by the wild-type enzyme but also by generating completely new products of diverse structure. Specifically, we have tripled the overall number of characterized products generated by EIZS. Moreover, we have converted EIZS into six different sesquiterpene synthases: F96A EIZS is an (E)-β-farnesene synthase, F96W EIZS is a zizaene synthase, F95H EIZS is a β-curcumene synthase, F95M EIZS is a β-acoradiene synthase, F198L EIZS is a β-cedrene synthase, and F96V EIZS and W203F EIZS are (Z)-γ-bisabolene synthases. Active site aromatic residues appear to be hot spots for reprogramming the cyclization cascade by manipulating the stability and conformation of critical carbocation intermediates. A majority of mutant enzymes exhibit only relatively modest 2–100-fold losses of catalytic activity, suggesting that residues responsible for triggering substrate ionization readily tolerate mutations deeper in the active site cavity. PMID:24517311

  20. Midbrain volume segmentation using active shape models and LBPs

    NASA Astrophysics Data System (ADS)

    Olveres, Jimena; Nava, Rodrigo; Escalante-Ramírez, Boris; Cristóbal, Gabriel; García-Moreno, Carla María.

    2013-09-01

    In recent years, the use of Magnetic Resonance Imaging (MRI) to detect different brain structures such as midbrain, white matter, gray matter, corpus callosum, and cerebellum has increased. This fact together with the evidence that midbrain is associated with Parkinson's disease has led researchers to consider midbrain segmentation as an important issue. Nowadays, Active Shape Models (ASM) are widely used in literature for organ segmentation where the shape is an important discriminant feature. Nevertheless, this approach is based on the assumption that objects of interest are usually located on strong edges. Such a limitation may lead to a final shape far from the actual shape model. This paper proposes a novel method based on the combined use of ASM and Local Binary Patterns for segmenting midbrain. Furthermore, we analyzed several LBP methods and evaluated their performance. The joint-model considers both global and local statistics to improve final adjustments. The results showed that our proposal performs substantially better than the ASM algorithm and provides better segmentation measurements.

  1. Which mantle below the active rift segments in Afar?

    NASA Astrophysics Data System (ADS)

    Pik, Raphael; Stab, Martin; Ancellin, Marie-Anne; Sarah, Medynski; Cloquet, Christophe; Vye-Brown, Charlotte; Ayalew, Dereje; Chazot, Gilles; Bellahsen, Nicolas; Leroy, Sylvie

    2014-05-01

    The evolution of mantle sources beneath the Ethiopian volcanic province has long been discussed and debated with a long-lived controversy in identifying mantle reservoirs and locating them in the mantle. One interpretation of the isotopic composition of erupted lavas considers that the Afar mantle plume composition is best expressed by recent lavas from Afar and Gulf of Aden (e.g. Erta Ale, Manda Inakir and the 45°E torus anomaly on the Gulf of Aden) implying that all other volcanics (including other active segments and the initial flood basalt province) result from mixing of this plume component with additional lithospheric and asthenospheric components. A completely opposite view considers that the initial Oligocene continental flood basalts best represent the isotopic composition of the Afar mantle plume, which is subsequently mixed in various proportions with continental lithospheric mantle for generating some of the specific signature of Miocene and Quaternary volcanics. The precise and correct identification of mantle components involved in the generation of magmas is of particular importance because this is the only way to document the participation of mantle during extension and its potential role in break-up processes. In this contribution we provide new isotopic data for central Afar and we revisit the whole data set of the Ethiopian volcanic province in order to: (i) precisely identify the distinct mantle components implicated and (ii) discuss their location and evolution not only considering geochemical mixings, but also taking into account additional characteristics of erupted magmatic suites (volumes, location and relationships with amount of extension and segmentation). This new interpretation of geochemical data allows reconsidering the evolution of mantle in the course of rift evolution. In terms of mantle sources, two populations of active segments are frontally opposed in the volcanic province: those that share exactly the same composition with

  2. Contour extraction of Drosophila embryos.

    PubMed

    Li, Qi; Kambhamettu, Chandra

    2011-01-01

    Contour extraction of Drosophila (fruit fly) embryos is an important step to build a computational system for matching expression pattern of embryonic images to assist the discovery of the nature of genes. Automatic contour extraction of embryos is challenging due to severe image variations, including 1) the size, orientation, shape, and appearance of an embryo of interest; 2) the neighboring context of an embryo of interest (such as nontouching and touching neighboring embryos); and 3) illumination circumstance. In this paper, we propose an automatic framework for contour extraction of the embryo of interest in an embryonic image. The proposed framework contains three components. Its first component applies a mixture model of quadratic curves, with statistical features, to initialize the contour of the embryo of interest. An efficient method based on imbalanced image points is proposed to compute model parameters. The second component applies active contour model to refine embryo contours. The third component applies eigen-shape modeling to smooth jaggy contours caused by blurred embryo boundaries. We test the proposed framework on a data set of 8,000 embryonic images, and achieve promising accuracy (88 percent), that is, substantially higher than the-state-of-the-art results.

  3. Classification of physical activities based on body-segments coordination.

    PubMed

    Fradet, Laetitia; Marin, Frederic

    2016-09-01

    Numerous innovations based on connected objects and physical activity (PA) monitoring have been proposed. However, recognition of PAs requires robust algorithm and methodology. The current study presents an innovative approach for PA recognition. It is based on the heuristic definition of postures and the use of body-segments coordination obtained through external sensors. The first part of this study presents the methodology required to define the set of accelerations which is the most appropriate to represent the particular body-segments coordination involved in the chosen PAs (here walking, running, and cycling). For that purpose, subjects of different ages and heterogeneous physical conditions walked, ran, cycled, and performed daily activities at different paces. From the 3D motion capture, vertical and horizontal accelerations of 8 anatomical landmarks representative of the body were computed. Then, the 680 combinations from up to 3 accelerations were compared to identify the most appropriate set of acceleration to discriminate the PAs in terms of body segment coordinations. The discrimination was based on the maximal Hausdorff Distance obtained between the different set of accelerations. The vertical accelerations of both knees demonstrated the best PAs discrimination. The second step was the proof of concept, implementing the proposed algorithm to classify PAs of new group of subjects. The originality of the proposed algorithm is the possibility to use the subject's specific measures as reference data. With the proposed algorithm, 94% of the trials were correctly classified. In conclusion, our study proposed a flexible and extendable methodology. At the current stage, the algorithm has been shown to be valid for heterogeneous subjects, which suggests that it could be deployed in clinical or health-related applications regardless of the subjects' physical abilities or characteristics.

  4. Classification of physical activities based on body-segments coordination.

    PubMed

    Fradet, Laetitia; Marin, Frederic

    2016-09-01

    Numerous innovations based on connected objects and physical activity (PA) monitoring have been proposed. However, recognition of PAs requires robust algorithm and methodology. The current study presents an innovative approach for PA recognition. It is based on the heuristic definition of postures and the use of body-segments coordination obtained through external sensors. The first part of this study presents the methodology required to define the set of accelerations which is the most appropriate to represent the particular body-segments coordination involved in the chosen PAs (here walking, running, and cycling). For that purpose, subjects of different ages and heterogeneous physical conditions walked, ran, cycled, and performed daily activities at different paces. From the 3D motion capture, vertical and horizontal accelerations of 8 anatomical landmarks representative of the body were computed. Then, the 680 combinations from up to 3 accelerations were compared to identify the most appropriate set of acceleration to discriminate the PAs in terms of body segment coordinations. The discrimination was based on the maximal Hausdorff Distance obtained between the different set of accelerations. The vertical accelerations of both knees demonstrated the best PAs discrimination. The second step was the proof of concept, implementing the proposed algorithm to classify PAs of new group of subjects. The originality of the proposed algorithm is the possibility to use the subject's specific measures as reference data. With the proposed algorithm, 94% of the trials were correctly classified. In conclusion, our study proposed a flexible and extendable methodology. At the current stage, the algorithm has been shown to be valid for heterogeneous subjects, which suggests that it could be deployed in clinical or health-related applications regardless of the subjects' physical abilities or characteristics. PMID:27441831

  5. [Body-contouring surgery].

    PubMed

    Pitanguy, Ivo

    2003-01-01

    Concepts of beauty have been continuously evolving throughout the history of mankind. The voluptuous figures that were idealized by artists in the past have been substituted by slimmer forms. Medical advances in this century have permitted safe and efficient surgical correction of contour deformities. Until recently, these alterations were mostly hidden under heavy clothing or were reluctantly accepted. Current fashion trends generally promote body-revealing attire. The media frequently encourages the importance of fitness and good health linking these qualities with youthfulness and beauty. The subliminal as well as overt message is that these are necessary and desirable requirements for social acceptance and professional success. On the other hand, current sedentary lifestyle and dietary excesses, associated with factors such as genetic determination, pregnancy and the aging process, contribute to alterations of body contour that result in the loss of the individual's body image. This creates a strong psychological motivation for surgical correction. Localized fat deposits and skin flaccidity are sometimes resistant to the most sincere efforts in weight loss and sport activities. This ever-increasing request for contour surgery has been favorably met by safe and effective anesthesiology as well as efficient surgical techniques, resulting in a high degree of patient satisfaction. It is essential that today's aesthetic surgeon understand the motivations of patients who present with body contour deformities. A request for surgical treatment should be seen as a legitimate desire to achieve a physical form that approximates the individual with his or her ideal self-image. Additionally, the surgeon must always consider the possible benefit of including the participation of a multidisciplinary team approach. Depending on each case, this team should include consultants in endocrinology, dermatology, oculoplastics, pediatrics and other appropriate specialties.

  6. Top-down control in contour grouping.

    PubMed

    Volberg, Gregor; Wutz, Andreas; Greenlee, Mark W

    2013-01-01

    Human observers tend to group oriented line segments into full contours if they follow the Gestalt rule of 'good continuation'. It is commonly assumed that contour grouping emerges automatically in early visual cortex. In contrast, recent work in animal models suggests that contour grouping requires learning and thus involves top-down control from higher brain structures. Here we explore mechanisms of top-down control in perceptual grouping by investigating synchronicity within EEG oscillations. Human participants saw two micro-Gabor arrays in a random order, with the task to indicate whether the first (S1) or the second stimulus (S2) contained a contour of collinearly aligned elements. Contour compared to non-contour S1 produced a larger posterior post-stimulus beta power (15-21 Hz). Contour S2 was associated with a pre-stimulus decrease in posterior alpha power (11-12 Hz) and in fronto-posterior theta (4-5 Hz) phase couplings, but not with a post-stimulus increase in beta power. The results indicate that subjects used prior knowledge from S1 processing for S2 contour grouping. Expanding previous work on theta oscillations, we propose that long-range theta synchrony shapes neural responses to perceptual groupings regulating lateral inhibition in early visual cortex.

  7. User-driven segmentation approach: interactive snakes

    NASA Astrophysics Data System (ADS)

    Kunert, Tobias; Heiland, Marc; Meinzer, Hans-Peter

    2002-05-01

    For diagnostics and therapy planning, the segmentation of medical images is an important pre-processing step. Currently, manual segmentation tools are most common in clinical routine. Because the work is very time-consuming, there is a large interest in tools assisting the physician. Most of the known segmentation techniques suffer from an inadequate user interface, which prevents their use in a clinical environment. The segmentation of medical images is very difficult. A promising method to overcome difficulties such as imaging artifacts are active contour models. In order to enhance the clinical usability, we propose a user-driven segmentation approach. Following this way, we developed a new segmentation method, which we call interactive snakes. Thereto, we elaborated an interaction style which is more intuitive to the clinical user and derived a new active contour model. The segmentation method provides a very tight coupling with the user. The physician is interactively attaching boundary markers to the image, whereby he is able to bring in his knowledge. At the same time, the segmentation is updated in real-time. Interactive snakes are a comprehensible segmentation method for the clinical use. It is reasonable to employ them both as a core tool and as an editing tool for incorrect results.

  8. Contouring randomly spaced data

    NASA Technical Reports Server (NTRS)

    Kibler, J. F.; Morris, W. D.; Hamm, R. W.

    1977-01-01

    Computer program using triangulation contouring technique contours data points too numerous to fit into rectangular grid. Using random access procedures, program can handle up to 56,000 data points and provides up to 20 contour intervals for multiple number of parameters.

  9. Guided energy-minimizing model for segmentation of vector fields

    NASA Astrophysics Data System (ADS)

    Binias, Bartosz

    2016-06-01

    Active contours or snakes, are a group of image segmentation methods based on the idea of energy-minimizng curves. In this paper classical snake model with added Balloon Force is modified, granting it the capability of performing object segmentation task on data with unlimited number of channels. Thanks to introduction of novel component, named the Guiding Energy, into the classical active contour energy functional, the method is now capable of focusing on the objects which posses a specified features provided to the model.

  10. Uterus segmentation in dynamic MRI using LBP texture descriptors

    NASA Astrophysics Data System (ADS)

    Namias, R.; Bellemare, M.-E.; Rahim, M.; Pirró, N.

    2014-03-01

    Pelvic floor disorders cover pathologies of which physiopathology is not well understood. However cases get prevalent with an ageing population. Within the context of a project aiming at modelization of the dynamics of pelvic organs, we have developed an efficient segmentation process. It aims at alleviating the radiologist with a tedious one by one image analysis. From a first contour delineating the uterus-vagina set, the organ border is tracked along a dynamic mri sequence. The process combines movement prediction, local intensity and texture analysis and active contour geometry control. Movement prediction allows a contour intitialization for next image in the sequence. Intensity analysis provides image-based local contour detection enhanced by local binary pattern (lbp) texture descriptors. Geometry control prohibits self intersections and smoothes the contour. Results show the efficiency of the method with images produced in clinical routine.

  11. Contour integration with corners.

    PubMed

    Persike, Malte; Meinhardt, Günter

    2016-10-01

    Contour integration refers to the ability of the visual system to bind disjoint local elements into coherent global shapes. In cluttered images containing randomly oriented elements a contour becomes salient when its elements are coaligned with a smooth global trajectory, as described by the Gestalt law of good continuation. Abrupt changes of curvature strongly diminish contour salience. Here we show that by inserting local corner elements at points of angular discontinuity, a jagged contour becomes as salient as a straight one. We report results from detection experiments for contours with and without corner elements which indicate their psychophysical equivalence. This presents a challenge to the notion that contour integration mostly relies on local interactions between neurons tuned to single orientations, and suggests that a site where single orientations and more complex local features are combined constitutes the early basis of contour and 2D shape processing.

  12. Contour integration with corners.

    PubMed

    Persike, Malte; Meinhardt, Günter

    2016-10-01

    Contour integration refers to the ability of the visual system to bind disjoint local elements into coherent global shapes. In cluttered images containing randomly oriented elements a contour becomes salient when its elements are coaligned with a smooth global trajectory, as described by the Gestalt law of good continuation. Abrupt changes of curvature strongly diminish contour salience. Here we show that by inserting local corner elements at points of angular discontinuity, a jagged contour becomes as salient as a straight one. We report results from detection experiments for contours with and without corner elements which indicate their psychophysical equivalence. This presents a challenge to the notion that contour integration mostly relies on local interactions between neurons tuned to single orientations, and suggests that a site where single orientations and more complex local features are combined constitutes the early basis of contour and 2D shape processing. PMID:27542687

  13. CONTOURING RANDOMLY SPACED DATA

    NASA Technical Reports Server (NTRS)

    Hamm, R. W.

    1994-01-01

    This program prepares contour plots of three-dimensional randomly spaced data. The contouring techniques use a triangulation procedure developed by Dr. C. L. Lawson of the Jet Propulsion Laboratory which allows the contouring of randomly spaced input data without first fitting the data into a rectangular grid. The program also allows contour points to be fitted with a smooth curve using an interpolating spline under tension. The input data points to be contoured are read from a magnetic tape or disk file with one record for each data point. Each record contains the X and Y coordinates, value to be contoured, and an alternate contour value (if applicable). The contour data is then partitioned by the program to reduce core storage requirements. Output consists of the contour plots and user messages. Several output options are available to the user such as: controlling which value in the data record is to be contoured, whether contours are drawn by polygonal lines or by a spline under tension (smooth curves), and controlling the contour level labels which may be suppressed if desired. The program can handle up to 56,000 data points and provide for up to 20 contour intervals for a multiple number of parameters. This program was written in FORTRAN IV for implementation on a CDC 6600 computer using CALCOMP plotting capabilities. The field length required is dependent upon the number of data points to be contoured. The program requires 42K octal storage locations plus the larger of: 24 times the maximum number of points in each data partition (defaults to maximum of 1000 data points in each partition with 20 percent overlap) or 2K plus four times the total number of points to be plotted. This program was developed in 1975.

  14. Segmentation of polycystic kidneys from MR images

    NASA Astrophysics Data System (ADS)

    Racimora, Dimitri; Vivier, Pierre-Hugues; Chandarana, Hersh; Rusinek, Henry

    2010-03-01

    Polycystic kidney disease (PKD) is a disorder characterized by the growth of numerous fluid filled cysts in the kidneys. Measuring cystic kidney volume is thus crucial to monitoring the evolution of the disease. While T2-weighted MRI delineates the organ, automatic segmentation is very difficult due to highly variable shape and image contrast. The interactive stereology methods used currently involve a compromise between segmentation accuracy and time. We have investigated semi-automated methods: active contours and a sub-voxel morphology based algorithm. Coronal T2- weighted images of 17 patients were acquired in four breath-holds using the HASTE sequence on a 1.5 Tesla MRI unit. The segmentation results were compared to ground truth kidney masks obtained as a consensus of experts. Automatic active contour algorithm yielded an average 22% +/- 8.6% volume error. A recently developed method (Bridge Burner) based on thresholding and constrained morphology failed to separate PKD from the spleen, yielding 37.4% +/- 8.7% volume error. Manual post-editing reduced the volume error to 3.2% +/- 0.8% for active contours and 3.2% +/- 0.6% for Bridge Burner. The total time (automated algorithm plus editing) was 15 min +/- 5 min for active contours and 19 min +/- 11 min for Bridge Burner. The average volume errors for stereology method were 5.9%, 6.2%, 5.4% for mesh size 6.6, 11, 16.5 mm. The average processing times were 17, 7, 4 min. These results show that nearly two-fold improvement in PKD segmentation accuracy over stereology technique can be achieved with a combination of active contours and postediting.

  15. A Typology of Middle School Girls: Audience Segmentation Related to Physical Activity

    PubMed Central

    Staten, Lisa K.; Birnbaum, Amanda S.; Jobe, Jared B.; Elder, John P.

    2008-01-01

    The Trial of Activity for Adolescent Girls (TAAG) combines social ecological and social marketing approaches to promote girls’ participation in physical activity programs implemented at 18 middle schools throughout the United States. Key to the TAAG approach is targeting materials to a variety of audience segments. TAAG segments are individuals who share one or more common characteristic that is expected to correlate with physical activity. Thirteen focus groups with seventh and eighth grade girls were conducted to identify and characterize segments. Potential messages and channels of communication were discussed for each segment. Based on participant responses, six primary segments were identified: athletic, preppy, quiet, rebel, smart, and tough. The focus group information was used to develop targeted promotional tools to appeal to a diversity of girls. Using audience segmentation for targeting persuasive communication is potentially useful for intervention programs but may be sensitive; therefore, ethical issues must be critically examined. PMID:16397160

  16. Fault Segmentation and its Implication to the Evaluation of Future Earthquakes from Active Faults in Japan

    NASA Astrophysics Data System (ADS)

    Awata, Y.; Yoshioka, T.

    2005-12-01

    Segmentation of active faults is essential for the evaluation both of past and future faulting using geologic data from paleoseismological sites. A behavioral segment is defined as the smallest segment of fault having a characteristic history of faulting. More over, we have to estimate the earthquake segments that can be consist of multiple faulting along a system of behavioral segments. Active fault strands in Japan are segmented into behavioral segments based on fault discontinuity of 2-3 km and larger (Active Fault Res. Group, GSJ, 2000), large bend of fault strand and paleoseismicity. 431 behavioral segments, >= 10 km in length and >= 0.1 m/ky in long-term slip-rate, are identified from a database of active faults in Japan, that is constructed at AFRC, GSJ/AIST. The length of the segments is averaged 21 km and approximately 70 km in maximum. Only 8 segments are exceed 45 km in length. These lengths are very similar to those of historical surface ruptures not only in Japan since 1891 Nobi earthquake, but also in other regions having different tectonic setting. According to the scaling law between fault length and amount of displacement of behavioral segment, a maximum length of ca. 70 km can estimate a slip of ca. 14 m. This amount of slip is as large as world largest slip occurred during the 1931 Fuyun earthquake of M 8, 1999 Chichi earthquake of M 7.4 and the 2001 Central Kunlun earthquake of M 7.9 in East Asia. Recent geological and seismological studies on large earthquakes have revealed that multiple-rupturing is very common during large earthquakes. Therefore, evaluation of simultaneous faulting along a system of active faults is indispensable for the estimation of earthquake size. A Matsuda's (1990) idea of "seismogenic faults", that is divided or grouped based on the geometric discontinuity of 5 km, may useful for the best estimation of earthquake segment. The Japanese behavioral segments are grouped into "seismogenic faults", each consists of about 2

  17. A Typology of Middle School Girls: Audience Segmentation Related to Physical Activity

    ERIC Educational Resources Information Center

    Staten, Lisa K.; Birnbaum, Amanda S.; Jobe, Jared B.; Elder, John P.

    2006-01-01

    The Trial of Activity for Adolescent Girls (TAAG) combines social ecological and social marketing approaches to promote girls' participation in physical activity programs implemented at 18 middle schools throughout the United States. Key to the TAAG approach is targeting materials to a variety of audience segments. TAAG segments are individuals…

  18. Distributed Contour Trees

    SciTech Connect

    Morozov, Dmitriy; Weber, Gunther H.

    2014-03-31

    Topological techniques provide robust tools for data analysis. They are used, for example, for feature extraction, for data de-noising, and for comparison of data sets. This chapter concerns contour trees, a topological descriptor that records the connectivity of the isosurfaces of scalar functions. These trees are fundamental to analysis and visualization of physical phenomena modeled by real-valued measurements. We study the parallel analysis of contour trees. After describing a particular representation of a contour tree, called local{global representation, we illustrate how di erent problems that rely on contour trees can be solved in parallel with minimal communication.

  19. Fast marching over the 2D Gabor magnitude domain for tongue body segmentation

    NASA Astrophysics Data System (ADS)

    Cui, Zhenchao; Zhang, Hongzhi; Zhang, David; Li, Naimin; Zuo, Wangmeng

    2013-12-01

    Tongue body segmentation is a prerequisite to tongue image analysis and has recently received considerable attention. The existing tongue body segmentation methods usually involve two key steps: edge detection and active contour model (ACM)-based segmentation. However, conventional edge detectors cannot faithfully detect the contour of the tongue body, and the initialization of ACM suffers from the edge discontinuity problem. To address these issues, we proposed a novel tongue body segmentation method, GaborFM, which initializes ACM by performing fast marching over the two-dimensional (2D) Gabor magnitude domain of the tongue images. For the enhancement of the contour of the tongue body, we used the 2D Gabor magnitude-based detector. To cope with the edge discontinuity problem, the fast marching method was utilized to connect the discontinuous contour segments, resulting in a closed and continuous tongue body contour for subsequent ACM-based segmentation. Qualitative and quantitative results showed that GaborFM is superior to the other methods for tongue body segmentation.

  20. Automatic Coronary Artery Segmentation Using Active Search for Branches and Seemingly Disconnected Vessel Segments from Coronary CT Angiography

    PubMed Central

    Shim, Hackjoon; Jeon, Byunghwan; Jang, Yeonggul; Hong, Youngtaek; Jung, Sunghee; Ha, Seongmin; Chang, Hyuk-Jae

    2016-01-01

    We propose a Bayesian tracking and segmentation method of coronary arteries on coronary computed tomographic angiography (CCTA). The geometry of coronary arteries including lumen boundary is estimated in Maximum A Posteriori (MAP) framework. Three consecutive sphere based filtering is combined with a stochastic process that is based on the similarity of the consecutive local neighborhood voxels and the geometric constraint of a vessel. It is also founded on the prior knowledge that an artery can be seen locally disconnected and consist of branches which may be seemingly disconnected due to plaque build up. For such problem, an active search method is proposed to find branches and seemingly disconnected but actually connected vessel segments. Several new measures have been developed for branch detection, disconnection check and planar vesselness measure. Using public domain Rotterdam CT dataset, the accuracy of extracted centerline is demonstrated and automatic reconstruction of coronary artery mesh is shown. PMID:27536939

  1. Supersonic inlet contour interpolation

    NASA Technical Reports Server (NTRS)

    Sorensen, N. E.; Latham, E. A.

    1975-01-01

    A method for designing supersonic inlet contours is described which consists in the interpolation of the contours of two known inlets designed for different Mach numbers, thereby determining the contours for a third inlet at an intermediate design Mach number. Several similar axisymmetric inlet contours were interpolated from known inlets with design Mach numbers ranging from 2.16 to 4.0 and with design Mach numbers differing by as much as 1.0. The flowfields were calculated according to Sorensen's (1965) computer program. Shockwave structure and pressure distribution characteristics are shown for the interpolated inlets. The validity of the interpolation is demonstrated by comparing the plots of the flowfield properties across the throat station of the interpolated inlet with the known inlets which were designed iteratively. It seems possible to write a computer program so that a matrix of known inlet contours can be interpolated.

  2. Fast globally optimal segmentation of cells in fluorescence microscopy images.

    PubMed

    Bergeest, Jan-Philip; Rohr, Karl

    2011-01-01

    Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. We propose a new approach for segmenting cell nuclei which is based on active contours and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches.

  3. Contour-based classification of video objects

    NASA Astrophysics Data System (ADS)

    Richter, Stephan; Kuehne, Gerald; Schuster, Oliver

    2000-12-01

    The recognition of objects that appear in a video sequence is an essential aspect of any video content analysis system. We present an approach which classifies a segmented video object base don its appearance in successive video frames. The classification is performed by matching curvature features of the contours of these object views to a database containing preprocessed views of prototypical objects using a modified curvature scale space technique. By integrating the result of an umber of successive frames and by using the modified curvature scale space technique as an efficient representation of object contours, our approach enables the robust, tolerant and rapid object classification of video objects.

  4. Contour-based classification of video objects

    NASA Astrophysics Data System (ADS)

    Richter, Stephan; Kuehne, Gerald; Schuster, Oliver

    2001-01-01

    The recognition of objects that appear in a video sequence is an essential aspect of any video content analysis system. We present an approach which classifies a segmented video object base don its appearance in successive video frames. The classification is performed by matching curvature features of the contours of these object views to a database containing preprocessed views of prototypical objects using a modified curvature scale space technique. By integrating the result of an umber of successive frames and by using the modified curvature scale space technique as an efficient representation of object contours, our approach enables the robust, tolerant and rapid object classification of video objects.

  5. A geometric deformable model for echocardiographic image segmentation

    NASA Technical Reports Server (NTRS)

    Hang, X.; Greenberg, N. L.; Thomas, J. D.

    2002-01-01

    Gradient vector flow (GVF), an elegant external force for parametric deformable models, can capture object boundaries from both sides. A new geometric deformable model is proposed that combines GVF and the geodesic active contour model. The level set method is used as the numerical method of this model. The model is applied for echocardiographic image segmentation.

  6. Male Body Contouring.

    PubMed

    Singh, Babu; Keaney, Terrence; Rossi, Anthony M

    2015-09-01

    Men are increasingly turning to dermatologists and plastic surgeons to request procedures that correct or enhance physical features. With the advent of this emerging new patient population, alterations in preexisting aesthetic techniques, gender-specific uses of existing devices and overall approaches need to be revisited and adapted to obtain results that are suitable for the male patient. Recently, body contouring has become one of the most sought out procedures by men. Although the majority of clinical studies involving body contouring esthetics are performed with female patients, gains from such studies can be extrapolated to men. Body contouring can be broadly classified as non-invasive or invasive, depending on the modality used. Non-invasive contouring is most frequently performed with devices that target subcutaneous adipose with focused electrical or thermal energy, including low-level laser, cryolipolysis, ultrasonography, and radiofrequency. Invasive body contouring modalities useful for male body contouring include liposuction, pectoral and abdominal wall etching, jawline fillers, synthetic deoxycholic acid injections, and solid silicone implants. The purpose of this review is to bring attention to the unique aspects, strategies, and modalities used in aesthetic body contouring for the male patient.

  7. Variable contour securing system

    NASA Technical Reports Server (NTRS)

    Zebus, P. P.; Packer, P. N.; Haynie, C. C. (Inventor)

    1978-01-01

    A variable contour securing system has a retaining structure for a member whose surface contains a variable contour. The retaining mechanism includes a spaced array of adjustable spindles mounted on a housing. Each spindle has a base member support cup at one end. A vacuum source is applied to the cups for seating the member adjacent to the cups. A locking mechanism sets the spindles in a predetermined position once the member has been secured to the spindle support cups.

  8. Algorithms for Accurate and Fast Plotting of Contour Surfaces in 3D Using Hexahedral Elements

    NASA Astrophysics Data System (ADS)

    Singh, Chandan; Saini, Jaswinder Singh

    2016-07-01

    In the present study, Fast and accurate algorithms for the generation of contour surfaces in 3D are described using hexahedral elements which are popular in finite element analysis. The contour surfaces are described in the form of groups of boundaries of contour segments and their interior points are derived using the contour equation. The locations of contour boundaries and the interior points on contour surfaces are as accurate as the interpolation results obtained by hexahedral elements and thus there are no discrepancies between the analysis and visualization results.

  9. Evaluation of image features and search strategies for segmentation of bone structures in radiographs using Active Shape Models.

    PubMed

    Behiels, Gert; Maes, Frederik; Vandermeulen, Dirk; Suetens, Paul

    2002-03-01

    In this paper, we evaluate various image features and different search strategies for fitting Active Shape Models (ASM) to bone object boundaries in digitized radiographs. The original ASM method iteratively refines the pose and shape parameters of the point distribution model driving the ASM by a least squares fit of the shape to update the target points at the estimated object boundary position, as determined by a suitable object boundary criterion. We propose an improved search procedure that is more robust against outlier configurations in the boundary target points by requiring subsequent shape changes to be smooth, which is imposed by a smoothness constraint on the displacement of neighbouring target points at each iteration and implemented by a minimal cost path approach. We compare the original ASM search method and our improved search algorithm with a third method that does not rely on iteratively refined target point positions, but instead optimizes a global Bayesian objective function derived from statistical a priori contour shape and image models. Extensive validation of these methods on a database containing more than 400 images of the femur, humerus and calcaneus using the manual expert segmentation as ground truth shows that our minimal cost path method is the most robust. We also evaluate various measures for capturing local image appearance around each boundary point and conclude that the Mahalanobis distance applied to normalized image intensity profiles extracted normal to the shape is the most suitable criterion among the tested ones for guiding the ASM optimization. PMID:11836134

  10. GENERALIZED DIGITAL CONTOURING PROGRAM

    NASA Technical Reports Server (NTRS)

    Jones, R. L.

    1994-01-01

    This is a digital computer contouring program developed by combining desirable characteristics from several existing contouring programs. It can easily be adapted to many different research requirements. The overlaid structure of the program permits desired modifications to be made with ease. The contouring program performs both the task of generating a depth matrix from either randomly or regularly spaced surface heights and the task of contouring the data. Each element of the depth matrix is computed as a weighted mean of heights predicted at an element by planes tangent to the surface at neighboring control points. Each contour line is determined by its intercepts with the sides of geometrical figures formed by connecting the various elements of the depth matrix with straight lines. Although contour charts are usually thought of as being two-dimensional pictorial representations of topographic formations of land masses, they can also be useful in portraying data which are obtained during the course of research in various scientific disciplines and which would ordinarily be tabulated. Any set of data which can be referenced to a two-dimensional coordinate system can be graphically represented by this program. This program is written in FORTRAN IV and ASSEMBLER for batch execution and has been implemented on the CDC 6000 Series. This program was developed in 1971.

  11. Prostate contouring in MRI guided biopsy

    PubMed Central

    Vikal, Siddharth; Haker, Steven; Tempany, Clare; Fichtinger, Gabor

    2010-01-01

    With MRI possibly becoming a modality of choice for detection and staging of prostate cancer, fast and accurate outlining of the prostate is required in the volume of clinical interest. We present a semi-automatic algorithm that uses a priori knowledge of prostate shape to arrive at the final prostate contour. The contour of one slice is then used as initial estimate in the neighboring slices. Thus we propagate the contour in 3D through steps of refinement in each slice. The algorithm makes only minimum assumptions about the prostate shape. A statistical shape model of prostate contour in polar transform space is employed to narrow search space. Further, shape guidance is implicitly imposed by allowing only plausible edge orientations using template matching. The algorithm does not require region-homogeneity, discriminative edge force, or any particular edge profile. Likewise, it makes no assumption on the imaging coils and pulse sequences used and it is robust to the patient's pose (supine, prone, etc.). The contour method was validated using expert segmentation on clinical MRI data. We recorded a mean absolute distance of 2.0 ± 0.6 mm and dice similarity coefficient of 0.93 ± 0.3 in midsection. The algorithm takes about 1 second per slice. PMID:21132083

  12. Prostate contouring in MRI guided biopsy.

    PubMed

    Vikal, Siddharth; Haker, Steven; Tempany, Clare; Fichtinger, Gabor

    2009-03-27

    With MRI possibly becoming a modality of choice for detection and staging of prostate cancer, fast and accurate outlining of the prostate is required in the volume of clinical interest. We present a semi-automatic algorithm that uses a priori knowledge of prostate shape to arrive at the final prostate contour. The contour of one slice is then used as initial estimate in the neighboring slices. Thus we propagate the contour in 3D through steps of refinement in each slice. The algorithm makes only minimum assumptions about the prostate shape. A statistical shape model of prostate contour in polar transform space is employed to narrow search space. Further, shape guidance is implicitly imposed by allowing only plausible edge orientations using template matching. The algorithm does not require region-homogeneity, discriminative edge force, or any particular edge profile. Likewise, it makes no assumption on the imaging coils and pulse sequences used and it is robust to the patient's pose (supine, prone, etc.). The contour method was validated using expert segmentation on clinical MRI data. We recorded a mean absolute distance of 2.0 ± 0.6 mm and dice similarity coefficient of 0.93 ± 0.3 in midsection. The algorithm takes about 1 second per slice. PMID:21132083

  13. Selective Invocation of Shape Priors for Deformable Segmentation and Morphologic Classification of Prostate Cancer Tissue Microarrays

    PubMed Central

    Ali, Sahirzeeshan; Veltri, Robert; Epstein, Jonathan A.; Christudass, Christhunesa; Madabhushi, Anant

    2015-01-01

    Shape based active contours have emerged as a natural solution to overlap resolution. However, most of these shape-based methods are computationally expensive. There are instances in an image where no overlapping objects are present and applying these schemes results in significant computational overhead without any accompanying, additional benefit. In this paper we present a novel adaptive active contour scheme (AdACM) that combines boundary and region based energy terms with a shape prior in a multi level set formulation. To reduce the computational overhead, the shape prior term in the variational formulation is only invoked for those instances in the image where overlaps between objects are identified; these overlaps being identified via a contour concavity detection scheme. By not having to invoke all 3 terms (shape, boundary, region) for segmenting every object in the scene, the computational expense of the integrated active contour model is dramatically reduced, a particularly relevant consideration when multiple objects have to be segmented on very large histopathological images. The AdACM was employed for the task of segmenting nuclei on 80 prostate cancer tissue microarray images from 40 patient studies. Nuclear shape based, architectural and textural features extracted from these segmentations were extracted and found to able to discriminate different Gleason grade patterns with a classification accuracy of 86% via a quadratic discriminant analysis (QDA) classifier. On average the AdACM model provided 60% savings in computational times compared to a non-optimized hybrid active contour model involving a shape prior. PMID:25466771

  14. Efficient threshold for volumetric segmentation

    NASA Astrophysics Data System (ADS)

    Burdescu, Dumitru D.; Brezovan, Marius; Stanescu, Liana; Stoica Spahiu, Cosmin; Ebanca, Daniel

    2015-07-01

    Image segmentation plays a crucial role in effective understanding of digital images. However, the research on the existence of general purpose segmentation algorithm that suits for variety of applications is still very much active. Among the many approaches in performing image segmentation, graph based approach is gaining popularity primarily due to its ability in reflecting global image properties. Volumetric image segmentation can simply result an image partition composed by relevant regions, but the most fundamental challenge in segmentation algorithm is to precisely define the volumetric extent of some object, which may be represented by the union of multiple regions. The aim in this paper is to present a new method to detect visual objects from color volumetric images and efficient threshold. We present a unified framework for volumetric image segmentation and contour extraction that uses a virtual tree-hexagonal structure defined on the set of the image voxels. The advantage of using a virtual tree-hexagonal network superposed over the initial image voxels is that it reduces the execution time and the memory space used, without losing the initial resolution of the image.

  15. Robust contour decomposition using a constant curvature criterion

    NASA Technical Reports Server (NTRS)

    Wuescher, Daniel M.; Boyer, Kim L.

    1991-01-01

    The problem of decomposing an extended boundary or contour into simple primitives is addressed with particular emphasis on Laplacian-of-Gaussian (LoG) zero-crossing contours. A technique is introduced for partitioning such contours into constant curvature segments. A nonlinear `blip' filter matched to the impairment signature of the curvature computation process, an overlapped voting scheme, and a sequential contiguous segment extraction mechanism are used. This technique is insensitive to reasonable changes in algorithm parameters and robust to noise and minor viewpoint-induced distortions in the contour shape, such as those encountered between stereo image pairs. The results vary smoothly with the data, and local perturbations induce only local changes in the result. Robustness and insensitivity are experimentally verified.

  16. Diagnostic accuracy of ovarian cyst segmentation in B-mode ultrasound images

    NASA Astrophysics Data System (ADS)

    Bibicu, Dorin; Moraru, Luminita; Stratulat (Visan), Mirela

    2013-11-01

    Cystic and polycystic ovary syndrome is an endocrine disorder affecting women in the fertile age. The Moore Neighbor Contour, Watershed Method, Active Contour Models, and a recent method based on Active Contour Model with Selective Binary and Gaussian Filtering Regularized Level Set (ACM&SBGFRLS) techniques were used in this paper to detect the border of the ovarian cyst from echography images. In order to analyze the efficiency of the segmentation an original computer aided software application developed in MATLAB was proposed. The results of the segmentation were compared and evaluated against the reference contour manually delineated by a sonography specialist. Both the accuracy and time complexity of the segmentation tasks are investigated. The Fréchet distance (FD) as a similarity measure between two curves and the area error rate (AER) parameter as the difference between the segmented areas are used as estimators of the segmentation accuracy. In this study, the most efficient methods for the segmentation of the ovarian were analyzed cyst. The research was carried out on a set of 34 ultrasound images of the ovarian cyst.

  17. Segmentation of the brain from 3D MRI using a hierarchical active surface template

    NASA Astrophysics Data System (ADS)

    Snell, John W.; Merickel, Michael B.; Ortega, James M.; Goble, John C.; Brookeman, James R.; Kassell, Neal F.

    1994-05-01

    The accurate segmentation of the brain from three-dimensional medical imagery is important as the basis for visualization, morphometry, surgical planning and intraoperative navigation. The complex and variable nature of brain anatomy makes recognition of the brain boundaries a difficult problem and frustrates segmentation schemes based solely on local image features. We have developed a deformable surface model of the brain as a mechanism for utilizing a priori anatomical knowledge in the segmentation process. The active surface template uses an energy minimization scheme to find a globally consistent surface configuration given a set of potentially ambiguous image features. Solution of the entire 3D problem at once produces superior results to those achieved using a slice by slice approach. We have achieved good results with MR image volumes of both normal and abnormal subjects. Evaluation of the segmentation results has been performed using cadaver studies.

  18. Active appearance model and deep learning for more accurate prostate segmentation on MRI

    NASA Astrophysics Data System (ADS)

    Cheng, Ruida; Roth, Holger R.; Lu, Le; Wang, Shijun; Turkbey, Baris; Gandler, William; McCreedy, Evan S.; Agarwal, Harsh K.; Choyke, Peter; Summers, Ronald M.; McAuliffe, Matthew J.

    2016-03-01

    Prostate segmentation on 3D MR images is a challenging task due to image artifacts, large inter-patient prostate shape and texture variability, and lack of a clear prostate boundary specifically at apex and base levels. We propose a supervised machine learning model that combines atlas based Active Appearance Model (AAM) with a Deep Learning model to segment the prostate on MR images. The performance of the segmentation method is evaluated on 20 unseen MR image datasets. The proposed method combining AAM and Deep Learning achieves a mean Dice Similarity Coefficient (DSC) of 0.925 for whole 3D MR images of the prostate using axial cross-sections. The proposed model utilizes the adaptive atlas-based AAM model and Deep Learning to achieve significant segmentation accuracy.

  19. Comparing demographic, health status and psychosocial strategies of audience segmentation to promote physical activity.

    PubMed

    Boslaugh, Sarah E; Kreuter, Matthew W; Nicholson, Robert A; Naleid, Kimberly

    2005-08-01

    The goal of audience segmentation is to identify population subgroups that are homogeneous with respect to certain variables associated with a given outcome or behavior. When such groups are identified and understood, targeted intervention strategies can be developed to address their unique characteristics and needs. This study compares the results of audience segmentation for physical activity that is based on either demographic, health status or psychosocial variables alone, or a combination of all three types of variables. Participants were 1090 African-American and White adults from two public health centers in St Louis, MO. Using a classification-tree algorithm to form homogeneous groups, analyses showed that more segments with greater variability in physical activity were created using psychosocial versus health status or demographic variables and that a combination of the three outperformed any individual set of variables. Simple segmentation strategies such as those relying on demographic variables alone provided little improvement over no segmentation at all. Audience segmentation appears to yield more homogeneous subgroups when psychosocial and health status factors are combined with demographic variables.

  20. Accelerometry-Derived Physical Activity of First through Third Grade Children during the Segmented School Day

    ERIC Educational Resources Information Center

    Weaver, R. Glenn; Crimarco, Anthony; Brusseau, Timothy A.; Webster, Collin A.; Burns, Ryan D.; Hannon, James C.

    2016-01-01

    Background: Schools should provide children 30 minutes/day of moderate-to-vigorous-physical-activity (MVPA). Determining school day segments that contribute to children's MVPA can inform school-based activity promotion. The purpose of this paper was to identify the proportion of children accumulating 30 minutes/day of school-based MVPA, and to…

  1. An Investigation of the Effects of Different Types of Activities during Pauses in a Segmented Instructional Animation

    ERIC Educational Resources Information Center

    Cheon, Jongpil; Chung, Sungwon; Crooks, Steven M.; Song, Jaeki; Kim, Jeakyeong

    2014-01-01

    Since the complex and transient information in instructional animations requires more cognitive resources, the segmenting principle has been proposed to reduce cognitive overload by providing smaller chunks with pauses between segments. This study examined the effects of different types of activities during pauses in a segmented animation. Four…

  2. Complement Activation in Patients with Focal Segmental Glomerulosclerosis

    PubMed Central

    Thurman, Joshua M.; Wong, Maria; Renner, Brandon; Frazer-Abel, Ashley; Giclas, Patricia C.; Joy, Melanie S.; Jalal, Diana; Radeva, Milena K.; Gassman, Jennifer; Gipson, Debbie S.; Kaskel, Frederick; Friedman, Aaron; Trachtman, Howard

    2015-01-01

    Background Recent pre-clinical studies have shown that complement activation contributes to glomerular and tubular injury in experimental FSGS. Although complement proteins are detected in the glomeruli of some patients with FSGS, it is not known whether this is due to complement activation or whether the proteins are simply trapped in sclerotic glomeruli. We measured complement activation fragments in the plasma and urine of patients with primary FSGS to determine whether complement activation is part of the disease process. Study Design Plasma and urine samples from patients with biopsy-proven FSGS who participated in the FSGS Clinical Trial were analyzed. Setting and Participants We identified 19 patients for whom samples were available from weeks 0, 26, 52 and 78. The results for these FSGS patients were compared to results in samples from 10 healthy controls, 10 patients with chronic kidney disease (CKD), 20 patients with vasculitis, and 23 patients with lupus nephritis. Outcomes Longitudinal control of proteinuria and estimated glomerular filtration rate (eGFR). Measurements Levels of the complement fragments Ba, Bb, C4a, and sC5b-9 in plasma and urine. Results Plasma and urine Ba, C4a, sC5b-9 were significantly higher in FSGS patients at the time of diagnosis than in the control groups. Plasma Ba levels inversely correlated with the eGFR at the time of diagnosis and at the end of the study. Plasma and urine Ba levels at the end of the study positively correlated with the level of proteinuria, the primary outcome of the study. Limitations Limited number of patients with samples from all time-points. Conclusions The complement system is activated in patients with primary FSGS, and elevated levels of plasma Ba correlate with more severe disease. Measurement of complement fragments may identify a subset of patients in whom the complement system is activated. Further investigations are needed to confirm our findings and to determine the prognostic significance of

  3. 3D active surfaces for liver segmentation in multisequence MRI images.

    PubMed

    Bereciartua, Arantza; Picon, Artzai; Galdran, Adrian; Iriondo, Pedro

    2016-08-01

    Biopsies for diagnosis can sometimes be replaced by non-invasive techniques such as CT and MRI. Surgeons require accurate and efficient methods that allow proper segmentation of the organs in order to ensure the most reliable intervention planning. Automated liver segmentation is a difficult and open problem where CT has been more widely explored than MRI. MRI liver segmentation represents a challenge due to the presence of characteristic artifacts, such as partial volumes, noise and low contrast. In this paper, we present a novel method for multichannel MRI automatic liver segmentation. The proposed method consists of the minimization of a 3D active surface by means of the dual approach to the variational formulation of the underlying problem. This active surface evolves over a probability map that is based on a new compact descriptor comprising spatial and multisequence information which is further modeled by means of a liver statistical model. This proposed 3D active surface approach naturally integrates volumetric regularization in the statistical model. The advantages of the compact visual descriptor together with the proposed approach result in a fast and accurate 3D segmentation method. The method was tested on 18 healthy liver studies and results were compared to a gold standard made by expert radiologists. Comparisons with other state-of-the-art approaches are provided by means of nine well established quality metrics. The obtained results improve these methodologies, achieving a Dice Similarity Coefficient of 98.59. PMID:27282235

  4. Research on adaptive segmentation and activity classification method of filamentous fungi image in microbe fermentation

    NASA Astrophysics Data System (ADS)

    Cai, Xiaochun; Hu, Yihua; Wang, Peng; Sun, Dujuan; Hu, Guilan

    2009-10-01

    The paper presents an adaptive segmentation and activity classification method for filamentous fungi image. Firstly, an adaptive structuring element (SE) construction algorithm is proposed for image background suppression. Based on watershed transform method, the color labeled segmentation of fungi image is taken. Secondly, the fungi elements feature space is described and the feature set for fungi hyphae activity classification is extracted. The growth rate evaluation of fungi hyphae is achieved by using SVM classifier. Some experimental results demonstrate that the proposed method is effective for filamentous fungi image processing.

  5. The Development of Contour Interpolation: Evidence from Subjective Contours

    ERIC Educational Resources Information Center

    Hadad, Bat-Sheva; Maurer, Daphne; Lewis, Terri L.

    2010-01-01

    Adults are skilled at perceiving subjective contours in regions without any local image information (e.g., [Ginsburg, 1975] and [Kanizsa, 1976]). Here we examined the development of this skill and the effect thereon of the support ratio (i.e., the ratio of the physically specified contours to the total contour length). Children (6-, 9-, and…

  6. Neurotensin Changes Propulsive Activity into a Segmental Motor Pattern in the Rat Colon

    PubMed Central

    Li, Hongfei; Chen, Ji-Hong; Yang, Zixian; Huang, Min; Yu, Yuanjie; Tan, Shiyun; Luo, Hesheng; Huizinga, Jan D

    2016-01-01

    Background/Aims Neurotensin is a gut-brain peptide with both inhibitory and excitatory actions on the colonic musculature; our objective was to understand the implications of this for motor patterns occurring in the intact colon of the rat. Methods The effects of neurotensin with concentrations ranging from 0.1–100 nM were studied in the intact rat colon in vitro, by investigating spatio-temporal maps created from video recordings of colonic motility before and after neurotensin. Results Low concentration of neurotensin (0.1–1 nM) inhibited propagating long distance contractions and rhythmic propagating motor complexes; in its place a slow propagating rhythmic segmental motor pattern developed. The neurotensin receptor 1 antagonist SR-48692 prevented the development of the segmental motor pattern. Higher concentrations of neurotensin (10 nM and 100 nM) were capable of restoring long distance contraction activity and inhibiting the segmental activity. The slow propagating segmental contraction showed a rhythmic contraction—relaxation cycle at the slow wave frequency originating from the interstitial cells of Cajal associated with the myenteric plexus pacemaker. High concentrations given without prior additions of low concentrations did not evoke the segmental motor pattern. These actions occurred when neurotensin was given in the bath solution or intraluminally. The segmental motor pattern evoked by neurotensin was inhibited by the neural conduction blocker lidocaine. Conclusions Neurotensin (0.1–1 nM) inhibits the dominant propulsive motor patterns of the colon and a distinct motor pattern of rhythmic slow propagating segmental contractions develops. This motor pattern has the hallmarks of haustral boundary contractions. PMID:26882114

  7. Enzyme catalysis in an aqueous/organic segment flow microreactor: ways to stabilize enzyme activity.

    PubMed

    Karande, Rohan; Schmid, Andreas; Buehler, Katja

    2010-06-01

    Multiphase flow microreactors benefit from rapid mixing and high mass transfer rates, yet their application in enzymatic catalysis is limited due to the fast inactivation of enzymes used as biocatalysts. Enzyme inactivation during segment flow is due to the large interfacial area between aqueous and organic phases. The Peclet number of the system points to strong convective forces within the segments, and this results in rapid deactivation of the enzyme depending on segment length and flow rate. Addition of surfactant to the aqueous phase or enzyme immobilization prevents the biocatalyst from direct contact with the interface and thus stabilizes the enzyme activity. Almost 100% enzyme activity can be recovered compared to 45% without any enzyme or medium modification. Drop tensiometry measurements point to a mixed enzyme-surfactant interfacial adsorption, and above a certain concentration, the surfactant forms a protective layer between the interface and the biocatalyst in the aqueous compartments. Theoretical models were used to compare adsorption kinetics of the protein to the interface in the segment flow microreactor and in the drop tensiometry measurements. This study is the basis for the development of segment flow microreactors as a tool to perform productive enzymatic catalysis. PMID:20201570

  8. The activation of segmental and tonal information in visual word recognition.

    PubMed

    Li, Chuchu; Lin, Candise Y; Wang, Min; Jiang, Nan

    2013-08-01

    Mandarin Chinese has a logographic script in which graphemes map onto syllables and morphemes. It is not clear whether Chinese readers activate phonological information during lexical access, although phonological information is not explicitly represented in Chinese orthography. In the present study, we examined the activation of phonological information, including segmental and tonal information in Chinese visual word recognition, using the Stroop paradigm. Native Mandarin speakers named the presentation color of Chinese characters in Mandarin. The visual stimuli were divided into five types: color characters (e.g., , hong2, "red"), homophones of the color characters (S+T+; e.g., , hong2, "flood"), different-tone homophones (S+T-; e.g., , hong1, "boom"), characters that shared the same tone but differed in segments with the color characters (S-T+; e.g., , ping2, "bottle"), and neutral characters (S-T-; e.g., , qian1, "leading through"). Classic Stroop facilitation was shown in all color-congruent trials, and interference was shown in the incongruent trials. Furthermore, the Stroop effect was stronger for S+T- than for S-T+ trials, and was similar between S+T+ and S+T- trials. These findings suggested that both tonal and segmental forms of information play roles in lexical constraints; however, segmental information has more weight than tonal information. We proposed a revised visual word recognition model in which the functions of both segmental and suprasegmental types of information and their relative weights are taken into account. PMID:23400856

  9. Accurate vessel segmentation with constrained B-snake.

    PubMed

    Yuanzhi Cheng; Xin Hu; Ji Wang; Yadong Wang; Tamura, Shinichi

    2015-08-01

    We describe an active contour framework with accurate shape and size constraints on the vessel cross-sectional planes to produce the vessel segmentation. It starts with a multiscale vessel axis tracing in a 3D computed tomography (CT) data, followed by vessel boundary delineation on the cross-sectional planes derived from the extracted axis. The vessel boundary surface is deformed under constrained movements on the cross sections and is voxelized to produce the final vascular segmentation. The novelty of this paper lies in the accurate contour point detection of thin vessels based on the CT scanning model, in the efficient implementation of missing contour points in the problematic regions and in the active contour model with accurate shape and size constraints. The main advantage of our framework is that it avoids disconnected and incomplete segmentation of the vessels in the problematic regions that contain touching vessels (vessels in close proximity to each other), diseased portions (pathologic structure attached to a vessel), and thin vessels. It is particularly suitable for accurate segmentation of thin and low contrast vessels. Our method is evaluated and demonstrated on CT data sets from our partner site, and its results are compared with three related methods. Our method is also tested on two publicly available databases and its results are compared with the recently published method. The applicability of the proposed method to some challenging clinical problems, the segmentation of the vessels in the problematic regions, is demonstrated with good results on both quantitative and qualitative experimentations; our segmentation algorithm can delineate vessel boundaries that have level of variability similar to those obtained manually.

  10. Brain aneurysm segmentation in CTA and 3DRA using geodesic active regions based on second order prototype features and nonparametric density estimation

    NASA Astrophysics Data System (ADS)

    Hernandez, Monica; Frangi, Alejandro F.

    2005-04-01

    Coupling the geodesic active contours model with statistical information based on regions introduces robustness in the segmentation of images with weak or inhomogeneous gradients. In the estimation of the probability density function for each region take part the definition of the features that describe the image inside the different regions and the method of density estimation itself. A Gaussian Mixture Model is frequently proposed for density estimation. This approach is based on the assumption that the intensity distribution of the image is the most discriminant feature in a region. However, the use of second order features provides a better discrimination of the different regions, as these features represent more accurately the local properties of the image manifold. Due to the high dimensionality of the problem, the use of non parametric density estimation methods becomes necessary. In this article, we present a novel method of introducing the second order information of an image for non parametric estimation of the probability density functions of the different tissues that are present in medical images. The novelty of the method stems on the use of the response of the image under an orthogonal harmonic operator set projected onto a prototype space for feature generation. The technique described here is applied to the segmentation of brain aneurysms in Computed Tomography Angiography (CTA) and 3D Rotational Angiography (3DRA) showing a qualitative improvement from the Gaussian Mixture Model approach.

  11. Population responses to contour integration: early encoding of discrete elements and late perceptual grouping.

    PubMed

    Gilad, Ariel; Meirovithz, Elhanan; Slovin, Hamutal

    2013-04-24

    The neuronal mechanisms underlying perceptual grouping of discrete, similarly oriented elements are not well understood. To investigate this, we measured neural population responses using voltage-sensitive dye imaging in V1 of monkeys trained on a contour-detection task. By mapping the contour and background elements onto V1, we could study their neural processing. Population response early in time showed activation patches corresponding to the contour/background individual elements. However, late increased activity in the contour elements, along with suppressed activity in the background elements, enabled us to visualize in single trials a salient continuous contour "popping out" from a suppressed background. This modulated activity in the contour and in background extended beyond the cortical representation of individual contour or background elements. Finally, the late modulation was correlated with behavioral performance of contour saliency and the monkeys' perceptual report. Thus, opposing responses in the contour and background may underlie perceptual grouping in V1.

  12. Knee cartilage segmentation using active shape models and local binary patterns

    NASA Astrophysics Data System (ADS)

    González, Germán.; Escalante-Ramírez, Boris

    2014-05-01

    Segmentation of knee cartilage has been useful for opportune diagnosis and treatment of osteoarthritis (OA). This paper presents a semiautomatic segmentation technique based on Active Shape Models (ASM) combined with Local Binary Patterns (LBP) and its approaches to describe the surrounding texture of femoral cartilage. The proposed technique is tested on a 16-image database of different patients and it is validated through Leave- One-Out method. We compare different segmentation techniques: ASM-LBP, ASM-medianLBP, and ASM proposed by Cootes. The ASM-LBP approaches are tested with different ratios to decide which of them describes the cartilage texture better. The results show that ASM-medianLBP has better performance than ASM-LBP and ASM. Furthermore, we add a routine which improves the robustness versus two principal problems: oversegmentation and initialization.

  13. Numerosity underestimation in sets with illusory contours.

    PubMed

    Kirjakovski, Atanas; Matsumoto, Eriko

    2016-05-01

    People underestimate the numerosity of collections in which a few dots are connected in pairs by task-irrelevant lines. Such configural processing suggests that visual numerosity depends on the perceived scene segments, rather than on the perceived total area occupied by a collection. However, a methodology that uses irrelevant line connections may also introduce unnecessary distraction and variety, or obscure the perception of task-relevant items, given the saliency of the lines. To avoid such potentially confounding variables, we conducted four experiments where the line-connected dots were replaced with collinear inducers of Kanizsa-type illusory contours. Our participants had to compare two simultaneously presented collections and choose the more numerous one. Displays comprised c-shaped inducers and disks (Experiment 1), c-shaped inducers only (Experiments 2 and 4), or closed inducers (Experiment 3). One display always showed a 12- (Experiments 1-3) or 48-item reference pattern (Experiment 4); the other was a test pattern with numerosity varying between 9 and 15 (Experiments 1-3) or 36-60 items (Experiment 4). By manipulating the number of illusory contours in the test patterns, the level of connectedness increased or decreased respectively. The fitted psychometric functions revealed an underestimation that increased with the number of illusory contours in Experiments 1 and 2, but was absent in Experiments 3 and 4, where illusory contours were more difficult to perceive or larger numerosities were used. Results corroborate claims that visual numerosity estimation depends on segmented inputs, but only within moderate numerical ranges. PMID:27038561

  14. Packaged Fault Model for Geometric Segmentation of Active Faults Into Earthquake Source Faults

    NASA Astrophysics Data System (ADS)

    Nakata, T.; Kumamoto, T.

    2004-12-01

    In Japan, the empirical formula proposed by Matsuda (1975) mainly based on the length of the historical surface fault ruptures and magnitude, is generally applied to estimate the size of future earthquakes from the extent of existing active faults for seismic hazard assessment. Therefore validity of the active fault length and defining individual segment boundaries where propagating ruptures terminate are essential and crucial to the reliability for the accurate assessments. It is, however, not likely for us to clearly identify the behavioral earthquake segments from observation of surface faulting during the historical period, because most of the active faults have longer recurrence intervals than 1000 years in Japan. Besides uncertainties of the datasets obtained mainly from fault trenching studies are quite large for fault grouping/segmentation. This is why new methods or criteria should be applied for active fault grouping/segmentation, and one of the candidates may be geometric criterion of active faults. Matsuda (1990) used _gfive kilometer_h as a critical distance for grouping and separation of neighboring active faults. On the other hand, Nakata and Goto (1998) proposed the geometric criteria such as (1) branching features of active fault traces and (2) characteristic pattern of vertical-slip distribution along the fault traces as tools to predict rupture length of future earthquakes. The branching during the fault rupture propagation is regarded as an effective energy dissipation process and could result in final rupture termination. With respect to the characteristic pattern of vertical-slip distribution, especially with strike-slip components, the up-thrown sides along the faults are, in general, located on the fault blocks in the direction of relative strike-slip. Applying these new geometric criteria to the high-resolution active fault distribution maps, the fault grouping/segmentation could be more practically conducted. We tested this model

  15. An improved level set method for vertebra CT image segmentation

    PubMed Central

    2013-01-01

    Background Clinical diagnosis and therapy for the lumbar disc herniation requires accurate vertebra segmentation. The complex anatomical structure and the degenerative deformations of the vertebrae makes its segmentation challenging. Methods An improved level set method, namely edge- and region-based level set method (ERBLS), is proposed for vertebra CT images segmentation. By considering the gradient information and local region characteristics of images, the proposed model can efficiently segment images with intensity inhomogeneity and blurry or discontinuous boundaries. To reduce the dependency on manual initialization in many active contour models and for an automatic segmentation, a simple initialization method for the level set function is built, which utilizes the Otsu threshold. In addition, the need of the costly re-initialization procedure is completely eliminated. Results Experimental results on both synthetic and real images demonstrated that the proposed ERBLS model is very robust and efficient. Compared with the well-known local binary fitting (LBF) model, our method is much more computationally efficient and much less sensitive to the initial contour. The proposed method has also applied to 56 patient data sets and produced very promising results. Conclusions An improved level set method suitable for vertebra CT images segmentation is proposed. It has the flexibility of segmenting the vertebra CT images with blurry or discontinuous edges, internal inhomogeneity and no need of re-initialization. PMID:23714300

  16. Assessment of the relationship between lesion segmentation accuracy and computer-aided diagnosis scheme performance

    NASA Astrophysics Data System (ADS)

    Zheng, Bin; Pu, Jiantao; Park, Sang Cheol; Zuley, Margarita; Gur, David

    2008-03-01

    In this study we randomly select 250 malignant and 250 benign mass regions as a training dataset. The boundary contours of these regions were manually identified and marked. Twelve image features were computed for each region. An artificial neural network (ANN) was trained as a classifier. To select a specific testing dataset, we applied a topographic multi-layer region growth algorithm to detect boundary contours of 1,903 mass regions in an initial pool of testing regions. All processed regions are sorted based on a size difference ratio between manual and automated segmentation. We selected a testing dataset involving 250 malignant and 250 benign mass regions with larger size difference ratios. Using the area under ROC curve (A Z value) as performance index we investigated the relationship between the accuracy of mass segmentation and the performance of a computer-aided diagnosis (CAD) scheme. CAD performance degrades as the size difference ratio increases. Then, we developed and tested a hybrid region growth algorithm that combined the topographic region growth with an active contour approach. In this hybrid algorithm, the boundary contour detected by the topographic region growth is used as the initial contour of the active contour algorithm. The algorithm iteratively searches for the optimal region boundaries. A CAD likelihood score of the growth region being a true-positive mass is computed in each iteration. The region growth is automatically terminated once the first maximum CAD score is reached. This hybrid region growth algorithm reduces the size difference ratios between two areas segmented automatically and manually to less than +/-15% for all testing regions and the testing A Z value increases to from 0.63 to 0.90. The results indicate that CAD performance heavily depends on the accuracy of mass segmentation. In order to achieve robust CAD performance, reducing lesion segmentation error is important.

  17. A double-panel active segmented partition module using decoupled analog feedback controllers: numerical model.

    PubMed

    Sagers, Jason D; Leishman, Timothy W; Blotter, Jonathan D

    2009-06-01

    Low-frequency sound transmission has long plagued the sound isolation performance of lightweight partitions. Over the past 2 decades, researchers have investigated actively controlled structures to prevent sound transmission from a source space into a receiving space. An approach using active segmented partitions (ASPs) seeks to improve low-frequency sound isolation capabilities. An ASP is a partition which has been mechanically and acoustically segmented into a number of small individually controlled modules. This paper provides a theoretical and numerical development of a single ASP module configuration, wherein each panel of the double-panel structure is independently actuated and controlled by an analog feedback controller. A numerical model is developed to estimate frequency response functions for the purpose of controller design, to understand the effects of acoustic coupling between the panels, to predict the transmission loss of the module in both passive and active states, and to demonstrate that the proposed ASP module will produce bidirectional sound isolation.

  18. Multi-scale texture-based level-set segmentation of breast B-mode images.

    PubMed

    Lang, Itai; Sklair-Levy, Miri; Spitzer, Hedva

    2016-05-01

    Automatic segmentation of ultrasonographic breast lesions is very challenging, due to the lesions' spiculated nature and the variance in shape and texture of the B-mode ultrasound images. Many studies have tried to answer this challenge by applying a variety of computational methods including: Markov random field, artificial neural networks, and active contours and level-set techniques. These studies focused on creating an automatic contour, with maximal resemblance to a manual contour, delineated by a trained radiologist. In this study, we have developed an algorithm, designed to capture the spiculated boundary of the lesion by using the properties from the corresponding ultrasonic image. This is primarily achieved through a unique multi-scale texture identifier (inspired by visual system models) integrated in a level-set framework. The algorithm׳s performance has been evaluated quantitatively via contour-based and region-based error metrics. We compared the algorithm-generated contour to a manual contour delineated by an expert radiologist. In addition, we suggest here a new method for performance evaluation where corrections made by the radiologist replace the algorithm-generated (original) result in the correction zones. The resulting corrected contour is then compared to the original version. The evaluation showed: (1) Mean absolute error of 0.5 pixels between the original and the corrected contour; (2) Overlapping area of 99.2% between the lesion regions, obtained by the algorithm and the corrected contour. These results are significantly better than those previously reported. In addition, we have examined the potential of our segmentation results to contribute to the discrimination between malignant and benign lesions. PMID:27010737

  19. The role of eye movements in a contour detection task.

    PubMed

    Van Humbeeck, Nathalie; Schmitt, Nadine; Hermens, Frouke; Wagemans, Johan; Ernst, Udo A

    2013-12-04

    Vision combines local feature integration with active viewing processes, such as eye movements, to perceive complex visual scenes. However, it is still unclear how these processes interact and support each other. Here, we investigated how the dynamics of saccadic eye movements interact with contour integration, focusing on situations in which contours are difficult to find or even absent. We recorded observers' eye movements while they searched for a contour embedded in a background of randomly oriented elements. Task difficulty was manipulated by varying the contour's path angle. An association field model of contour integration was employed to predict potential saccade targets by identifying stimulus locations with high contour salience. We found that the number and duration of fixations increased with the increasing path angle of the contour. In addition, fixation duration increased over the course of a trial, and the time course of saccade amplitude depended on the percept of observers. Model fitting revealed that saccades fully compensate for the reduced saliency of peripheral contour targets. Importantly, our model predicted fixation locations to a considerable degree, indicating that observers fixated collinear elements. These results show that contour integration actively guides eye movements and determines their spatial and temporal parameters.

  20. Model-driven, probabilistic level set based segmentation of magnetic resonance images of the brain.

    PubMed

    Verma, Nishant; Muralidhar, Gautam S; Bovik, Alan C; Cowperthwaite, Matthew C; Markey, Mia K

    2011-01-01

    Accurate segmentation of magnetic resonance (MR) images of the brain to differentiate features such as soft tissue, tumor, edema and necrosis is critical for both diagnosis and treatment purposes. Region-based formulations of geometric active contour models are popular choices for segmentation of MR and other medical images. Most of the traditional region-based formulations model local region intensity by assuming a piecewise constant approximation. However, the piecewise constant approximation rarely holds true for medical images such as MR images due to the presence of noise and bias field, which invariably results in a poor segmentation of the image. To overcome this problem, we have developed a probabilistic region-based active contour model for automatic segmentation of MR images of the brain. In our approach, a mixture of Gaussian distributions is used to accurately model the arbitrarily shaped local region intensity distribution. Prior spatial information derived from probabilistic atlases is also integrated into the level set evolution framework for guiding the segmentation process. Our experiments with a series of publicly available brain MR images show that the proposed active contour model gives stable and accurate segmentation results when compared to the traditional region based formulations. PMID:22254928

  1. Local adaptive approach toward segmentation of microscopic images of activated sludge flocs

    NASA Astrophysics Data System (ADS)

    Khan, Muhammad Burhan; Nisar, Humaira; Ng, Choon Aun; Lo, Po Kim; Yap, Vooi Voon

    2015-11-01

    Activated sludge process is a widely used method to treat domestic and industrial effluents. The conditions of activated sludge wastewater treatment plant (AS-WWTP) are related to the morphological properties of flocs (microbial aggregates) and filaments, and are required to be monitored for normal operation of the plant. Image processing and analysis is a potential time-efficient monitoring tool for AS-WWTPs. Local adaptive segmentation algorithms are proposed for bright-field microscopic images of activated sludge flocs. Two basic modules are suggested for Otsu thresholding-based local adaptive algorithms with irregular illumination compensation. The performance of the algorithms has been compared with state-of-the-art local adaptive algorithms of Sauvola, Bradley, Feng, and c-mean. The comparisons are done using a number of region- and nonregion-based metrics at different microscopic magnifications and quantification of flocs. The performance metrics show that the proposed algorithms performed better and, in some cases, were comparable to the state-of the-art algorithms. The performance metrics were also assessed subjectively for their suitability for segmentations of activated sludge images. The region-based metrics such as false negative ratio, sensitivity, and negative predictive value gave inconsistent results as compared to other segmentation assessment metrics.

  2. An optical approach to validate ultrasound surface segmentation of the heart

    NASA Astrophysics Data System (ADS)

    Wang, Bo; Schlaefer, Alexander; Zhang, Zhenxi

    2014-09-01

    The patient specific geometry of the heart is of interest for a number of diagnostic methods, e.g., when modeling the inverse electrocardiography (ECG) problem. One approach to get images of the heart is three-dimensional ultrasound. However, segmentation of the surface is complicated and segmentation methods are typically validated against manually drawn contours. This requires considerable expert knowledge. Hence, we have developed a setup that allows studying the accuracy of image segmentation from cardiac ultrasound. Using an optical tracking system, we have measured the three-dimensional surface of an isolated porcine heart. We studied whether the actual geometry can be reconstructed from both optical and ultrasound images. We illustrate the use of our approach in quantifying the segmentation result for a three-dimensional region-based active contour algorithm.

  3. Segmentation of hand radiographs by using multi-level connected active appearance models

    NASA Astrophysics Data System (ADS)

    Kauffman, Joost A.; Slump, Cornelis H.; Bernelot Moens, Hein J.

    2005-04-01

    Robust and accurate segmentation methods are important for the computerized evaluation of medical images. For treatment of rheumatoid arthritis, joint damage assessment in radiographs of hands is frequently used for monitoring disease progression. Current clinical scoring methods are based on visual measurements that are time-consuming and subject to intra and inter-reader variance. A solution may be found in the development of partially automated assessment procedures. This requires reliable segmentation algorithms. Our work demonstrates a segmentation method based on multiple connected active appearance models (AAM) with multiple search steps using different quality levels. The quality level can be regulated by setting the image resolution and the number of landmarks in the AAMs. We performed experiments using two models of different quality levels for shape and texture information. Both models included AAMs for the carpal region, the metacarpals, and all phalanges. By starting an iterative search with the faster, low-quality model, we were able to determine the initial parameters of the second, high-quality model. After the second search, the results showed successful segmentation for 22 of 30 test images. For these images, 70% of the landmarks were found within 1.3 mm difference from manual placement by an expert. The multi-level search approach resulted in a reduction of 50% in calculation time compared to a search using a single model. Results are expected to improve when the model is refined by increasing the number of training examples and the resolution of the models.

  4. Method for contour extraction for object representation

    DOEpatents

    Skourikhine, Alexei N.; Prasad, Lakshman

    2005-08-30

    Contours are extracted for representing a pixelated object in a background pixel field. An object pixel is located that is the start of a new contour for the object and identifying that pixel as the first pixel of the new contour. A first contour point is then located on the mid-point of a transition edge of the first pixel. A tracing direction from the first contour point is determined for tracing the new contour. Contour points on mid-points of pixel transition edges are sequentially located along the tracing direction until the first contour point is again encountered to complete tracing the new contour. The new contour is then added to a list of extracted contours that represent the object. The contour extraction process associates regions and contours by labeling all the contours belonging to the same object with the same label.

  5. Control of the segmentation process by graded MAPK/ERK activation in the chick embryo.

    PubMed

    Delfini, Marie-Claire; Dubrulle, Julien; Malapert, Pascale; Chal, Jérome; Pourquié, Olivier

    2005-08-01

    The regular spacing of somites during vertebrate embryogenesis involves a dynamic gradient of FGF signaling that controls the timing of maturation of cells in the presomitic mesoderm (PSM). How the FGF signal is transduced by PSM cells is unclear. Here, we first show that the FGF gradient is translated into graded activation of the extracellular signal-regulated kinase (ERK)/mitogen-activated protein kinase (MAPK) pathway along the PSM in the chicken embryo. Using in ovo electroporation of PSM cells, we demonstrate that constitutive activation of ERK signaling in the PSM blocks segmentation by preventing maturation of PSM cells, thus phenocopying the overexpression of FGF8. Conversely, inhibition of ERK phosphorylation mimics a loss of function of FGF signaling in the PSM. Interestingly, video microscopy analysis of cell movements shows that ERK regulates the motility of PSM cells, suggesting that the decrease of cell movements along the PSM enables mesenchymal PSM cells to undergo proper segmentation. Together, our data demonstrate that ERK is the effector of the gradient of FGF in the PSM that controls the segmentation process.

  6. Influence of the hinge region on complement activation, C1q binding, and segmental flexibility in chimeric human immunoglobulins.

    PubMed Central

    Tan, L K; Shopes, R J; Oi, V T; Morrison, S L

    1990-01-01

    We have characterized a series of genetically engineered chimeric human IgG3 and IgG4 anti-dansyl (DNS) antibodies with identical antibody-combining sites but different hinge region amino acid compositions to determine how the hinge region influences Fab fragment segmental flexibility, C1q binding, and complement activation. Our data support the correlation between "upper hinge" length and Fab segmental flexibility; moreover, we confirm that a hinge region is essential for C1q binding and complement activation. However, the hinge length by itself is not sufficient for complement activity in IgG molecules. We have demonstrated that the IgG4 hinge, which imparts restricted segmental flexibility, reduces the ability of IgG3 molecules to activate complement. We also find that the IgG3 hinge region, which imparts greater segmental motion, is not sufficient to create complement activation activity in IgG4 anti-DNS antibodies. Finally, we conclude that (i) segmental motion is correlated with "upper hinge" length, (ii) hinge length and segmental flexibility is not enough to alter complement binding and activation, and (iii) segmental flexibility does not correlate with proficiency to activate the complement cascade. PMID:2296577

  7. Segmentation of the common carotid artery with active shape models from 3D ultrasound images

    NASA Astrophysics Data System (ADS)

    Yang, Xin; Jin, Jiaoying; He, Wanji; Yuchi, Ming; Ding, Mingyue

    2012-03-01

    Carotid atherosclerosis is a major cause of stroke, a leading cause of death and disability. In this paper, we develop and evaluate a new segmentation method for outlining both lumen and adventitia (inner and outer walls) of common carotid artery (CCA) from three-dimensional ultrasound (3D US) images for carotid atherosclerosis diagnosis and evaluation. The data set consists of sixty-eight, 17× 2× 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80mg atorvastain and nine with placebo), who had carotid stenosis of 60% or more, at baseline and after three months of treatment. We investigate the use of Active Shape Models (ASMs) to segment CCA inner and outer walls after statin therapy. The proposed method was evaluated with respect to expert manually outlined boundaries as a surrogate for ground truth. For the lumen and adventitia segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC) of 93.6%+/- 2.6%, 91.8%+/- 3.5%, mean absolute distances (MAD) of 0.28+/- 0.17mm and 0.34 +/- 0.19mm, maximum absolute distances (MAXD) of 0.87 +/- 0.37mm and 0.74 +/- 0.49mm. The proposed algorithm took 4.4 +/- 0.6min to segment a single 3D US images, compared to 11.7+/-1.2min for manual segmentation. Therefore, the method would promote the translation of carotid 3D US to clinical care for the fast, safety and economical monitoring of the atherosclerotic disease progression and regression during therapy.

  8. Segmentation of common carotid artery with active appearance models from ultrasound images

    NASA Astrophysics Data System (ADS)

    Yang, Xin; He, Wanji; Fenster, Aaron; Yuchi, Ming; Ding, Mingyue

    2013-02-01

    Carotid atherosclerosis is a major cause of stroke, a leading cause of death and disability. In this paper, a new segmentation method is proposed and evaluated for outlining the common carotid artery (CCA) from transverse view images, which were sliced from three-dimensional ultrasound (3D US) of 1mm inter-slice distance (ISD), to support the monitoring and assessment of carotid atherosclerosis. The data set consists of forty-eight 3D US images acquired from both left and right carotid arteries of twelve patients in two time points who had carotid stenosis of 60% or more at the baseline. The 3D US data were collected at baseline and three-month follow-up, where seven treated with 80mg atorvastatin and five with placebo. The baseline manual boundaries were used for Active Appearance Models (AAM) training; while the treatment data for segmentation testing and evaluation. The segmentation results were compared with experts manually outlined boundaries, as a surrogate for ground truth, for further evaluation. For the adventitia and lumen segmentations, the algorithm yielded Dice Coefficients (DC) of 92.06%+/-2.73% and 89.67%+/-3.66%, mean absolute distances (MAD) of 0.28+/-0.18 mm and 0.22+/-0.16 mm, maximum absolute distances (MAXD) of 0.71+/-0.28 mm and 0.59+/-0.21 mm, respectively. The segmentation results were also evaluated via Pratt's figure of merit (FOM) with the value of 0.61+/-0.06 and 0.66+/-0.05, which provides a quantitative measure for judging the similarity. Experimental results indicate that the proposed method can promote the carotid 3D US usage for a fast, safe and economical monitoring of the atherosclerotic disease progression and regression during therapy.

  9. Medical image segmentation by combining graph cuts and oriented active appearance models.

    PubMed

    Chen, Xinjian; Udupa, Jayaram K; Bagci, Ulas; Zhuge, Ying; Yao, Jianhua

    2012-04-01

    In this paper, we propose a novel method based on a strategic combination of the active appearance model (AAM), live wire (LW), and graph cuts (GCs) for abdominal 3-D organ segmentation. The proposed method consists of three main parts: model building, object recognition, and delineation. In the model building part, we construct the AAM and train the LW cost function and GC parameters. In the recognition part, a novel algorithm is proposed for improving the conventional AAM matching method, which effectively combines the AAM and LW methods, resulting in the oriented AAM (OAAM). A multiobject strategy is utilized to help in object initialization. We employ a pseudo-3-D initialization strategy and segment the organs slice by slice via a multiobject OAAM method. For the object delineation part, a 3-D shape-constrained GC method is proposed. The object shape generated from the initialization step is integrated into the GC cost computation, and an iterative GC-OAAM method is used for object delineation. The proposed method was tested in segmenting the liver, kidneys, and spleen on a clinical CT data set and also on the MICCAI 2007 Grand Challenge liver data set. The results show the following: 1) The overall segmentation accuracy of true positive volume fraction TPVF > 94.3% and false positive volume fraction can be achieved; 2) the initialization performance can be improved by combining the AAM and LW; 3) the multiobject strategy greatly facilitates initialization; 4) compared with the traditional 3-D AAM method, the pseudo-3-D OAAM method achieves comparable performance while running 12 times faster; and 5) the performance of the proposed method is comparable to state-of-the-art liver segmentation algorithm. The executable version of the 3-D shape-constrained GC method with a user interface can be downloaded from http://xinjianchen.wordpress.com/research/. PMID:22311862

  10. Active-source seismic imaging below Lake Malawi (Nyasa) from the SEGMeNT project

    NASA Astrophysics Data System (ADS)

    Shillington, D. J.; Scholz, C. A.; Gaherty, J. B.; Accardo, N. J.; McCartney, T.; Chindandali, P. R. N.; Kamihanda, G.; Trinhammer, P.; Wood, D. A.; Khalfan, M.; Ebinger, C. J.; Nyblade, A.; Mbogoni, G. J.; Mruma, A. H.; Salima, J.; Ferdinand-Wambura, R.

    2015-12-01

    Little is known about the controls on the initiation and development of magmatism and segmentation in young rift systems. The northern Lake Malawi (Nyasa) rift in the East African Rift System is an early stage rift exhibiting pronounced tectonic segmentation, which is defined in the upper crust by ~100-km-long border faults. Very little volcanism is associated with rifting; the only surface expression of magmatism occurs in an accommodation zone between segments to the north of the lake in the Rungwe Volcanic Province. The SEGMeNT (Study of Extension and maGmatism in Malawi aNd Tanzania) project is a multidisciplinary, multinational study that is acquiring a suite of geophysical, geological and geochemical data to characterize deformation and magmatism in the crust and mantle lithosphere along 2-3 segments of this rift. As a part of the SEGMeNT project, we acquired seismic reflection and refraction data in Lake Malawi (Nyasa) in March-April 2015. Over 2000 km of seismic reflection data were acquired with a 500 to 2580 cu in air gun array from GEUS/Aarhus and a 500- to 1500-m-long seismic streamer from Syracuse University over a grid of lines across and along the northern and central basins. Air gun shots from MCS profiles and 1000 km of additional shooting with large shot intervals were also recorded on 27 short-period and 6 broadband lake bottom seismometers from Scripps Oceanographic Institute as a part of the Ocean Bottom Seismic Instrument Pool (OBSIP) as well as the 55-station onshore seismic array. The OBS were deployed along one long strike line and two dip lines. We will present preliminary data and results from seismic reflection and refraction data acquired in the lake and their implications for crustal deformation within and between rift segments. Seismic reflection data image structures up to ~5-6 km below the lake bottom, including syntectonic sediments, intrabasinal faults and other complex horsts. Some intrabasinal faults in both the northern and

  11. Precision contour gage

    DOEpatents

    Bieg, L.F.

    1990-12-11

    An apparatus for gaging the contour of a machined part includes a rotary slide assembly, a kinematic mount to move the apparatus into and out of position for measuring the part while the part is still on the machining apparatus, a linear probe assembly with a suspension arm and a probe assembly including as probe tip for providing a measure of linear displacement of the tip on the surface of the part, a means for changing relative positions between the part and the probe tip, and a means for recording data points representing linear positions of the probe tip at prescribed rotation intervals in the position changes between the part and the probe tip. 5 figs.

  12. Precision contour gage

    DOEpatents

    Bieg, Lothar F.

    1990-12-11

    An apparatus for gaging the contour of a machined part includes a rotary slide assembly, a kinematic mount to move the apparatus into and out of position for measuring the part while the part is still on the machining apparatus, a linear probe assembly with a suspension arm and a probe assembly including as probe tip for providing a measure of linear displacement of the tip on the surface of the part, a means for changing relative positions between the part and the probe tip, and a means for recording data points representing linear positions of the probe tip at prescribed rotation intervals in the position changes between the part and the probe tip.

  13. A hybrid framework of multiple active appearance models and global registration for 3D prostate segmentation in MRI

    NASA Astrophysics Data System (ADS)

    Ghose, Soumya; Oliver, Arnau; Martí, Robert; Lladó, Xavier; Freixenet, Jordi; Mitra, Jhimli; Vilanova, Joan C.; Meriaudeau, Fabrice

    2012-02-01

    Real-time fusion of Magnetic Resonance (MR) and Trans Rectal Ultra Sound (TRUS) images aid in the localization of malignant tissues in TRUS guided prostate biopsy. Registration performed on segmented contours of the prostate reduces computational complexity and improves the multimodal registration accuracy. However, accurate and computationally efficient 3D segmentation of the prostate in MR images could be a challenging task due to inter-patient shape and intensity variability of the prostate gland. In this work, we propose to use multiple statistical shape and appearance models to segment the prostate in 2D and a global registration framework to impose shape restriction in 3D. Multiple mean parametric models of the shape and appearance corresponding to the apex, central and base regions of the prostate gland are derived from principal component analysis (PCA) of prior shape and intensity information of the prostate from the training data. The estimated parameters are then modified with the prior knowledge of the optimization space to achieve segmentation in 2D. The 2D segmented slices are then rigidly registered with the average 3D model produced by affine registration of the ground truth of the training datasets to minimize pose variations and impose 3D shape restriction. The proposed method achieves a mean Dice similarity coefficient (DSC) value of 0.88+/-0.11, and mean Hausdorff distance (HD) of 3.38+/-2.81 mm when validated with 15 prostate volumes of a public dataset in leave-one-out validation framework. The results achieved are better compared to some of the works in the literature.

  14. Purification and properties of the light-activated cyclic nucleotide phosphodiesterase of rod outer segments.

    PubMed

    Miki, N; Baraban, J M; Keirns, J J; Boyce, J J; Bitensky, M W

    1975-08-25

    Frog (Rana catesbiana) rod outer segment disc membranes contain a cyclic nucleotide phosphodiesterase (EC 3.1.4.17) which is activated by light in the presence of ATP. This enzyme is firmly bound to the disc membrane, but can be eluted from the membrane with 10 mM Tris-HCl buffer, pH 7.4 and 2 mM EDTA. The eluted phosphodiesterase has reduced activity, but can be activated approximately 10-fold by polycations such as protamine and polylysine. The eluted phosphodiesterase can no longer be activated by light in the presence of ATP, that is, activation by light apparently depends on the native orientation of phosphodiesterase in relationship to other disc membrane components. The eluted phosphodiesterase was purified to homogeneity as judged by analytical polyacrylamide gel electrophoresis and polyacrylamide gel isoelectric focusing. The over-all purification from intact retina was approximately 925-fold. The purification of phosphodiesterase from the isolated rod outer segment preparation was about 185-fold with a 28% yield. Phosphodiesterase accounts for approximately 0.5% of the disc membrane protein. The eluted phosphodiesterase (inactive form) has a sedimentation coefficient of 12.4 S corresponding to an approximate molecular weight of 240,000. Sodium dodecyl sulfate polyacrylamide gel electrophoresis separates the purified phosphodiesterase into two subunits of 120,000 and 110,000 daltons. With cyclic 3':5'-GMP (cGMP) as substrate the Km for the purified phosphodiesterase is 70 muM. Protamine increases the Vmax without changing the Km for cGMP. The isoelectric point (pI) of the native dimer is 5.7. Limited exposure of the eluted phosphodiesterase (inactive form) to trypsin produces a somewhat greater activation than is obtained with 0.5 mg/ml of protamine. The trypsin-activated phosphodiesterase has a sedimentation coefficient of 7.8 S corresponding to an approximate molecular weight of 170,000. The 110,000-dalton subunit is much less sensitive to trypsin

  15. Automatic segmentation of cell nuclei in Feulgen-stained histological sections of prostate cancer and quantitative evaluation of segmentation results.

    PubMed

    Nielsen, Birgitte; Albregtsen, Fritz; Danielsen, Håvard E

    2012-07-01

    Digital image analysis of cell nuclei is useful to obtain quantitative information for the diagnosis and prognosis of cancer. However, the lack of a reliable automatic nuclear segmentation is a limiting factor for high-throughput nuclear image analysis. We have developed a method for automatic segmentation of nuclei in Feulgen-stained histological sections of prostate cancer. A local adaptive thresholding with an object perimeter gradient verification step detected the nuclei and was combined with an active contour model that featured an optimized initialization and worked within a restricted region to improve convergence of the segmentation of each nucleus. The method was tested on 30 randomly selected image frames from three cases, comparing the results from the automatic algorithm to a manual delineation of 924 nuclei. The automatic method segmented a few more nuclei compared to the manual method, and about 73% of the manually segmented nuclei were also segmented by the automatic method. For each nucleus segmented both manually and automatically, the accuracy (i.e., agreement with manual delineation) was estimated. The mean segmentation sensitivity/specificity were 95%/96%. The results from the automatic method were not significantly different from the ground truth provided by manual segmentation. This opens the possibility for large-scale nuclear analysis based on automatic segmentation of nuclei in Feulgen-stained histological sections.

  16. A general purpose contouring system

    USGS Publications Warehouse

    Evenden, Gerald Ian

    1975-01-01

    Three Decsystem-10 FORTRAN IV programs provide a general purpose system for contouring two-dimensional data. The system can provide both quick or final, publication quality contour maps on either interactive or offline plotting devices. Complete user documentation, with examples, and program listings are presented.

  17. Contour Integration across Spatial Frequency

    ERIC Educational Resources Information Center

    Persike, Malte; Olzak, Lynn A.; Meinhardt, Gunter

    2009-01-01

    Association field models of contour integration suggest that local band-pass elements are spatially grouped to global contours within limited bands of spatial frequency (Field, Hayes, & Hess, 1993). While results for local orientation and spacing variation render support for AF models, effects of spatial frequency (SF) have rarely been addressed.…

  18. Sensory Information and Subjective Contour

    ERIC Educational Resources Information Center

    Brussell, Edward M.; And Others

    1977-01-01

    The possibility that subjective contours are an artifact of brightness contrast was explored. Concludes that subjective contour and brightness contrast are distinct perceptual phenomena but share a dependency on the processing of edge information transmitted through the achromatic channels of the visual system. (Editor/RK)

  19. Abnormal contextual modulation of visual contour detection in patients with schizophrenia.

    PubMed

    Schallmo, Michael-Paul; Sponheim, Scott R; Olman, Cheryl A

    2013-01-01

    Schizophrenia patients demonstrate perceptual deficits consistent with broad dysfunction in visual context processing. These include poor integration of segments forming visual contours, and reduced visual contrast effects (e.g. weaker orientation-dependent surround suppression, ODSS). Background image context can influence contour perception, as stimuli near the contour affect detection accuracy. Because of ODSS, this contextual modulation depends on the relative orientation between the contour and flanking elements, with parallel flankers impairing contour perception. However in schizophrenia, the impact of abnormal ODSS during contour perception is not clear. It is also unknown whether deficient contour perception marks genetic liability for schizophrenia, or is strictly associated with clinical expression of this disorder. We examined contour detection in 25 adults with schizophrenia, 13 unaffected first-degree biological relatives of schizophrenia patients, and 28 healthy controls. Subjects performed a psychophysics experiment designed to quantify the effect of flanker orientation during contour detection. Overall, patients with schizophrenia showed poorer contour detection performance than relatives or controls. Parallel flankers suppressed and orthogonal flankers enhanced contour detection performance for all groups, but parallel suppression was relatively weaker for schizophrenia patients than healthy controls. Relatives of patients showed equivalent performance with controls. Computational modeling suggested that abnormal contextual modulation in schizophrenia may be explained by suppression that is more broadly tuned for orientation. Abnormal flanker suppression in schizophrenia is consistent with weaker ODSS and/or broader orientation tuning. This work provides the first evidence that such perceptual abnormalities may not be associated with a genetic liability for schizophrenia.

  20. An efficient method for accurate segmentation of LV in contrast-enhanced cardiac MR images

    NASA Astrophysics Data System (ADS)

    Suryanarayana K., Venkata; Mitra, Abhishek; Srikrishnan, V.; Jo, Hyun Hee; Bidesi, Anup

    2016-03-01

    Segmentation of left ventricle (LV) in contrast-enhanced cardiac MR images is a challenging task because of high variability in the image intensity. This is due to a) wash-in and wash-out of the contrast agent over time and b) poor contrast around the epicardium (outer wall) region. Current approaches for segmentation of the endocardium (inner wall) usually involve application of a threshold within the region of interest, followed by refinement techniques like active contours. A limitation of this method is under-segmentation of the inner wall because of gradual loss of contrast at the wall boundary. On the other hand, the challenge in outer wall segmentation is the lack of reliable boundaries because of poor contrast. There are four main contributions in this paper to address the aforementioned issues. First, a seed image is selected using variance based approach on 4D time-frame images over which initial endocardium and epicardium is segmented. Secondly, we propose a patch based feature which overcomes the problem of gradual contrast loss for LV endocardium segmentation. Third, we propose a novel Iterative-Edge-Refinement (IER) technique for epicardium segmentation. Fourth, we propose a greedy search algorithm for propagating the initial contour segmented on seed-image across other time frame images. We have experimented our technique on five contrast-enhanced cardiac MR Datasets (4D) having a total of 1097 images. The segmentation results for all 1097 images have been visually inspected by a clinical expert and have shown good accuracy.

  1. In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation.

    PubMed

    Xia, Chunlei; Wang, Longtan; Chung, Bu-Keun; Lee, Jang-Myung

    2015-08-19

    In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions.

  2. In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation

    PubMed Central

    Xia, Chunlei; Wang, Longtan; Chung, Bu-Keun; Lee, Jang-Myung

    2015-01-01

    In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions. PMID:26295395

  3. Impact of lesion segmentation metrics on computer-aided diagnosis/detection in breast computed tomography

    PubMed Central

    Kuo, Hsien-Chi; Giger, Maryellen L.; Reiser, Ingrid; Drukker, Karen; Boone, John M.; Lindfors, Karen K.; Yang, Kai; Edwards, Alexandra

    2014-01-01

    Abstract. Evaluation of segmentation algorithms usually involves comparisons of segmentations to gold-standard delineations without regard to the ultimate medical decision-making task. We compare two segmentation evaluations methods—a Dice similarity coefficient (DSC) evaluation and a diagnostic classification task–based evaluation method using lesions from breast computed tomography. In our investigation, we use results from two previously developed lesion-segmentation algorithms [a global active contour model (GAC) and a global with local aspects active contour model]. Although similar DSC values were obtained (0.80 versus 0.77), we show that the global + local active contour (GLAC) model, as compared with the GAC model, is able to yield significantly improved classification performance in terms of area under the receivers operating characteristic (ROC) curve in the task of distinguishing malignant from benign lesions. [Area under the ROC curve (AUC)=0.78 compared to 0.63, p≪0.001]. This is mainly because the GLAC model yields better detailed information required in the calculation of morphological features. Based on our findings, we conclude that the DSC metric alone is not sufficient for evaluating segmentation lesions in computer-aided diagnosis tasks. PMID:26158052

  4. A GENERAL ALGORITHM FOR THE CONSTRUCTION OF CONTOUR PLOTS

    NASA Technical Reports Server (NTRS)

    Johnson, W.

    1994-01-01

    The graphical presentation of experimentally or theoretically generated data sets frequently involves the construction of contour plots. A general computer algorithm has been developed for the construction of contour plots. The algorithm provides for efficient and accurate contouring with a modular approach which allows flexibility in modifying the algorithm for special applications. The algorithm accepts as input data values at a set of points irregularly distributed over a plane. The algorithm is based on an interpolation scheme in which the points in the plane are connected by straight line segments to form a set of triangles. In general, the data is smoothed using a least-squares-error fit of the data to a bivariate polynomial. To construct the contours, interpolation along the edges of the triangles is performed, using the bivariable polynomial if data smoothing was performed. Once the contour points have been located, the contour may be drawn. This program is written in FORTRAN IV for batch execution and has been implemented on an IBM 360 series computer with a central memory requirement of approximately 100K of 8-bit bytes. This computer algorithm was developed in 1981.

  5. Segmentation of confocal microscopic image of insect brain

    NASA Astrophysics Data System (ADS)

    Wu, Ming-Jin; Lin, Chih-Yang; Ching, Yu-Tai

    2002-05-01

    Accurate analysis of insect brain structures in digital confocal microscopic images is valuable and important to biology research needs. The first step is to segment meaningful structures from images. Active contour model, known as snakes, is widely used for segmentation of medical images. A new class of active contour model called gradient vector flow snake has been introduced in 1998 to overcome some critical problems encountered in the traditional snake. In this paper, we use gradient vector flow snake to segment the mushroom body and the central body from the confocal microscopic insect brain images. First, an edge map is created from images by some edge filters. Second, a gradient vector flow field is calculated from the edge map using a computational diffusion process. Finally, a traditional snake deformation process starts until it reaches a stable configuration. User interface is also provided here, allowing users to edit the snake during deformation process, if desired. Using the gradient vector flow snake as the main segmentation method and assist with user interface, we can properly segment the confocal microscopic insect brain image for most of the cases. The identified mushroom and central body can then be used as the preliminary results toward a 3-D reconstruction process for further biology researches.

  6. An in vitro method for recording single unit afferent activity from mesenteric nerves innervating isolated segments of rat ileum.

    PubMed

    Sharkey, K A; Cervero, F

    1986-04-01

    A technique has been developed for recording single unit afferent activity from mesenteric nerves in isolated segments of rat distal ileum in vitro. The preparation consists of a 3-cm segment of ileum, containing a single neurovascular bundle, held horizontally in an organ bath. One end of the segment is attached to a tension transducer to record changes in longitudinal tension of the gut muscle and the other is connected to a pressure transducer to record changes in intra-luminal pressure. Electromyographic activity of the smooth muscle is recorded using glass-insulated tungsten microelectrodes inserted in the wall of the gut. Afferent nerve activity is recorded with a monopolar platinum wire electrode from filaments of the mesenteric nerves that run between the artery and vein supplying the segment. This preparation permits the detailed analysis of the electrical activity of intestinal afferent nerve fibres correlated with mechanical and chemical events occurring naturally in the gut or imposed experimentally on it.

  7. Recognizing the authenticity of emotional expressions: F0 contour matters when you need to know.

    PubMed

    Drolet, Matthis; Schubotz, Ricarda I; Fischer, Julia

    2014-01-01

    Authenticity of vocal emotion expression affects emotion recognition and brain activity in the so-called Theory of Mind (ToM) network, which is implied in the ability to explain and predict behavior by attributing mental states to other individuals. Exploiting the variability of the fundamental frequency (F0 contour), which varies more (higher contour) in play-acted expressions than authentic ones, we examined whether contour biases explicit categorization toward a particular authenticity or emotion category. Moreover, we tested whether contour modulates blood-oxygen-level dependent (BOLD) response in the ToM network and explored the role of task as a top-down modulator. The effects of contour on BOLD signal were analyzed by contrasting high and low contour stimuli within two previous fMRI studies that implemented emotion and authenticity rating tasks. Participants preferentially categorized higher contour stimuli as play-acted and lower contour stimuli as sad. Higher contour was found to up-regulate activation task-independently in the primary auditory cortex. Stimulus contour and task were found to interact in a network including medial prefrontal cortex, with an increase in BOLD signal for low-contour stimuli during explicit perception of authenticity and an increase for high-contour stimuli during explicit perception of emotion. Contour-induced BOLD effects appear to be purely stimulus-driven in early auditory and intonation perception, while being strongly task-dependent in regions involved in higher cognition.

  8. Contour Error Map Algorithm

    NASA Technical Reports Server (NTRS)

    Merceret, Francis; Lane, John; Immer, Christopher; Case, Jonathan; Manobianco, John

    2005-01-01

    The contour error map (CEM) algorithm and the software that implements the algorithm are means of quantifying correlations between sets of time-varying data that are binarized and registered on spatial grids. The present version of the software is intended for use in evaluating numerical weather forecasts against observational sea-breeze data. In cases in which observational data come from off-grid stations, it is necessary to preprocess the observational data to transform them into gridded data. First, the wind direction is gridded and binarized so that D(i,j;n) is the input to CEM based on forecast data and d(i,j;n) is the input to CEM based on gridded observational data. Here, i and j are spatial indices representing 1.25-km intervals along the west-to-east and south-to-north directions, respectively; and n is a time index representing 5-minute intervals. A binary value of D or d = 0 corresponds to an offshore wind, whereas a value of D or d = 1 corresponds to an onshore wind. CEM includes two notable subalgorithms: One identifies and verifies sea-breeze boundaries; the other, which can be invoked optionally, performs an image-erosion function for the purpose of attempting to eliminate river-breeze contributions in the wind fields.

  9. Brain networks supporting perceptual grouping and contour selection.

    PubMed

    Volberg, Gregor; Greenlee, Mark W

    2014-01-01

    The human visual system groups local elements into global objects seemingly without effort. Using a contour integration task and EEG source level analyses, we tested the hypothesis that perceptual grouping requires a top-down selection, rather than a passive pooling, of neural information that codes local elements in the visual image. The participants were presented visual displays with or without a hidden contour. Two tasks were performed: a central luminance-change detection task and a peripheral contour detection task. Only in the contour-detection task could we find differential brain activity between contour and non-contour conditions, within a distributed brain network including parietal, lateral occipital and primary visual areas. Contour processing was associated with an inflow of information from lateral occipital into primary visual regions, as revealed from the slope of phase differences between source level oscillations within these areas. The findings suggest that contour integration results from a selection of neural information from lower visual areas, and that this selection is driven by the lateral occipital cortex.

  10. Volcanic evolution of an active magmatic rift segment on a 100 Kyr timescale: exposure dating of lavas from the Manda Hararo/Dabbahu segment of the Afar Rift

    NASA Astrophysics Data System (ADS)

    Medynski, S.; Williams, A.; Pik, R.; Burnard, P.; Vye, C.; France, L.; Ayalew, D.; Yirgu, G.

    2012-12-01

    the 2005 rifting episode. This second magmatic centre supplies magma to the remaining 2/3 of the segment, but scarcely impacts its Northern termination (where the Dabbahu activity predominates) - except during extraordinary events when dykes are long enough to reach those parts, as in 2005. The eruption ages of the different lava units correlates with their degrees of differentiation, allowing different magmatic cycles of about a few tens of years each to be distinguished. During the first recorded magmatic cycle (~70 ka to ~55 ka), Dabbahu is built of wide-spreading pāhoehoe flows around localised eruptive centres. The resulting topography of the volcanic edifice remains low, and is only slightly affected by rift-related fault activity, with the development of minor scarps. The second recorded magmatic cycle (~50 ka to ~20 ka) coincides with a strong development of Dabbahu topography - underlined by the change in lava morphology with well channelized 'a'ā flows since 50 ka. Tectonic activity also clearly increases over this period, with the initiation of the major fault scarps of the rift, which have been dated at around 35 ka. Our study underlines the role of the magma supply and availability beneath Dabbahu in the evolution both topographies of Dabbahu volcano and of the rift depression morphology.

  11. An effective segmentation method of ultrasonic thyroid nodules

    NASA Astrophysics Data System (ADS)

    Du, Wenpeng; Sang, Nong

    2015-12-01

    Segmentation of ultrasound image is an important port of ultrasound medical computer-aided system. However, due to the speckle noise, intensity heterogeneity, and low contrast, the ultrasonic segmentation is much difficult. In this paper, we introduce an effective method which integrates edge phase information and an effective active contour model to make the segmentation better. First, we use the speckle reducing anisotropic diffusion method to suppress the noise in ultrasound images. Then, we utilize the local phase information from monogenic signal to form a novel edge indicator and we use the indicator to replace the traditional intensity-based speed stopping term in distance regularized level set evolution. Another contribution of this paper is that we extend the proposed method to the field of ultrasonic thyroid nodules segmentation, qualitative and quantitative comparative results demonstrate the outperformance of our approach.

  12. An automated method for segmentation of epithelial cervical cells in images of ThinPrep.

    PubMed

    Harandi, Negar M; Sadri, Saeed; Moghaddam, Noushin A; Amirfattahi, Rassul

    2010-12-01

    We present an automated method for segmentation of epithelial cells in images taken from ThinPrep scenes by a digital camera in a cytology lab. The method covers both steps of localization of cell objects in low resolution and detection of cytoplasm and nucleus boundary in high resolution. The underlying method makes use of geometric active contours as a powerful tool of segmentation. We also provide the analysis of the connected cells. For this purpose an automatic circular decomposition method is incorporated and adapted to the application by changing its segmentation condition. The results are evaluated numerically and compared with those of previous work in literature. PMID:20703603

  13. Brain Activation of Negative Feedback in Rule Acquisition Revealed in a Segmented Wisconsin Card Sorting Test

    PubMed Central

    Wang, Jing; Cao, Bihua; Cai, Xueli; Gao, Heming; Li, Fuhong

    2015-01-01

    The present study is to investigate the brain activation associated with the informative value of negative feedback in rule acquisition. In each trial of a segmented Wisconsin Card Sorting Test, participants were provided with three reference cards and one target card, and were asked to match one of three reference cards to the target card based on a classification rule. Participants received feedback after each match. Participants would acquire the rule after one negative feedback (1-NF condition) or two successive negative feedbacks (2-NF condition). The functional magnetic resonance imaging (fMRI) results indicated that lateral prefrontal-to-parietal cortices were more active in the 2-NF condition than in the 1-NF condition. The activation in the right lateral prefrontal cortex and left posterior parietal cortex increased gradually with the amount of negative feedback. These results demonstrate that the informative value of negative feedback in rule acquisition might be modulated by the lateral prefronto-parietal loop. PMID:26469519

  14. WCPP-THE WOLF PLOTTING AND CONTOURING PACKAGE

    NASA Technical Reports Server (NTRS)

    Masaki, G. T.

    1994-01-01

    The WOLF Contouring and Plotting Package provides the user with a complete general purpose plotting and contouring capability. This package is a complete system for producing line printer, SC4020, Gerber, Calcomp, and SD4060 plots. The package has been designed to be highly flexible and easy to use. Any plot from a quick simple plot (which requires only one call to the package) to highly sophisticated plots (including motion picture plots) can be easily generated with only a basic knowledge of FORTRAN and the plot commands. Anyone designing a software system that requires plotted output will find that this package offers many advantages over the standard hardware support packages available. The WCPP package is divided into a plot segment and a contour segment. The plot segment can produce output for any combination of line printer, SC4020, Gerber, Calcomp, and SD4060 plots. The line printer plots allow the user to have plots available immediately after a job is run at a low cost. Although the resolution of line printer plots is low, the quick results allows the user to judge if a high resolution plot of a particular run is desirable. The SC4020 and SD4060 provide high speed high resolution cathode ray plots with film and hard copy output available. The Gerber and Calcomp plotters provide very high quality (of publishable quality) plots of good resolution. Being bed or drum type plotters, the Gerber and Calcomp plotters are usually slow and not suited for large volume plotting. All output for any or all of the plotters can be produced simultaneously. The types of plots supported are: linear, semi-log, log-log, polar, tabular data using the FORTRAN WRITE statement, 3-D perspective linear, and affine transformations. The labeling facility provides for horizontal labels, vertical labels, diagonal labels, vector characters of a requested size (special character fonts are easily implemented), and rotated letters. The gridding routines label the grid lines according to

  15. Influence of bacterial toxins on the GTPase activity of transducin from bovine retinal rod outer segments

    SciTech Connect

    Rybin, V.O.; Gureeva, A.A.

    1986-05-10

    The action of cholera toxin, capable of ADP-ribosylation of the activator N/sub s/ protein, and pertussis toxin, capable of ADP-ribosylation of the inhibitor N/sub i/ protein of the adenylate cyclase complex, on transducin, the GTP-binding protein of the rod outer segments of the retina, was investigated. It was shown that under the action of pertussis and cholera toxins, the GTPase activity of transducin is inhibited. Pertussin toxin inhibits the GTPase of native retinal rod outer segments by 30-40%, while GTPase of homogeneous transducin produces a 70-80% inhibition. The action of toxins on transducin depends on the presence and nature of the guanylic nucleotide with which incubation is performed. On the basis of the data obtained it is suggested that pertussis toxin interacts with pretransducin and with the transducin-GDP complex, while cholera toxin ADP-ribosylates the transducin-GTP complex and does not act on transducin lacking GTP.

  16. A novel 3D partitioned active shape model for segmentation of brain MR images.

    PubMed

    Zhao, Zheen; Aylward, Stephen R; Teoh, Earn Khwang

    2005-01-01

    A 3D Partitioned Active Shape Model (PASM) is proposed in this paper to address the problems of the 3D Active Shape Models (ASM). When training sets are small. It is usually the case in 3D segmentation, 3D ASMs tend to be restrictive. This is because the allowable region spanned by relatively few eigenvectors cannot capture the full range of shape variability. The 3D PASM overcomes this limitation by using a partitioned representation of the ASM. Given a Point Distribution Model (PDM), the mean mesh is partitioned into a group of small tiles. In order to constrain deformation of tiles, the statistical priors of tiles are estimated by applying Principal Component Analysis to each tile. To avoid the inconsistency of shapes between tiles, training samples are projected as curves in one hyperspace instead of point clouds in several hyperspaces. The deformed points are then fitted into the allowable region of the model by using a curve alignment scheme. The experiments on 3D human brain MRIs show that when the numbers of the training samples are limited, the 3D PASMs significantly improve the segmentation results as compared to 3D ASMs and 3D Hierarchical ASMs.

  17. Non-contact contour gage

    DOEpatents

    Bieg, Lothar F.

    1990-12-18

    A fluid probe for measuring the surface contour of a machined part is provided whereby the machined part can remain on the machining apparatus during surface contour measurement. A measuring nozzle in a measuring probe directs a measuring fluid flow onto the surface. The measuring nozzle is on the probe situated midway between two guide nozzles that direct guide fluid flows onto the surface. When the guide fluid flows interact with the surface, they cause the measuring flow and measuring probe to be oriented perpendicular to the surface. The measuring probe includes a pressure chamber whose pressure is monitored. As the measuring fluid flow encounters changes in surface contour, pressure changes occur in the pressure chamber. The surface contour is represented as data corresponding to pressure changes in the pressure chamber as the surface is scanned.

  18. Wavelet Representation of Contour Sets

    SciTech Connect

    Bertram, M; Laney, D E; Duchaineau, M A; Hansen, C D; Hamann, B; Joy, K I

    2001-07-19

    We present a new wavelet compression and multiresolution modeling approach for sets of contours (level sets). In contrast to previous wavelet schemes, our algorithm creates a parametrization of a scalar field induced by its contoum and compactly stores this parametrization rather than function values sampled on a regular grid. Our representation is based on hierarchical polygon meshes with subdivision connectivity whose vertices are transformed into wavelet coefficients. From this sparse set of coefficients, every set of contours can be efficiently reconstructed at multiple levels of resolution. When applying lossy compression, introducing high quantization errors, our method preserves contour topology, in contrast to compression methods applied to the corresponding field function. We provide numerical results for scalar fields defined on planar domains. Our approach generalizes to volumetric domains, time-varying contours, and level sets of vector fields.

  19. Isopachic contouring of opaque plates

    NASA Technical Reports Server (NTRS)

    Post, D.; Asundi, A.; Czarnek, R.

    1984-01-01

    Contour maps of change of thickness of opaque plates subjected to external loads are obtained using holographic interferometry in conjunction with the moire effect. A simple holographic-interferometry arrangement is used first to obtain contour maps of the out-of-plane displacements of the two sides of the object. Carrier patterns of equal magnitude but opposite signs are added to these contours. Superposition of the reconstructed holograms of the two sides produces a pattern of additive-moire fringes, which are contours of change of thickness. Effects of midplane warpage of the loaded specimen are cancelled. Sensitivity is lambda/2 per fringe order, contrast of the isopachic-fringe pattern is excellent, and the process is compatible with a mechanical-testing-machine environment.

  20. Generalized gradient and contour program

    USGS Publications Warehouse

    Hellman, Marshall Strong

    1972-01-01

    This program computes estimates of gradients, prepares contour maps, and plots various sets of data provided by the user on the CalComp plotters. The gradients represent the maximum rates of change of a real variable Z=f(X,Y) with respect to the twodimensional rectangle on which the function is defined. The contours are lines of equal Z values. The program also plots special line data sets provided by the user.

  1. Winding number constrained contour detection.

    PubMed

    Ming, Yansheng; Li, Hongdong; He, Xuming

    2015-01-01

    Salient contour detection can benefit from the integration of both contour cues and region cues. However, this task is difficult due to different nature of region representations and contour representations. To solve this problem, this paper proposes an energy minimization framework based on winding number constraints. In this framework, both region cues, such as color/texture homogeneity, and contour cues, such as local contrast and continuity, are represented in a joint objective function, which has both region and contour labels. The key problem is how to design constraints that ensure the topological consistency of the two kinds of labels. Our technique is based on the topological concept of winding number. Using a fast method for winding number computation, a small number of linear constraints are derived to ensure label consistency. Our method is instantiated by ratio-based energy functions. By successfully integrating both region and contour cues, our method shows advantages over competitive methods. Our method is extended to incorporate user interaction, which leads to further improvements.

  2. HOSVD-Based 3D Active Appearance Model: Segmentation of Lung Fields in CT Images.

    PubMed

    Wang, Qingzhu; Kang, Wanjun; Hu, Haihui; Wang, Bin

    2016-07-01

    An Active Appearance Model (AAM) is a computer vision model which can be used to effectively segment lung fields in CT images. However, the fitting result is often inadequate when the lungs are affected by high-density pathologies. To overcome this problem, we propose a Higher-order Singular Value Decomposition (HOSVD)-based Three-dimensional (3D) AAM. An evaluation was performed on 310 diseased lungs form the Lung Image Database Consortium Image Collection. Other contemporary AAMs operate directly on patterns represented by vectors, i.e., before applying the AAM to a 3D lung volume,it has to be vectorized first into a vector pattern by some technique like concatenation. However, some implicit structural or local contextual information may be lost in this transformation. According to the nature of the 3D lung volume, HOSVD is introduced to represent and process the lung in tensor space. Our method can not only directly operate on the original 3D tensor patterns, but also efficiently reduce the computer memory usage. The evaluation resulted in an average Dice coefficient of 97.0 % ± 0.59 %, a mean absolute surface distance error of 1.0403 ± 0.5716 mm, a mean border positioning errors of 0.9187 ± 0.5381 pixel, and a Hausdorff Distance of 20.4064 ± 4.3855, respectively. Experimental results showed that our methods delivered significant and better segmentation results, compared with the three other model-based lung segmentation approaches, namely 3D Snake, 3D ASM and 3D AAM. PMID:27277277

  3. Basic features of low-temperature plasma formation in the course of composite coating synthesis at the active faces of complex contoured hard tools

    NASA Astrophysics Data System (ADS)

    Brzhozovsky, B. M.; Zimnyakov, D. A.; Zinina, E. P.; Martynov, V. V.; Pleshakova, E. S.; Yuvchenko, S. A.

    2016-04-01

    Basic features of combined-discharge low-temperature plasma formation around the surfaces of complex-contoured metal units are considered. It is shown that it makes the possibilities for synthesis of hardened high-durable coatings of hard tools appropriate for material processing in extreme load-temperature conditions. Experimental study of the coating formation was carried out in combination with the analysis of emission spectra of a low-temperature plasma cloud. Some practical examples of the coating applications are presented.

  4. A fully automatic framework for cell segmentation on non-confocal adaptive optics images

    NASA Astrophysics Data System (ADS)

    Liu, Jianfei; Dubra, Alfredo; Tam, Johnny

    2016-03-01

    By the time most retinal diseases are diagnosed, macroscopic irreversible cellular loss has already occurred. Earlier detection of subtle structural changes at the single photoreceptor level is now possible, using the adaptive optics scanning light ophthalmoscope (AOSLO). This work aims to develop a fully automatic segmentation framework to extract cell boundaries from non-confocal split-detection AOSLO images of the cone photoreceptor mosaic in the living human eye. Significant challenges include anisotropy, heterogeneous cell regions arising from shading effects, and low contrast between cells and background. To overcome these challenges, we propose the use of: 1) multi-scale Hessian response to detect heterogeneous cell regions, 2) convex hulls to create boundary templates, and 3) circularlyconstrained geodesic active contours to refine cell boundaries. We acquired images from three healthy subjects at eccentric retinal regions and manually contoured cells to generate ground-truth for evaluating segmentation accuracy. Dice coefficient, relative absolute area difference, and average contour distance were 82±2%, 11±6%, and 2.0±0.2 pixels (Mean±SD), respectively. We find that strong shading effects from vessels are a main factor that causes cell oversegmentation and false segmentation of non-cell regions. Our segmentation algorithm can automatically and accurately segment photoreceptor cells on non-confocal AOSLO images, which is the first step in longitudinal tracking of cellular changes in the individual eye over the time course of disease progression.

  5. Saliency-aware food image segmentation for personal dietary assessment using a wearable computer

    NASA Astrophysics Data System (ADS)

    Chen, Hsin-Chen; Jia, Wenyan; Sun, Xin; Li, Zhaoxin; Li, Yuecheng; Fernstrom, John D.; Burke, Lora E.; Baranowski, Thomas; Sun, Mingui

    2015-02-01

    Image-based dietary assessment has recently received much attention in the community of obesity research. In this assessment, foods in digital pictures are specified, and their portion sizes (volumes) are estimated. Although manual processing is currently the most utilized method, image processing holds much promise since it may eventually lead to automatic dietary assessment. In this paper we study the problem of segmenting food objects from images. This segmentation is difficult because of various food types, shapes and colors, different decorating patterns on food containers, and occlusions of food and non-food objects. We propose a novel method based on a saliency-aware active contour model (ACM) for automatic food segmentation from images acquired by a wearable camera. An integrated saliency estimation approach based on food location priors and visual attention features is designed to produce a salient map of possible food regions in the input image. Next, a geometric contour primitive is generated and fitted to the salient map by means of multi-resolution optimization with respect to a set of affine and elastic transformation parameters. The food regions are then extracted after contour fitting. Our experiments using 60 food images showed that the proposed method achieved significantly higher accuracy in food segmentation when compared to conventional segmentation methods.

  6. Model-based segmentation of hand radiographs

    NASA Astrophysics Data System (ADS)

    Weiler, Frank; Vogelsang, Frank

    1998-06-01

    An important procedure in pediatrics is to determine the skeletal maturity of a patient from radiographs of the hand. There is great interest in the automation of this tedious and time-consuming task. We present a new method for the segmentation of the bones of the hand, which allows the assessment of the skeletal maturity with an appropriate database of reference bones, similar to the atlas based methods. The proposed algorithm uses an extended active contour model for the segmentation of the hand bones, which incorporates a-priori knowledge of shape and topology of the bones in an additional energy term. This `scene knowledge' is integrated in a complex hierarchical image model, that is used for the image analysis task.

  7. Positron emission tomography detects tissue metabolic activity in myocardial segments with persistent thallium perfusion defects

    SciTech Connect

    Brunken, R.; Schwaiger, M.; Grover-McKay, M.; Phelps, M.E.; Tillisch, J.; Schelbert, H.R.

    1987-09-01

    Positron emission tomography with /sup 13/N-ammonia and /sup 18/F-2-deoxyglucose was used to assess myocardial perfusion and glucose utilization in 51 myocardial segments with a stress thallium defect in 12 patients. Myocardial infarction was defined by a concordant reduction in segmental perfusion and glucose utilization, and myocardial ischemia was identified by preservation of glucose utilization in segments with rest hypoperfusion. Of the 51 segments studied, 36 had a fixed thallium defect, 11 had a partially reversible defect and 4 had a completely reversible defect. Only 15 (42%) of the 36 segments with a fixed defect and 4 (36%) of the 11 segments with a partially reversible defect exhibited myocardial infarction on study with positron tomography. In contrast, residual myocardial glucose utilization was identified in the majority of segments with a fixed (58%) or a partially reversible (64%) thallium defect. All of the segments with a completely reversible defect appeared normal on positron tomography. Apparent improvement in the thallium defect on delayed images did not distinguish segments with ischemia from infarction. Thus, positron emission tomography reveals evidence of persistent tissue metabolism in the majority of segments with a fixed or partially resolving stress thallium defect, implying that markers of perfusion alone may underestimate the extent of viable tissue in hypoperfused myocardial segments.

  8. Dynamic synchronization of ongoing neuronal activity across spinal segments regulates sensory information flow

    PubMed Central

    Contreras-Hernández, E; Chávez, D; Rudomin, P

    2015-01-01

    Previous studies on the correlation between spontaneous cord dorsum potentials recorded in the lumbar spinal segments of anaesthetized cats suggested the operation of a population of dorsal horn neurones that modulates, in a differential manner, transmission along pathways mediating Ib non-reciprocal postsynaptic inhibition and pathways mediating primary afferent depolarization and presynaptic inhibition. In order to gain further insight into the possible neuronal mechanisms that underlie this process, we have measured changes in the correlation between the spontaneous activity of individual dorsal horn neurones and the cord dorsum potentials associated with intermittent activation of these inhibitory pathways. We found that high levels of neuronal synchronization within the dorsal horn are associated with states of incremented activity along the pathways mediating presynaptic inhibition relative to pathways mediating Ib postsynaptic inhibition. It is suggested that ongoing changes in the patterns of functional connectivity within a distributed ensemble of dorsal horn neurones play a relevant role in the state-dependent modulation of impulse transmission along inhibitory pathways, among them those involved in the central control of sensory information. This feature would allow the same neuronal network to be involved in different functional tasks. Key points We have examined, in the spinal cord of the anaesthetized cat, the relationship between ongoing correlated fluctuations of dorsal horn neuronal activity and state-dependent activation of inhibitory reflex pathways. We found that high levels of synchronization between the spontaneous activity of dorsal horn neurones occur in association with the preferential activation of spinal pathways leading to primary afferent depolarization and presynaptic inhibition relative to activation of pathways mediating Ib postsynaptic inhibition. It is suggested that changes in synchronization of ongoing activity within a

  9. Entropy reduction via simplified image contourization

    NASA Technical Reports Server (NTRS)

    Turner, Martin J.

    1993-01-01

    The process of contourization is presented which converts a raster image into a set of plateaux or contours. These contours can be grouped into a hierarchical structure, defining total spatial inclusion, called a contour tree. A contour coder has been developed which fully describes these contours in a compact and efficient manner and is the basis for an image compression method. Simplification of the contour tree has been undertaken by merging contour tree nodes thus lowering the contour tree's entropy. This can be exploited by the contour coder to increase the image compression ratio. By applying general and simple rules derived from physiological experiments on the human vision system, lossy image compression can be achieved which minimizes noticeable artifacts in the simplified image.

  10. Efficient graph-cut tattoo segmentation

    NASA Astrophysics Data System (ADS)

    Kim, Joonsoo; Parra, Albert; Li, He; Delp, Edward J.

    2015-03-01

    Law enforcement is interested in exploiting tattoos as an information source to identify, track and prevent gang-related crimes. Many tattoo image retrieval systems have been described. In a retrieval system tattoo segmentation is an important step for retrieval accuracy since segmentation removes background information in a tattoo image. Existing segmentation methods do not extract the tattoo very well when the background includes textures and color similar to skin tones. In this paper we describe a tattoo segmentation approach by determining skin pixels in regions near the tattoo. In these regions graph-cut segmentation using a skin color model and a visual saliency map is used to find skin pixels. After segmentation we determine which set of skin pixels are connected with each other that form a closed contour including a tattoo. The regions surrounded by the closed contours are considered tattoo regions. Our method segments tattoos well when the background includes textures and color similar to skin.

  11. Multiscale approach to contour fitting for MR images

    NASA Astrophysics Data System (ADS)

    Rueckert, Daniel; Burger, Peter

    1996-04-01

    We present a new multiscale contour fitting process which combines information about the image and the contour of the object at different levels of scale. The algorithm is based on energy minimizing deformable models but avoids some of the problems associated with these models. The segmentation algorithm starts by constructing a linear scale-space of an image through convolution of the original image with a Gaussian kernel at different levels of scale, where the scale corresponds to the standard deviation of the Gaussian kernel. At high levels of scale large scale features of the objects are preserved while small scale features, like object details as well as noise, are suppressed. In order to maximize the accuracy of the segmentation, the contour of the object of interest is then tracked in scale-space from coarse to fine scales. We propose a hybrid multi-temperature simulated annealing optimization to minimize the energy of the deformable model. At high levels of scale the SA optimization is started at high temperatures, enabling the SA optimization to find a global optimal solution. At lower levels of scale the SA optimization is started at lower temperatures (at the lowest level the temperature is close to 0). This enforces a more deterministic behavior of the SA optimization at lower scales and leads to an increasingly local optimization as high energy barriers cannot be crossed. The performance and robustness of the algorithm have been tested on spin-echo MR images of the cardiovascular system. The task was to segment the ascending and descending aorta in 15 datasets of different individuals in order to measure regional aortic compliance. The results show that the algorithm is able to provide more accurate segmentation results than the classic contour fitting process and is at the same time very robust to noise and initialization.

  12. Telomerase activity concentrates in the mitotically active segments of human hair follicles.

    PubMed

    Ramirez, R D; Wright, W E; Shay, J W; Taylor, R S

    1997-01-01

    Telomerase is a ribonucleoprotein enzyme capable of adding hexanucleotide repeats onto the ends of linear chromosomal DNA. Whereas normal somatic cells with a limited replicative capacity fail to express telomerase activity, most immortal eukaryotic cells do. Cells of renewal tissues (e.g., skin, intestine, blood) require an extensive proliferative capacity. Some cells in such renewal tissues also express telomerase activity, most likely to prevent rapid erosion of their telomeres during cell proliferation. In this study, we measured the levels of telomerase activity in dissected compartments of the human hair follicle: hair shaft, gland-containing fragment, upper intermediate fragment (where it is thought undifferentiated stem cells reside), lower intermediate fragment, and in the bulb-containing fragment (an area with high mitotic activity containing a more differentiated pool of keratinocytes). In anagen follicles, high levels of telomerase activity were found almost exclusively in the bulb-containing fragment of the follicles, with low levels of telomerase in the bulge area (intermediate fragments) and gland-containing fragment. In comparison, catagen follicles had low levels of telomerase activity in the bulb-containing fragments as well as in other compartments. Such observations indicate that, in anagen hair follicles, the fragments containing cells actively dividing (e.g., transient amplifying cells) express telomerase activity, whereas fragments containing cells with low mitotic activity, for example, quiescent stem cells, express low levels of telomerase activity. PMID:8980299

  13. SU-E-J-132: Automated Segmentation with Post-Registration Atlas Selection Based On Mutual Information

    SciTech Connect

    Ren, X; Gao, H; Sharp, G

    2015-06-15

    Purpose: The delineation of targets and organs-at-risk is a critical step during image-guided radiation therapy, for which manual contouring is the gold standard. However, it is often time-consuming and may suffer from intra- and inter-rater variability. The purpose of this work is to investigate the automated segmentation. Methods: The automatic segmentation here is based on mutual information (MI), with the atlas from Public Domain Database for Computational Anatomy (PDDCA) with manually drawn contours.Using dice coefficient (DC) as the quantitative measure of segmentation accuracy, we perform leave-one-out cross-validations for all PDDCA images sequentially, during which other images are registered to each chosen image and DC is computed between registered contour and ground truth. Meanwhile, six strategies, including MI, are selected to measure the image similarity, with MI to be the best. Then given a target image to be segmented and an atlas, automatic segmentation consists of: (a) the affine registration step for image positioning; (b) the active demons registration method to register the atlas to the target image; (c) the computation of MI values between the deformed atlas and the target image; (d) the weighted image fusion of three deformed atlas images with highest MI values to form the segmented contour. Results: MI was found to be the best among six studied strategies in the sense that it had the highest positive correlation between similarity measure (e.g., MI values) and DC. For automated segmentation, the weighted image fusion of three deformed atlas images with highest MI values provided the highest DC among four proposed strategies. Conclusion: MI has the highest correlation with DC, and therefore is an appropriate choice for post-registration atlas selection in atlas-based segmentation. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)

  14. Active Optics for a Segmented Primary Mirror on a Deep-Space Optical Receiver Antenna (DSORA)

    NASA Technical Reports Server (NTRS)

    Clymer, B. D.

    1990-01-01

    This article investigates the active optical control of segments in the primary mirror to correct for wavefront errors in the Deep-Space Optical Receiver Antenna (DSORA). Although an exact assessment of improvement in signal blur radius cannot be made until a more detailed preliminary structural design is completed, analytical tools are identified for a time when such designs become available. A brief survey of appropriate sensing approaches is given. Since the choice of control algorithm and architecture depends on the particular sensing system used, typical control systems, estimated complexities, and the type of equipment required are discussed. Once specific sensor and actuator systems are chosen, the overall control system can be optimized using methods identified in the literature.

  15. Primary focal and segmental glomerulosclerosis and soluble factor urokinase-type plasminogen activator receptor.

    PubMed

    Trimarchi, Hernán

    2013-11-01

    Primary focal and segmental glomerulosclerosis (FSGS) may be due to genetic or acquired etiologies and is a common cause of nephrotic syndrome with high morbidity that often leads to end-stage renal failure. The different available therapeutic approaches are unsuccessful, in part due to partially deciphered heterogeneous and complex pathophysiological mechanisms. Moreover, the term FSGS, even in its primary form, comprises a histological description shared by a number of different causes with completely different molecular pathways of disease. This review focuses on the latest developments regarding the pathophysiology of primary acquired FSGS caused by soluble factor urokinase type plasminogen activator receptor, a circulating permeability factor involved in proteinuria and edema formation, and describes recent advances with potential success in therapy.

  16. Pattern segmentation with activity dependent natural frequency shift and sub-threshold resonance

    NASA Astrophysics Data System (ADS)

    Shtrahman, E.; Zochowski, M.

    2015-03-01

    Understanding the mechanisms underlying distributed pattern formation in brain networks and its content driven dynamical segmentation is an area of intense study. We investigate a theoretical mechanism for selective activation of diverse neural populations that is based on dynamically shifting cellular resonances in functionally or structurally coupled networks. We specifically show that sub-threshold neuronal depolarization from synaptic coupling or external input can shift neurons into and out of resonance with specific bands of existing extracellular oscillations, and this can act as a dynamic readout mechanism during information storage and retrieval. We find that this mechanism is robust and suggest it as a general coding strategy that can be applied to any network with oscillatory nodes.

  17. Sonority contours in word recognition

    NASA Astrophysics Data System (ADS)

    McLennan, Sean

    2003-04-01

    Contrary to the Generativist distinction between competence and performance which asserts that speech or perception errors are due to random, nonlinguistic factors, it seems likely that errors are principled and possibly governed by some of the same constraints as language. A preliminary investigation of errors modeled after the child's ``Chain Whisper'' game (a degraded stimulus task) suggests that a significant number of recognition errors can be characterized as an improvement in syllable sonority contour towards the linguistically least-marked, voiceless-stop-plus-vowel syllable. An independent study of sonority contours showed that approximately half of the English lexicon can be uniquely identified by their contour alone. Additionally, ``sororities'' (groups of words that share a single sonority contour), surprisingly, show no correlation to familiarity or frequency in either size or membership. Together these results imply that sonority contours may be an important factor in word recognition and in defining word ``neighborhoods.'' Moreover, they suggest that linguistic markedness constraints may be more prevalent in performance-related phenomena than previously accepted.

  18. Orientation-crowding within contours.

    PubMed

    Glen, James C; Dakin, Steven C

    2013-01-01

    We examined how crowding (the breakdown of object recognition in the periphery caused by interference from "clutter") depends on the global arrangement of target and distracting flanker elements. Specifically we probed orientation discrimination using a near-vertical target Gabor flanked by two vertical distractor Gabors (one above and one below the target). By applying variable (opposite-sign) horizontal offsets to the positions of the two flankers we arranged the elements so that on some trials they formed contours with the target and on others they did not. While the presence of flankers generally elevated orientation discrimination thresholds for the target we observe maximal crowding not when flanker and targets were co-aligned but when a small spatial offset was applied to flanker location, so that contours formed between flanker and targets only when the target orientation was cued. We also report that observers' orientation judgments are biased, with target orientation appearing either attracted or repulsed by the global/contour orientation. A second experiment reveals that the sign of this effect is dependent both on observer and on eccentricity. In general, the magnitude of repulsion is reduced with eccentricity but whether this becomes attraction (of element orientation to contour orientation) is dependent on observer. We note however that across observers and eccentricities, the magnitude of repulsion correlates positively with the amount of release from crowding observed with co-aligned targets and flankers, supporting the notion of fluctuating bias as the basis for elevated crowding within contours. PMID:23857951

  19. Automatic 3D lesion segmentation on breast ultrasound images

    NASA Astrophysics Data System (ADS)

    Kuo, Hsien-Chi; Giger, Maryellen L.; Reiser, Ingrid; Drukker, Karen; Edwards, Alexandra; Sennett, Charlene A.

    2013-02-01

    Automatically acquired and reconstructed 3D breast ultrasound images allow radiologists to detect and evaluate breast lesions in 3D. However, assessing potential cancers in 3D ultrasound can be difficult and time consuming. In this study, we evaluate a 3D lesion segmentation method, which we had previously developed for breast CT, and investigate its robustness on lesions on 3D breast ultrasound images. Our dataset includes 98 3D breast ultrasound images obtained on an ABUS system from 55 patients containing 64 cancers. Cancers depicted on 54 US images had been clinically interpreted as negative on screening mammography and 44 had been clinically visible on mammography. All were from women with breast density BI-RADS 3 or 4. Tumor centers and margins were indicated and outlined by radiologists. Initial RGI-eroded contours were automatically calculated and served as input to the active contour segmentation algorithm yielding the final lesion contour. Tumor segmentation was evaluated by determining the overlap ratio (OR) between computer-determined and manually-drawn outlines. Resulting average overlap ratios on coronal, transverse, and sagittal views were 0.60 +/- 0.17, 0.57 +/- 0.18, and 0.58 +/- 0.17, respectively. All OR values were significantly higher the 0.4, which is deemed "acceptable". Within the groups of mammogram-negative and mammogram-positive cancers, the overlap ratios were 0.63 +/- 0.17 and 0.56 +/- 0.16, respectively, on the coronal views; with similar results on the other views. The segmentation performance was not found to be correlated to tumor size. Results indicate robustness of the 3D lesion segmentation technique in multi-modality 3D breast imaging.

  20. A synthetic segment of surfactant protein A: structure, in vitro surface activity, and in vivo efficacy.

    PubMed

    Walther, F J; David-Cu, R; Leung, C; Bruni, R; Hernández-Juviel, J; Gordon, L M; Waring, A J

    1996-06-01

    Surfactant protein A (SP-A) is a 248-residue, water-soluble, lipid-associating protein found in lung surfactant. Analysis of the amino acid sequence using the Eisenberg hydrophobic moment algorithm predicts that the SP-A segment spanning residues 114-144 has high hydrophobic moments, typical of lipid-associating amphipathic domains. The secondary structure, in vitro surface activity and in vivo lung activity of this SP-A sequence were studied with a 31-residue synthetic peptide analog (A114-144). Analysis of the secondary structure using circular dichroism and Fourier transform infrared spectroscopy indicated association with lipid dispersions and a dominant helical content. Surface activity measurements of A114-144 with surfactant lipid dispersions and the hydrophobic surfactant proteins B and C (SP-B/C) showed that A114-144 enhances surface activity under conditions of dynamic compression and respreading on a Langmuir/Wilhelmy surface balance. Synthetic surfactant dispersions containing A114-144 improved lung compliance in spontaneously breathing, 28-d premature rabbits to a greater degree than surfactant dispersions with synthetic SP-B/C and synthetic surfactant lipids alone. These observations indicate that inclusion of A114-144 may improve synthetic preparations currently used for surfactant replacement therapy.

  1. Body Image and Body Contouring Procedures.

    PubMed

    Sarwer, David B; Polonsky, Heather M

    2016-10-01

    Dissatisfaction with physical appearance and body image is a common psychological phenomena in Western society. Body image dissatisfaction is frequently reported by those who have excess body weight, but also is seen in those of normal body weight. For both groups of individuals, this dissatisfaction impacts self-esteem and quality of life. Furthermore, it is believed to be the motivational catalyst to a range of appearance-enhancing behaviors, including weight loss efforts and physical activity. Body image dissatisfaction is also believed to play a role in the decision to seek the wide range of body contouring procedures offered by aesthetic physicians. Individuals who seek these procedures typically report increased body image dissatisfaction, focus on the feature they wish to alter with treatment, and often experience improvement in body image following treatment. At the same time, extreme body image dissatisfaction is a symptom of a number of recognized psychiatric disorders. These include anorexia nervosa, bulimia nervosa, and body dysmorphic disorder (BDD), all of which can contraindicate aesthetic treatment. This special topic review paper provides an overview of the relationship between body image dissatisfaction and aesthetic procedures designed to improve body contouring. The review specifically focuses on the relationship of body image and body weight, as well as the presentation of body image psychopathology that would contraindicate aesthetic surgery. The overall goal of the paper is to highlight the clinical implications of the existing research and provide suggestions for future research on the psychological aspects of body contouring procedures.

  2. Body Image and Body Contouring Procedures.

    PubMed

    Sarwer, David B; Polonsky, Heather M

    2016-10-01

    Dissatisfaction with physical appearance and body image is a common psychological phenomena in Western society. Body image dissatisfaction is frequently reported by those who have excess body weight, but also is seen in those of normal body weight. For both groups of individuals, this dissatisfaction impacts self-esteem and quality of life. Furthermore, it is believed to be the motivational catalyst to a range of appearance-enhancing behaviors, including weight loss efforts and physical activity. Body image dissatisfaction is also believed to play a role in the decision to seek the wide range of body contouring procedures offered by aesthetic physicians. Individuals who seek these procedures typically report increased body image dissatisfaction, focus on the feature they wish to alter with treatment, and often experience improvement in body image following treatment. At the same time, extreme body image dissatisfaction is a symptom of a number of recognized psychiatric disorders. These include anorexia nervosa, bulimia nervosa, and body dysmorphic disorder (BDD), all of which can contraindicate aesthetic treatment. This special topic review paper provides an overview of the relationship between body image dissatisfaction and aesthetic procedures designed to improve body contouring. The review specifically focuses on the relationship of body image and body weight, as well as the presentation of body image psychopathology that would contraindicate aesthetic surgery. The overall goal of the paper is to highlight the clinical implications of the existing research and provide suggestions for future research on the psychological aspects of body contouring procedures. PMID:27634782

  3. Multi-object segmentation framework using deformable models for medical imaging analysis.

    PubMed

    Namías, Rafael; D'Amato, Juan Pablo; Del Fresno, Mariana; Vénere, Marcelo; Pirró, Nicola; Bellemare, Marc-Emmanuel

    2016-08-01

    Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed

  4. Multi-object segmentation framework using deformable models for medical imaging analysis.

    PubMed

    Namías, Rafael; D'Amato, Juan Pablo; Del Fresno, Mariana; Vénere, Marcelo; Pirró, Nicola; Bellemare, Marc-Emmanuel

    2016-08-01

    Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed

  5. Topological Cacti: Visualizing Contour-based Statistics

    SciTech Connect

    Weber, Gunther H.; Bremer, Peer-Timo; Pascucci, Valerio

    2011-05-26

    Contours, the connected components of level sets, play an important role in understanding the global structure of a scalar field. In particular their nestingbehavior and topology-often represented in form of a contour tree-have been used extensively for visualization and analysis. However, traditional contour trees onlyencode structural properties like number of contours or the nesting of contours, but little quantitative information such as volume or other statistics. Here we use thesegmentation implied by a contour tree to compute a large number of per-contour (interval) based statistics of both the function defining the contour tree as well asother co-located functions. We introduce a new visual metaphor for contour trees, called topological cacti, that extends the traditional toporrery display of acontour tree to display additional quantitative information as width of the cactus trunk and length of its spikes. We apply the new technique to scalar fields ofvarying dimension and different measures to demonstrate the effectiveness of the approach.

  6. A spectral k-means approach to bright-field cell image segmentation.

    PubMed

    Bradbury, Laura; Wan, Justin W L

    2010-01-01

    Automatic segmentation of bright-field cell images is important to cell biologists, but difficult to complete due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). Standard approaches such as level set segmentation and active contours work well for fluorescent images where cells appear as round shape, but become less effective when optical artifacts such as halo exist in bright-field images. In this paper, we present a robust segmentation method which combines the spectral and k-means clustering techniques to locate cells in bright-field images. This approach models an image as a matrix graph and segment different regions of the image by computing the appropriate eigenvectors of the matrix graph and using the k-means algorithm. We illustrate the effectiveness of the method by segmentation results of C2C12 (muscle) cells in bright-field images. PMID:21096019

  7. Calcineurin signaling mediates activity-dependent relocation of the axon initial segment.

    PubMed

    Evans, Mark D; Sammons, Rosanna P; Lebron, Sabrina; Dumitrescu, Adna S; Watkins, Thomas B K; Uebele, Victor N; Renger, John J; Grubb, Matthew S

    2013-04-17

    The axon initial segment (AIS) is a specialized neuronal subcompartment located at the beginning of the axon that is crucially involved in both the generation of action potentials and the regulation of neuronal polarity. We recently showed that prolonged neuronal depolarization produces a distal shift of the entire AIS structure away from the cell body, a change associated with a decrease in neuronal excitability. Here, we used dissociated rat hippocampal cultures, with a major focus on the dentate granule cell (DGC) population, to explore the signaling pathways underlying activity-dependent relocation of the AIS. First, a pharmacological screen of voltage-gated calcium channels (VGCCs) showed that AIS relocation is triggered by activation of L-type Cav1 VGCCs with negligible contribution from any other VGCC subtypes. Additional pharmacological analysis revealed that downstream signaling events are mediated by the calcium-sensitive phosphatase calcineurin; inhibition of calcineurin with either FK506 or cyclosporin A totally abolished both depolarization- and optogenetically-induced activity-dependent AIS relocation. Furthermore, calcineurin activation is sufficient for AIS plasticity, because expression of a constitutively active form of the phosphatase resulted in relocation of the AIS of DGCs without a depolarizing stimulus. Finally, we assessed the role of calcineurin in other forms of depolarization-induced plasticity. Neither membrane resistance changes nor spine density changes were affected by FK506 treatment, suggesting that calcineurin acts via a separate pathway to modulate AIS plasticity. Together, these results emphasize calcineurin as a vital player in the regulation of intrinsic plasticity as governed by the AIS. PMID:23595753

  8. Image segmentation using random features

    NASA Astrophysics Data System (ADS)

    Bull, Geoff; Gao, Junbin; Antolovich, Michael

    2014-01-01

    This paper presents a novel algorithm for selecting random features via compressed sensing to improve the performance of Normalized Cuts in image segmentation. Normalized Cuts is a clustering algorithm that has been widely applied to segmenting images, using features such as brightness, intervening contours and Gabor filter responses. Some drawbacks of Normalized Cuts are that computation times and memory usage can be excessive, and the obtained segmentations are often poor. This paper addresses the need to improve the processing time of Normalized Cuts while improving the segmentations. A significant proportion of the time in calculating Normalized Cuts is spent computing an affinity matrix. A new algorithm has been developed that selects random features using compressed sensing techniques to reduce the computation needed for the affinity matrix. The new algorithm, when compared to the standard implementation of Normalized Cuts for segmenting images from the BSDS500, produces better segmentations in significantly less time.

  9. Welding deviation detection algorithm based on extremum of molten pool image contour

    NASA Astrophysics Data System (ADS)

    Zou, Yong; Jiang, Lipei; Li, Yunhua; Xue, Long; Huang, Junfen; Huang, Jiqiang

    2016-01-01

    The welding deviation detection is the basis of robotic tracking welding, but the on-line real-time measurement of welding deviation is still not well solved by the existing methods. There is plenty of information in the gas metal arc welding(GMAW) molten pool images that is very important for the control of welding seam tracking. The physical meaning for the curvature extremum of molten pool contour is revealed by researching the molten pool images, that is, the deviation information points of welding wire center and the molten tip center are the maxima and the local maxima of the contour curvature, and the horizontal welding deviation is the position difference of these two extremum points. A new method of weld deviation detection is presented, including the process of preprocessing molten pool images, extracting and segmenting the contours, obtaining the contour extremum points, and calculating the welding deviation, etc. Extracting the contours is the premise, segmenting the contour lines is the foundation, and obtaining the contour extremum points is the key. The contour images can be extracted with the method of discrete dyadic wavelet transform, which is divided into two sub contours including welding wire and molten tip separately. The curvature value of each point of the two sub contour lines is calculated based on the approximate curvature formula of multi-points for plane curve, and the two points of the curvature extremum are the characteristics needed for the welding deviation calculation. The results of the tests and analyses show that the maximum error of the obtained on-line welding deviation is 2 pixels(0.16 mm), and the algorithm is stable enough to meet the requirements of the pipeline in real-time control at a speed of less than 500 mm/min. The method can be applied to the on-line automatic welding deviation detection.

  10. Segmentation of bionano images for understanding cell dynamics.

    PubMed

    Mukewar, Pushkar; Wang, Geoffrey; Henning, Peter; Bao, Gang; Wang, May

    2004-01-01

    The use of quantum dots (QDs) and molecular beacons (MBs) is a recent advance in the field of nanotechnology. These techniques have enabled us to detect a single molecule in a cell, which helps in understanding the dynamics of a cell. The success of these techniques depends on the accurate and efficient analysis of the imaging data these techniques produce. The processing involves--segmentation of the particles, colocalisation and their tracking over multiple frames in 2D and 3D space. In this paper we have used the active contour models: snakes and their variation--GVF (gradient vector field) snakes for segmentation of nano(QD) and cell(MB) images. The results of segmentation have been used to measure the degree of colocalisation for quantum dot images and the gene expression values for molecular beacon images.

  11. Bacterial foraging based edge detection for cell image segmentation.

    PubMed

    Pan, Yongsheng; Zhou, Tao; Xia, Yong

    2015-01-01

    Edge detection is the most popular and common choices for cell image segmentation, in which local searching strategies are commonly used. In spite of their computational efficiency, traditional edge detectors, however, may either produce discontinued edges or rely heavily on initializations. In this paper, we propose a bacterial foraging based edge detection (BFED) algorithm for cell image segmentation. We model the gradients of intensities as the nutrient concentration and propel bacteria to forage along nutrient-rich locations via mimicking the behavior of Escherichia coli, including the chemotaxis, swarming, reproduction, elimination and dispersal. As a nature-inspired evolutionary technique, this algorithm can identify the desired edges and mark them as the tracks of bacteria. We have evaluated the proposed algorithm against the Canny, SUSAN, Verma's and an active contour model (ACM) based edge detectors on both synthetic and real cell images. Our results suggest that the BFED algorithm can identify boundaries more effectively and provide more accurate cell image segmentation. PMID:26737139

  12. Segmental basal cell naevus syndrome caused by an activating mutation in smoothened.

    PubMed

    Khamaysi, Z; Bochner, R; Indelman, M; Magal, L; Avitan-Hersh, E; Sarig, O; Sprecher, E; Bergman, R

    2016-07-01

    Aberrant sonic hedgehog signalling, mostly due to PTCH1 mutations, has been shown to play a central role in the pathogenesis of basal cell carcinoma (BCC), as well as in basal cell naevus syndrome (BCNS). Mutations in smoothened (SMO) encoding a receptor for sonic hedgehog have been reported in sporadic BCCs but not in BCNS. We report a case with multiple BCCs, pits and comedones in a segmental distribution over the upper part of the body, along with other findings compatible with BCNS. Histopathologically, there were different types of BCC. A heterozygous mutation (c.1234C>T, p.L412F) in SMO was detected in three BCCs but not in peripheral blood lymphocytes or the uninvolved skin. These were compatible with the type 1 mosaic form of BCNS. The p.L412F mutation was found experimentally to result in increased SMO transactivating activity, and the patient responded to vismodegib therapy. Activating mutations in SMO may cause BCNS. The identification of a gain-of-function mutation in SMO causing a type 1 mosaic form of BCNS further expands our understanding of the pathogenesis of BCC, with implications for the treatment of these tumours, whether sporadic or inherited. PMID:26822128

  13. Active Gaze Control Improves Optic Flow-Based Segmentation and Steering

    PubMed Central

    Raudies, Florian; Mingolla, Ennio; Neumann, Heiko

    2012-01-01

    An observer traversing an environment actively relocates gaze to fixate objects. Evidence suggests that gaze is frequently directed toward the center of an object considered as target but more likely toward the edges of an object that appears as an obstacle. We suggest that this difference in gaze might be motivated by specific patterns of optic flow that are generated by either fixating the center or edge of an object. To support our suggestion we derive an analytical model that shows: Tangentially fixating the outer surface of an obstacle leads to strong flow discontinuities that can be used for flow-based segmentation. Fixation of the target center while gaze and heading are locked without head-, body-, or eye-rotations gives rise to a symmetric expansion flow with its center at the point being approached, which facilitates steering toward a target. We conclude that gaze control incorporates ecological constraints to improve the robustness of steering and collision avoidance by actively generating flows appropriate to solve the task. PMID:22719889

  14. Fuzzy fusion of results of medical image segmentation

    NASA Astrophysics Data System (ADS)

    Guliato, Denise; Rangayyan, Rangaraj M.; Carnielli, Walter A.; Zuffo, Joao A.; Desautels, J. E. Leo

    1999-05-01

    We propose an abstract concept of data fusion based on finite automata and fuzzy sets to integrate and evaluate different sources of information, in particular results of multiple image segmentation procedures. We give an example of how the method may be applied to the problem of mammographic image segmentation to combine results of region growing and closed- contour detection techniques. We further propose a measure of fuzziness to assess the agreement between a segmented region and a reference contour. Results of application to breast tumor detection in mammograms indicate that the fusion results agree with reference contours provided by a radiologist to a higher extent than the results of the individual methods.

  15. MULTISCALE DISCRETIZATION OF SHAPE CONTOURS

    SciTech Connect

    Prasad, L.; Rao, R.

    2000-09-01

    We present an efficient multi-scale scheme to adaptively approximate the continuous (or densely sampled) contour of a planar shape at varying resolutions. The notion of shape is intimately related to the notion of contour, and the efficient representation of the contour of a shape is vital to a computational understanding of the shape. Any polygonal approximation of a planar smooth curve is equivalent to a piecewise constant approximation of the parameterized X and Y coordinate functions of a discrete point set obtained by densely sampling the curve. Using the Haar wavelet transform for the piecewise approximation yields a hierarchical scheme in which the size of the approximating point set is traded off against the morphological accuracy of the approximation. Our algorithm compresses the representation of the initial shape contour to a sparse sequence of points in the plane defining the vertices of the shape's polygonal approximation. Furthermore, it is possible to control the overall resolution of the approximation by a single, scale-independent parameter.

  16. Contour inflections are adaptable features.

    PubMed

    Bell, Jason; Sampasivam, Sinthujaa; McGovern, David P; Meso, Andrew Isaac; Kingdom, Frederick A A

    2014-06-03

    An object's shape is a strong cue for visual recognition. Most models of shape coding emphasize the role of oriented lines and curves for coding an object's shape. Yet inflection points, which occur at the junction of two oppositely signed curves, are ubiquitous features in natural scenes and carry important information about the shape of an object. Using a visual aftereffect in which the perceived shape of a contour is changed following prolonged viewing of a slightly different-shaped contour, we demonstrate a specific aftereffect for a contour inflection. Control conditions show that this aftereffect cannot be explained by adaptation to either the component curves or to the local orientation at the point of inflection. Further, we show that the aftereffect transfers weakly to a compound curve without an inflection, ruling out a general compound curvature detector as an explanation of our findings. We assume however that there are adaptable mechanisms for coding other specific forms of compound curves. Taken together, our findings provide evidence that the human visual system contains specific mechanisms for coding contour inflections, further highlighting their role in shape and object coding.

  17. Illusory contour formation survives crowding.

    PubMed

    Lau, Jonathan Siu Fung; Cheung, Sing-Hang

    2012-06-12

    Flanked objects are difficult to identify using peripheral vision due to visual crowding, which limits conscious access to target identity. Nonetheless, certain types of visual information have been shown to survive crowding. Such resilience to crowding provides valuable information about the underlying neural mechanism of crowding. Here we ask whether illusory contour formation survives crowding of the inducers. We manipulated the presence of illusory contours through the (mis)alignment of the four inducers of a Kanizsa square. In the inducer-aligned condition, the observers judged the perceived shape (thin vs. fat) of the illusory Kanizsa square, manipulated by small rotations of the inducers. In the inducer-misaligned condition, three of the four inducers (all except the upper-left) were rotated 90°. The observers judged the orientation of the upper-left inducer. Crowding of the inducers worsened observers' performance significantly only in the inducer-misaligned condition. Our findings suggest that information for illusory contour formation survives crowding of the inducers. Crowding happens at a stage where the low-level featural information is integrated for inducer orientation discrimination, but not at a stage where the same information is used for illusory contour formation.

  18. Hippocampus segmentation using locally weighted prior based level set

    NASA Astrophysics Data System (ADS)

    Achuthan, Anusha; Rajeswari, Mandava

    2015-12-01

    Segmentation of hippocampus in the brain is one of a major challenge in medical image segmentation due to its' imaging characteristics, with almost similar intensity between another adjacent gray matter structure, such as amygdala. The intensity similarity has causes the hippocampus to have weak or fuzzy boundaries. With this main challenge being demonstrated by hippocampus, a segmentation method that relies on image information alone may not produce accurate segmentation results. Therefore, it is needed an assimilation of prior information such as shape and spatial information into existing segmentation method to produce the expected segmentation. Previous studies has widely integrated prior information into segmentation methods. However, the prior information has been utilized through a global manner integration, and this does not reflect the real scenario during clinical delineation. Therefore, in this paper, a locally integrated prior information into a level set model is presented. This work utilizes a mean shape model to provide automatic initialization for level set evolution, and has been integrated as prior information into the level set model. The local integration of edge based information and prior information has been implemented through an edge weighting map that decides at voxel level which information need to be observed during a level set evolution. The edge weighting map shows which corresponding voxels having sufficient edge information. Experiments shows that the proposed integration of prior information locally into a conventional edge-based level set model, known as geodesic active contour has shown improvement of 9% in averaged Dice coefficient.

  19. Changes of contour of the spine caused by load carrying.

    PubMed

    Vacheron, J J; Poumarat, G; Chandezon, R; Vanneuville, G

    1999-01-01

    The development of new leisure activities such as walking has spread the use of the backpack as a means of carrying loads. The aim of this work was to present a way of defining the movements imposed on the trunk by this type of load carrying. A 20 kg load situated at the thoracic level (T9) of the trunk, was placed in a backpack (2.5 kg). The 12 subjects were average mountain guides of Auvergne region, intermediate level and complete beginners. External markers were glued to the projecting contours of the spinous processes of the C7, T7, T12, L3 and S1 vertebrae, the shin and the external occipital tuberosity (EOT). Using a Vicon 140 3-D system we measured the effective mobility of the different spinal segments in the sagittal plane during one step. For every subject, we noticed a significant decrease of the effective inter-segmental mobility (EISM) between S1-L3-T12 (p < .01) while backpacking a 22.5 kg load. A decrease of EISM also appeared at the next level between L3-T12-T7 (p < .05). An increase of the EISM between T7-C7-EOT was noted (p < .05). We supposed that strength loss of the back muscles and/or angular oscillations of the trunk could be a common cause of symptoms during backpacking. The subjects using this type of load carrying have to adopt an adequate position of the lumbar, dorsal and cervical vertebrae. PMID:10399210

  20. Automated fat measurement and segmentation with intensity inhomogeneity correction

    NASA Astrophysics Data System (ADS)

    Sussman, Daniel L.; Yao, Jianhua; Summers, Ronald M.

    2010-03-01

    Adipose tissue (AT) content, especially visceral AT (VAT), is an important indicator for risks of many disorders, including heart disease and diabetes. Fat measurement by traditional means is often inaccurate and cannot separate subcutaneous and visceral fat. MRI offers a medium to obtain accurate measurements and segmentation between subcutaneous and visceral fat. We present an approach to automatically label the voxels associated with adipose tissue and segment them between subcutaneous and visceral. Our method uses non-parametric non-uniform intensity normalization (N3) to correct for image artifacts and inhomogeneities, fuzzy c-means to cluster AT regions and active contour models to separate SAT and VAT. Our algorithm has four stages: body masking, preprocessing, SAT and VAT separation, and tissue classification and quantification. The method was validated against a manual method performed by two observers, which used thresholds and manual contours to separate SAT and VAT. We measured 25 patients, 22 of which were included in the final analysis and the other three had too much artifact for automated processing. For SAT and total AT, differences between manual and automatic measurements were comparable to manual inter-observer differences. VAT measurements showed more variance in the automated method, likely due to inaccurate contours.

  1. Prostate segmentation in MRI using fused T2-weighted and elastography images

    NASA Astrophysics Data System (ADS)

    Nir, Guy; Sahebjavaher, Ramin S.; Baghani, Ali; Sinkus, Ralph; Salcudean, Septimiu E.

    2014-03-01

    Segmentation of the prostate in medical imaging is a challenging and important task for surgical planning and delivery of prostate cancer treatment. Automatic prostate segmentation can improve speed, reproducibility and consistency of the process. In this work, we propose a method for automatic segmentation of the prostate in magnetic resonance elastography (MRE) images. The method utilizes the complementary property of the elastogram and the corresponding T2-weighted image, which are obtained from the phase and magnitude components of the imaging signal, respectively. It follows a variational approach to propagate an active contour model based on the combination of region statistics in the elastogram and the edge map of the T2-weighted image. The method is fast and does not require prior shape information. The proposed algorithm is tested on 35 clinical image pairs from five MRE data sets, and is evaluated in comparison with manual contouring. The mean absolute distance between the automatic and manual contours is 1.8mm, with a maximum distance of 5.6mm. The relative area error is 7.6%, and the duration of the segmentation process is 2s per slice.

  2. Automated identification of the lung contours in positron emission tomography

    NASA Astrophysics Data System (ADS)

    Nery, F.; Silvestre Silva, J.; Ferreira, N. C.; Caramelo, F. J.; Faustino, R.

    2013-03-01

    Positron Emission Tomography (PET) is a nuclear medicine imaging technique that permits to analyze, in three dimensions, the physiological processes in vivo. One of the areas where PET has demonstrated its advantages is in the staging of lung cancer, where it offers better sensitivity and specificity than other techniques such as CT. On the other hand, accurate segmentation, an important procedure for Computer Aided Diagnostics (CAD) and automated image analysis, is a challenging task given the low spatial resolution and the high noise that are intrinsic characteristics of PET images. This work presents an algorithm for the segmentation of lungs in PET images, to be used in CAD and group analysis in a large patient database. The lung boundaries are automatically extracted from a PET volume through the application of a marker-driven watershed segmentation procedure which is robust to the noise. In order to test the effectiveness of the proposed method, we compared the segmentation results in several slices using our approach with the results obtained from manual delineation. The manual delineation was performed by nuclear medicine physicians that used a software routine that we developed specifically for this task. To quantify the similarity between the contours obtained from the two methods, we used figures of merit based on region and also on contour definitions. Results show that the performance of the algorithm was similar to the performance of human physicians. Additionally, we found that the algorithm-physician agreement is similar (statistically significant) to the inter-physician agreement.

  3. Segment alignment control system

    NASA Technical Reports Server (NTRS)

    Aubrun, JEAN-N.; Lorell, Ken R.

    1988-01-01

    The segmented primary mirror for the LDR will require a special segment alignment control system to precisely control the orientation of each of the segments so that the resulting composite reflector behaves like a monolith. The W.M. Keck Ten Meter Telescope will utilize a primary mirror made up of 36 actively controlled segments. Thus the primary mirror and its segment alignment control system are directly analogous to the LDR. The problems of controlling the segments in the face of disturbances and control/structures interaction, as analyzed for the TMT, are virtually identical to those for the LDR. The two systems are briefly compared.

  4. Adjusting the Contour of Reflector Panels

    NASA Technical Reports Server (NTRS)

    Palmer, W. B.; Giebler, M. M.

    1984-01-01

    Postfabrication adjustment of contour of panels for reflector, such as parabolic reflector for radio antennas, possible with simple mechanism consisting of threaded stud, two nuts, and flexure. Contours adjusted manually.

  5. Contoured Surface Eddy Current Inspection System

    DOEpatents

    Batzinger, Thomas James; Fulton, James Paul; Rose, Curtis Wayne; Perocchi, Lee Cranford

    2003-04-08

    Eddy current inspection of a contoured surface of a workpiece is performed by forming a backing piece of flexible, resiliently yieldable material with a contoured exterior surface conforming in shape to the workpiece contoured surface. The backing piece is preferably cast in place so as to conform to the workpiece contoured surface. A flexible eddy current array probe is attached to the contoured exterior surface of the backing piece such that the probe faces the contoured surface of the workpiece to be inspected when the backing piece is disposed adjacent to the workpiece. The backing piece is then expanded volumetrically by inserting at least one shim into a slot in the backing piece to provide sufficient contact pressure between the probe and the workpiece contoured surface to enable the inspection of the workpiece contoured surface to be performed.

  6. Whole abdominal wall segmentation using augmented active shape models (AASM) with multi-atlas label fusion and level set

    NASA Astrophysics Data System (ADS)

    Xu, Zhoubing; Baucom, Rebeccah B.; Abramson, Richard G.; Poulose, Benjamin K.; Landman, Bennett A.

    2016-03-01

    The abdominal wall is an important structure differentiating subcutaneous and visceral compartments and intimately involved with maintaining abdominal structure. Segmentation of the whole abdominal wall on routinely acquired computed tomography (CT) scans remains challenging due to variations and complexities of the wall and surrounding tissues. In this study, we propose a slice-wise augmented active shape model (AASM) approach to robustly segment both the outer and inner surfaces of the abdominal wall. Multi-atlas label fusion (MALF) and level set (LS) techniques are integrated into the traditional ASM framework. The AASM approach globally optimizes the landmark updates in the presence of complicated underlying local anatomical contexts. The proposed approach was validated on 184 axial slices of 20 CT scans. The Hausdorff distance against the manual segmentation was significantly reduced using proposed approach compared to that using ASM, MALF, and LS individually. Our segmentation of the whole abdominal wall enables the subcutaneous and visceral fat measurement, with high correlation to the measurement derived from manual segmentation. This study presents the first generic algorithm that combines ASM, MALF, and LS, and demonstrates practical application for automatically capturing visceral and subcutaneous fat volumes.

  7. Whole Abdominal Wall Segmentation using Augmented Active Shape Models (AASM) with Multi-Atlas Label Fusion and Level Set

    PubMed Central

    Xu, Zhoubing; Baucom, Rebeccah B.; Abramson, Richard G.; Poulose, Benjamin K.; Landman, Bennett A.

    2016-01-01

    The abdominal wall is an important structure differentiating subcutaneous and visceral compartments and intimately involved with maintaining abdominal structure. Segmentation of the whole abdominal wall on routinely acquired computed tomography (CT) scans remains challenging due to variations and complexities of the wall and surrounding tissues. In this study, we propose a slice-wise augmented active shape model (AASM) approach to robustly segment both the outer and inner surfaces of the abdominal wall. Multi-atlas label fusion (MALF) and level set (LS) techniques are integrated into the traditional ASM framework. The AASM approach globally optimizes the landmark updates in the presence of complicated underlying local anatomical contexts. The proposed approach was validated on 184 axial slices of 20 CT scans. The Hausdorff distance against the manual segmentation was significantly reduced using proposed approach compared to that using ASM, MALF, and LS individually. Our segmentation of the whole abdominal wall enables the subcutaneous and visceral fat measurement, with high correlation to the measurement derived from manual segmentation. This study presents the first generic algorithm that combines ASM, MALF, and LS, and demonstrates practical application for automatically capturing visceral and subcutaneous fat volumes. PMID:27127333

  8. Dilated contour extraction and component labeling algorithm for object vector representation

    NASA Astrophysics Data System (ADS)

    Skourikhine, Alexei N.

    2005-08-01

    Object boundary extraction from binary images is important for many applications, e.g., image vectorization, automatic interpretation of images containing segmentation results, printed and handwritten documents and drawings, maps, and AutoCAD drawings. Efficient and reliable contour extraction is also important for pattern recognition due to its impact on shape-based object characterization and recognition. The presented contour tracing and component labeling algorithm produces dilated (sub-pixel) contours associated with corresponding regions. The algorithm has the following features: (1) it always produces non-intersecting, non-degenerate contours, including the case of one-pixel wide objects; (2) it associates the outer and inner (i.e., around hole) contours with the corresponding regions during the process of contour tracing in a single pass over the image; (3) it maintains desired connectivity of object regions as specified by 8-neighbor or 4-neighbor connectivity of adjacent pixels; (4) it avoids degenerate regions in both background and foreground; (5) it allows an easy augmentation that will provide information about the containment relations among regions; (6) it has a time complexity that is dominantly linear in the number of contour points. This early component labeling (contour-region association) enables subsequent efficient object-based processing of the image information.

  9. Active fault, fault growth and segment linkage along the Janauri anticline (frontal foreland fold), NW Himalaya, India

    NASA Astrophysics Data System (ADS)

    Malik, Javed N.; Shah, Afroz A.; Sahoo, Ajit K.; Puhan, B.; Banerjee, Chiranjib; Shinde, Dattatraya P.; Juyal, Navin; Singhvi, Ashok K.; Rath, Shishir K.

    2010-03-01

    The 100 km long frontal foreland fold — the Janauri anticline in NW Himalayan foothills represents a single segment formed due to inter-linking of the southern (JS1) and the northern (JS2) Janauri segments. This anticline is a product of the fault related fold growth that facilitated lateral propagation by acquiring more length and linkage of smaller segments giving rise to a single large segment. The linked portion marked by flat-uplifted surface in the central portion represents the paleo-water gap of the Sutlej River. This area is comparatively more active in terms of tectonic activity, well justified by the occurrence of fault scarps along the forelimb and backlimb of the anticline. Occurrence of active fault scarps on either side of the anticline suggests that the slip accommodated in the frontal part is partitioned between the main frontal thrust i.e. the Himalayan Frontal Thrust (HFT) and associated back-thrust. The uplift in the piedmont zone along southern portion of Janauri anticline marked by dissected younger hill range suggests fore-landward propagation of tectonic activity along newly developed Frontal Piedmont Thrust (FPT), an imbricated emergent thrust branching out from the HFT system. We suggests that this happened because the southern segment JS1 does not linked-up with the northwestern end of Chandigarh anticline segment (CS). In the northwestern end of the Janauri anticline, due to no structural asperity the tectonic activity on HFT was taken-up by two (HF1 — in the frontal part and HF2 — towards the hinterland side) newly developed parallel active faults ( Hajipur Fault) branched from the main JS2 segment. The lateral propagation and movements along HF1 and HF2 resulted in uplift of the floodplain as well as responsible for the northward shift of the Beas River. GPR and trench investigations suggest that earthquakes during the recent past were accompanied with surface rupture. OSL (optical stimulated luminescence) dates from the trench

  10. The Poggendorff illusion driven by real and illusory contour: Behavioral and neural mechanisms.

    PubMed

    Shen, Lu; Zhang, Ming; Chen, Qi

    2016-05-01

    The Poggendorff illusion refers to the phenomenon that the human brain misperceives a diagonal line as being apparently misaligned once the diagonal line is interrupted by two parallel edges, and the size of illusion is negatively correlated with the angle of interception of the oblique, i.e. the sharper the oblique angle, the larger the illusion. This optical illusion can be produced by both real and illusory contour. In this fMRI study, by parametrically varying the oblique angle, we investigated the shared and specific neural mechanisms underlying the Poggendorff illusion induced by real and illusory contour. At the behavioral level, not only the real but also the illusory contours were capable of inducing significant Poggendorff illusion. The size of illusion induced by the real contour, however, was larger than that induced by the illusory contour. At the neural level, real and illusory contours commonly activated more dorsal visual areas, and the real contours specifically activated more ventral visual areas. More importantly, examinations on the parametric modulation effects of the size of illusion revealed the specific neural mechanisms underlying the Poggendorff illusion induced by the real and the illusory contours, respectively. Left precentral gyrus and right middle occipital cortex were specifically involved in the Poggendorff illusion induced by the real contour. On the other hand, bilateral intraparietal sulcus (IPS) and right lateral occipital complex (LOC) were specifically involved in the Poggendorff illusion induced by the illusory contour. Functional implications of the above findings were further discussed.

  11. Level set based vertebra segmentation for the evaluation of Ankylosing Spondylitis

    NASA Astrophysics Data System (ADS)

    Tan, Sovira; Yao, Jianhua; Ward, Michael M.; Yao, Lawrence; Summers, Ronald M.

    2006-03-01

    Ankylosing Spondylitis is a disease of the vertebra where abnormal bone structures (syndesmophytes) grow at intervertebral disk spaces. Because this growth is so slow as to be undetectable on plain radiographs taken over years, it is necessary to resort to computerized techniques to complement qualitative human judgment with precise quantitative measures on 3-D CT images. Very fine segmentation of the vertebral body is required to capture the small structures caused by the pathology. We propose a segmentation algorithm based on a cascade of three level set stages and requiring no training or prior knowledge. First, the noise inside the vertebral body that often blocks the proper evolution of level set surfaces is attenuated by a sigmoid function whose parameters are determined automatically. The 1st level set (geodesic active contour) is designed to roughly segment the interior of the vertebra despite often highly inhomogeneous and even discontinuous boundaries. The result is used as an initial contour for the 2nd level set (Laplacian level set) that closely captures the inner boundary of the cortical bone. The last level set (reversed Laplacian level set) segments the outer boundary of the cortical bone and also corrects small flaws of the previous stage. We carried out extensive tests on 30 vertebrae (5 from each of 6 patients). Two medical experts scored the results at intervertebral disk spaces focusing on end plates and syndesmophytes. Only two minor segmentation errors at vertebral end plates were reported and two syndesmophytes were considered slightly under-segmented.

  12. Improving semi-automated segmentation by integrating learning with active sampling

    NASA Astrophysics Data System (ADS)

    Huo, Jing; Okada, Kazunori; Brown, Matthew

    2012-02-01

    Interactive segmentation algorithms such as GrowCut usually require quite a few user interactions to perform well, and have poor repeatability. In this study, we developed a novel technique to boost the performance of the interactive segmentation method GrowCut involving: 1) a novel "focused sampling" approach for supervised learning, as opposed to conventional random sampling; 2) boosting GrowCut using the machine learned results. We applied the proposed technique to the glioblastoma multiforme (GBM) brain tumor segmentation, and evaluated on a dataset of ten cases from a multiple center pharmaceutical drug trial. The results showed that the proposed system has the potential to reduce user interaction while maintaining similar segmentation accuracy.

  13. Novel multimodality segmentation using level sets and Jensen-Rényi divergence

    SciTech Connect

    Markel, Daniel; Zaidi, Habib; El Naqa, Issam

    2013-12-15

    Purpose: Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy (IGART). This work presents a novel multimodality segmentation algorithm using the Jensen-Rényi divergence (JRD) to evolve the geometric level set contour. The algorithm offers improved noise tolerance which is particularly applicable to segmentation of regions found in PET and cone-beam computed tomography. Methods: A steepest gradient ascent optimization method is used in conjunction with the JRD and a level set active contour to iteratively evolve a contour to partition an image based on statistical divergence of the intensity histograms. The algorithm is evaluated using PET scans of pharyngolaryngeal squamous cell carcinoma with the corresponding histological reference. The multimodality extension of the algorithm is evaluated using 22 PET/CT scans of patients with lung carcinoma and a physical phantom scanned under varying image quality conditions. Results: The average concordance index (CI) of the JRD segmentation of the PET images was 0.56 with an average classification error of 65%. The segmentation of the lung carcinoma images had a maximum diameter relative error of 63%, 19.5%, and 14.8% when using CT, PET, and combined PET/CT images, respectively. The estimated maximal diameters of the gross tumor volume (GTV) showed a high correlation with the macroscopically determined maximal diameters, with aR{sup 2} value of 0.85 and 0.88 using the PET and PET/CT images, respectively. Results from the physical phantom show that the JRD is more robust to image noise compared to mutual information and region growing. Conclusions: The JRD has shown improved noise tolerance compared to mutual information for the purpose of PET image segmentation. Presented is a flexible

  14. A novel method for the automatic segmentation of activity data from a wrist worn device: Preliminary results.

    PubMed

    Amor, James D; Ahanathapillai, Vijayalakshmi; James, Christopher J

    2014-01-01

    Activity monitoring is used in a number of fields in order to assess the physical activity of the user. Applications include health and well-being, rehabilitation and enhancing independent living. Data are often gathered from multiple accelerometers and analysis focuses on multi-parametric classification. For longer term monitoring this is unsuitable and it is desirable to develop a method for the precise analysis of activity data with respect to time. This paper presents the initial results of a novel approach to this problem which is capable of segmenting activity data collected from a single accelerometer recording naturalized activity.

  15. CPM: a deformable model for shape recovery and segmentation based on charged particles.

    PubMed

    Jalba, Andrei C; Wilkinson, Michael H F; Roerdink, Jos B T M

    2004-10-01

    A novel, physically motivated deformable model for shape recovery and segmentation is presented. The model, referred to as the charged-particle model (CPM), is inspired by classical electrodynamics and is based on a simulation of charged particles moving in an electrostatic field. The charges are attracted towards the contours of the objects of interest by an electrostatic field, whose sources are computed based on the gradient-magnitude image. The electric field plays the same role as the potential forces in the snake model, while internal interactions are modeled by repulsive Coulomb forces. We demonstrate the flexibility and potential of the model in a wide variety of settings: shape recovery using manual initialization, automatic segmentation, and skeleton computation. We perform a comparative analysis of the proposed model with the active contour model and show that specific problems of the latter are surmounted by our model. The model is easily extendable to 3D and copes well with noisy images.

  16. Intonation contour in synchronous speech

    NASA Astrophysics Data System (ADS)

    Wang, Bei; Cummins, Fred

    2003-10-01

    Synchronous Speech (Syn-S), obtained by having pairs of speakers read a prepared text together, has been shown to result in interesting properties in the temporal domain, especially in the reduction of inter-speaker variability in supersegmental timing [F. Cummins, ARLO 3, 7-11 (2002)]. Here we investigate the effect of synchronization among speakers on the intonation contour, with a view to informing models of intonation. Six pairs of speakers (all females) read a short text (176 words) both synchronously and solo. Results show that (1) the pitch accent height above a declining baseline is reduced in Syn-S, compared with solo speech, while the pitch accent location is consistent across speakers in both conditions; (2) in contrast to previous findings on duration matching, there is an asymmetry between speakers, with one speaker exerting a stronger influence on the observed intonation contour than the other; (3) agreement on the boundaries of intonational phrases is greater in Syn-S and intonation contours are well matched from the first syllable of the phrase and throughout.

  17. SU-E-T-134: Dosimetric Implications From Organ Segmentation

    SciTech Connect

    Wu, Z; Turian, J; Chu, J

    2014-06-01

    Purpose: To evaluate the dosimetric implications resulting from organ segmentation performed by different clinical experts Methods: Twelve patients received SBRT treatment to thoracic region within the past year were selected for this study. Three physicians contoured a set of organs following RTOG guideline. DVHs of all contours were generated from the approved plans used for treatment, and were compared to those produced during planning. Most OARs were evaluated on their max dose, some, such as heart and chest wall, were also evaluated on metrics such as max dose to 4cc of volume, or 30Gy volume dose. Results: In general, there is a greater dosimetric difference between the RTOG contour sets and clinical contour sets than among the three RTOG contour sets themselves for each patient. For example, there was no difference in esophagus max dose between the RTOG contour sets for ten patients. However, they showed an average of 2.3% higher max dose than the clinical contour set, with a standard deviation of 6.6%. The proximal bronchial tree (PBT) showed a similar behavior. The average difference of PBT max dose for seven patients is 0% between the three RTOG contour sets, with standard deviation of 1%. They showed an average of 16.1% higher max dose than the clinical contour set, with a standard deviation of 126%. Conclusion: This study shows that using RTOG contouring standards improves segmentation consistency between different physicians; most of the contours examined showed less than 1% dose difference. When RTOG contour sets were compared to the clinical contour set, the differences are much more significant. Thus it is important to standardize contouring guidelines in radiation therapy treatment planning. This will reduce uncertainties in clinical outcome analysis and research studies.

  18. What is in a contour map? A region-based logical formalization of contour semantics

    USGS Publications Warehouse

    Usery, E. Lynn; Hahmann, Torsten

    2015-01-01

    This paper analyses and formalizes contour semantics in a first-order logic ontology that forms the basis for enabling computational common sense reasoning about contour information. The elicited contour semantics comprises four key concepts – contour regions, contour lines, contour values, and contour sets – and their subclasses and associated relations, which are grounded in an existing qualitative spatial ontology. All concepts and relations are illustrated and motivated by physical-geographic features identifiable on topographic contour maps. The encoding of the semantics of contour concepts in first-order logic and a derived conceptual model as basis for an OWL ontology lay the foundation for fully automated, semantically-aware qualitative and quantitative reasoning about contours.

  19. Generation algorithm of craniofacial structure contour in cephalometric images

    NASA Astrophysics Data System (ADS)

    Mondal, Tanmoy; Jain, Ashish; Sardana, H. K.

    2010-02-01

    Anatomical structure tracing on cephalograms is a significant way to obtain cephalometric analysis. Computerized cephalometric analysis involves both manual and automatic approaches. The manual approach is limited in accuracy and repeatability. In this paper we have attempted to develop and test a novel method for automatic localization of craniofacial structure based on the detected edges on the region of interest. According to the grey scale feature at the different region of the cephalometric images, an algorithm for obtaining tissue contour is put forward. Using edge detection with specific threshold an improved bidirectional contour tracing approach is proposed by an interactive selection of the starting edge pixels, the tracking process searches repetitively for an edge pixel at the neighborhood of previously searched edge pixel to segment images, and then craniofacial structures are obtained. The effectiveness of the algorithm is demonstrated by the preliminary experimental results obtained with the proposed method.

  20. SU-E-J-108: Solving the Chinese Postman Problem for Effective Contour Deformation

    SciTech Connect

    Yang, J; Zhang, L; Balter, P; Court, L; Zhang, Y; Dong, L

    2015-06-15

    Purpose: To develop a practical approach for accurate contour deformation when deformable image registration (DIR) is used for atlas-based segmentation or contour propagation in image-guided radiotherapy. Methods: A contour deformation approach was developed on the basis of 3D mesh operations. The 2D contours represented by a series of points in each slice were first converted to a 3D triangular mesh, which was deformed by the deformation vectors resulting from DIR. A set of parallel 2D planes then cut through the deformed 3D mesh, generating unordered points and line segments, which should be reorganized into a set of 2D contour points. It was realized that the reorganization problem was equivalent to solving the Chinese Postman Problem (CPP) by traversing a graph built from the unordered points with the least cost. Alternatively, deformation could be applied to a binary mask converted from the original contours. The deformed binary mask was then converted back into contours at the CT slice locations. We performed a qualitative comparison to validate the mesh-based approach against the image-based approach. Results: The DIR could considerably change the 3D mesh, making complicated 2D contour representations after deformation. CPP was able to effectively reorganize the points in 2D planes no matter how complicated the 2D contours were. The mesh-based approach did not require a post-processing of the contour, thus accurately showing the actual deformation in DIR. The mesh-based approach could keep some fine details and resulted in smoother contours than the image-based approach did, especially for the lung structure. Image-based approach appeared to over-process contours and suffered from image resolution limits. The mesh-based approach was integrated into in-house DIR software for use in routine clinic and research. Conclusion: We developed a practical approach for accurate contour deformation. The efficiency of this approach was demonstrated in both clinic and

  1. Grouping by proximity in haptic contour detection.

    PubMed

    Overvliet, Krista E; Krampe, Ralf Th; Wagemans, Johan

    2013-01-01

    We investigated the applicability of the Gestalt principle of perceptual grouping by proximity in the haptic modality. To do so, we investigated the influence of element proximity on haptic contour detection. In the course of four sessions ten participants performed a haptic contour detection task in which they freely explored a haptic random dot display that contained a contour in 50% of the trials. A contour was defined by a higher density of elements (raised dots), relative to the background surface. Proximity of the contour elements as well as the average proximity of background elements was systematically varied. We hypothesized that if proximity of contour elements influences haptic contour detection, detection will be more likely when contour elements are in closer proximity. This should be irrespective of the ratio with the proximity of the background elements. Results showed indeed that the closer the contour elements were, the higher the detection rates. Moreover, this was the case independent of the contour/background ratio. We conclude that the Gestalt law of proximity applies to haptic contour detection.

  2. Segmental organization of vestibulospinal inputs to spinal interneurons mediating crossed activation of thoracolumbar motoneurons in the neonatal mouse.

    PubMed

    Kasumacic, Nedim; Lambert, François M; Coulon, Patrice; Bras, Helene; Vinay, Laurent; Perreault, Marie-Claude; Glover, Joel C

    2015-05-27

    Vestibulospinal pathways activate contralateral motoneurons (MNs) in the thoracolumbar spinal cord of the neonatal mouse exclusively via axons descending ipsilaterally from the vestibular nuclei via the lateral vestibulospinal tract (LVST; Kasumacic et al., 2010). Here we investigate how transmission from the LVST to contralateral MNs is mediated by descending commissural interneurons (dCINs) in different spinal segments. We test the polysynaptic nature of this crossed projection by assessing LVST-mediated ventral root (VR) response latencies, manipulating synaptic responses pharmacologically, and tracing the pathway transynaptically from hindlimb extensor muscles using rabies virus (RV). Longer response latencies in contralateral than ipsilateral VRs, near-complete abolition of LVST-mediated calcium responses in contralateral MNs by mephenesin, and the absence of transsynaptic RV labeling of contralateral LVST neurons within a monosynaptic time window all indicate an overwhelmingly polysynaptic pathway from the LVST to contralateral MNs. Optical recording of synaptically mediated calcium responses identifies LVST-responsive ipsilateral dCINs that exhibit segmental differences in proportion and dorsoventral distribution. In contrast to thoracic and lower lumbar segments, in which most dCINs are LVST responsive, upper lumbar segments stand out because they contain a much smaller and more ventrally restricted subpopulation of LVST-responsive dCINs. A large proportion of these upper lumbar LVST-responsive dCINs project to contralateral L5, which contains many of the hindlimb extensor MNs activated by the LVST. A selective channeling of LVST inputs through segmentally and dorsoventrally restricted subsets of dCINs provides a mechanism for targeting vestibulospinal signals differentially to contralateral trunk and hindlimb MNs in the mammalian spinal cord.

  3. A novel approach to extract closed foreground object contours in video surveillance

    NASA Astrophysics Data System (ADS)

    Tzanidou, Giounona; Edirisinghe, Eran A.

    2014-03-01

    In this paper we present a novel approach for the detection of closed contours of foreground objects in videos. The proposed methodology begins with an initial localization of contours that is achieved via background subtraction technique that makes use of mixture of Gaussian distributions to model the background. The features that are used to realize an approximate foreground contour segmentation consist of magnitude of gradient at multiple orientations and phase congruency. In the next stage, canny edges of the incoming frames are computed at multiple scales and thresholds using the saturation and value components of HSV image. The approximate foreground contour is refined by reflecting it on the detected edges. A color ratio based noise and shadow line removal technique has been devised to remove the falsely segmented noise and strong shadow edges. Ultimately, to ensure closed contours, edge completion algorithm by anisotropic diffusion is applied. Once the contour is completed, it undergoes flood fill to define the foreground areas. Detailed experimental results on benchmark dataset showed that the proposed framework performs well in most of the different background scenarios. It effectively tackles the presence of shadows, illumination changes, some cases of dynamic background and thermal videos.

  4. Modelization of fetal cranial contour from ultrasound axial slices

    NASA Astrophysics Data System (ADS)

    Duquenoy, Eric; Taleb-Ahmed, Abdelmalik; Reboul, Serge; Beral, Y.; Dubus, Jean-Paul

    1995-10-01

    The problem of the choice of slices angles, at the time of diagnosis of brain fetal malformations, is linked to the position of the fetus inside the uterus. The 3D reconstruction of intern parts of the brain and especially the callosus corpus can help to detect some malformations. This kind of reconstruction pass by several steps that depend all on the initial segmentation step. The main difficulties of the segmentation are linked on the one hand to the inherent noise of ultrasound imaging and on the other hand to the matching of views of the 2D sequence to process. The 3D reconstruction stage require the definition of a marker in the sequence of process. In agreement with physicians, we have used the cranial contour as reference on the one hand because it is considered as invariable and fixed and on the other hand because of its more pronounced contrast (due to the fact of its cartilaginous nature) than the other structures. Nevertheless, the classic techniques of segmentations have remained without effect (open contour, too noisy). Therefore, we have developed an algorithm allowing to define automatically the ellipse. This method is based on a parametrically deformable model using elliptic FOURIER decomposition.

  5. Graph-based active learning of agglomeration (GALA): a Python library to segment 2D and 3D neuroimages.

    PubMed

    Nunez-Iglesias, Juan; Kennedy, Ryan; Plaza, Stephen M; Chakraborty, Anirban; Katz, William T

    2014-01-01

    The aim in high-resolution connectomics is to reconstruct complete neuronal connectivity in a tissue. Currently, the only technology capable of resolving the smallest neuronal processes is electron microscopy (EM). Thus, a common approach to network reconstruction is to perform (error-prone) automatic segmentation of EM images, followed by manual proofreading by experts to fix errors. We have developed an algorithm and software library to not only improve the accuracy of the initial automatic segmentation, but also point out the image coordinates where it is likely to have made errors. Our software, called gala (graph-based active learning of agglomeration), improves the state of the art in agglomerative image segmentation. It is implemented in Python and makes extensive use of the scientific Python stack (numpy, scipy, networkx, scikit-learn, scikit-image, and others). We present here the software architecture of the gala library, and discuss several designs that we consider would be generally useful for other segmentation packages. We also discuss the current limitations of the gala library and how we intend to address them. PMID:24772079

  6. Neuronal oscillations form parietal/frontal networks during contour integration.

    PubMed

    Castellano, Marta; Plöchl, Michael; Vicente, Raul; Pipa, Gordon

    2014-01-01

    The ability to integrate visual features into a global coherent percept that can be further categorized and manipulated are fundamental abilities of the neural system. While the processing of visual information involves activation of early visual cortices, the recruitment of parietal and frontal cortices has been shown to be crucial for perceptual processes. Yet is it not clear how both cortical and long-range oscillatory activity leads to the integration of visual features into a coherent percept. Here, we will investigate perceptual grouping through the analysis of a contour categorization task, where the local elements that form contour must be linked into a coherent structure, which is then further processed and manipulated to perform the categorization task. The contour formation in our visual stimulus is a dynamic process where, for the first time, visual perception of contours is disentangled from the onset of visual stimulation or from motor preparation, cognitive processes that until now have been behaviorally attached to perceptual processes. Our main finding is that, while local and long-range synchronization at several frequencies seem to be an ongoing phenomena, categorization of a contour could only be predicted through local oscillatory activity within parietal/frontal sources, which in turn, would synchronize at gamma (>30 Hz) frequency. Simultaneously, fronto-parietal beta (13-30 Hz) phase locking forms a network spanning across neural sources that are not category specific. Both long range networks, i.e., the gamma network that is category specific, and the beta network that is not category specific, are functionally distinct but spatially overlapping. Altogether, we show that a critical mechanism underlying contour categorization involves oscillatory activity within parietal/frontal cortices, as well as its synchronization across distal cortical sites.

  7. Neuronal oscillations form parietal/frontal networks during contour integration.

    PubMed

    Castellano, Marta; Plöchl, Michael; Vicente, Raul; Pipa, Gordon

    2014-01-01

    The ability to integrate visual features into a global coherent percept that can be further categorized and manipulated are fundamental abilities of the neural system. While the processing of visual information involves activation of early visual cortices, the recruitment of parietal and frontal cortices has been shown to be crucial for perceptual processes. Yet is it not clear how both cortical and long-range oscillatory activity leads to the integration of visual features into a coherent percept. Here, we will investigate perceptual grouping through the analysis of a contour categorization task, where the local elements that form contour must be linked into a coherent structure, which is then further processed and manipulated to perform the categorization task. The contour formation in our visual stimulus is a dynamic process where, for the first time, visual perception of contours is disentangled from the onset of visual stimulation or from motor preparation, cognitive processes that until now have been behaviorally attached to perceptual processes. Our main finding is that, while local and long-range synchronization at several frequencies seem to be an ongoing phenomena, categorization of a contour could only be predicted through local oscillatory activity within parietal/frontal sources, which in turn, would synchronize at gamma (>30 Hz) frequency. Simultaneously, fronto-parietal beta (13-30 Hz) phase locking forms a network spanning across neural sources that are not category specific. Both long range networks, i.e., the gamma network that is category specific, and the beta network that is not category specific, are functionally distinct but spatially overlapping. Altogether, we show that a critical mechanism underlying contour categorization involves oscillatory activity within parietal/frontal cortices, as well as its synchronization across distal cortical sites. PMID:25165437

  8. Neuronal oscillations form parietal/frontal networks during contour integration

    PubMed Central

    Castellano, Marta; Plöchl, Michael; Vicente, Raul; Pipa, Gordon

    2014-01-01

    The ability to integrate visual features into a global coherent percept that can be further categorized and manipulated are fundamental abilities of the neural system. While the processing of visual information involves activation of early visual cortices, the recruitment of parietal and frontal cortices has been shown to be crucial for perceptual processes. Yet is it not clear how both cortical and long-range oscillatory activity leads to the integration of visual features into a coherent percept. Here, we will investigate perceptual grouping through the analysis of a contour categorization task, where the local elements that form contour must be linked into a coherent structure, which is then further processed and manipulated to perform the categorization task. The contour formation in our visual stimulus is a dynamic process where, for the first time, visual perception of contours is disentangled from the onset of visual stimulation or from motor preparation, cognitive processes that until now have been behaviorally attached to perceptual processes. Our main finding is that, while local and long-range synchronization at several frequencies seem to be an ongoing phenomena, categorization of a contour could only be predicted through local oscillatory activity within parietal/frontal sources, which in turn, would synchronize at gamma (>30 Hz) frequency. Simultaneously, fronto-parietal beta (13–30 Hz) phase locking forms a network spanning across neural sources that are not category specific. Both long range networks, i.e., the gamma network that is category specific, and the beta network that is not category specific, are functionally distinct but spatially overlapping. Altogether, we show that a critical mechanism underlying contour categorization involves oscillatory activity within parietal/frontal cortices, as well as its synchronization across distal cortical sites. PMID:25165437

  9. Intraparenchymal hemorrhage segmentation from clinical head CT of patients with traumatic brain injury

    NASA Astrophysics Data System (ADS)

    Roy, Snehashis; Wilkes, Sean; Diaz-Arrastia, Ramon; Butman, John A.; Pham, Dzung L.

    2015-03-01

    Quantification of hemorrhages in head computed tomography (CT) images from patients with traumatic brain injury (TBI) has potential applications in monitoring disease progression and better understanding of the patho-physiology of TBI. Although manual segmentations can provide accurate measures of hemorrhages, the processing time and inter-rater variability make it infeasible for large studies. In this paper, we propose a fully automatic novel pipeline for segmenting intraparenchymal hemorrhages (IPH) from clinical head CT images. Unlike previous methods of model based segmentation or active contour techniques, we rely on relevant and matching examples from already segmented images by trained raters. The CT images are first skull-stripped. Then example patches from an "atlas" CT and its manual segmentation are used to learn a two-class sparse dictionary for hemorrhage and normal tissue. Next, for a given "subject" CT, a subject patch is modeled as a sparse convex combination of a few atlas patches from the dictionary. The same convex combination is applied to the atlas segmentation patches to generate a membership for the hemorrhages at each voxel. Hemorrhages are segmented from 25 subjects with various degrees of TBI. Results are compared with segmentations obtained from an expert rater. A median Dice coefficient of 0.85 between automated and manual segmentations is achieved. A linear fit between automated and manual volumes show a slope of 1.0047, indicating a negligible bias in volume estimation.

  10. Ladder contours are undetectable in the periphery: a crowding effect?

    PubMed

    May, Keith A; Hess, Robert F

    2007-10-29

    We studied the perceptual integration of contours consisting of Gabor elements positioned along a smooth path, embedded among distractor elements. Contour elements either formed tangents to the path ("snakes") or were perpendicular to it ("ladders"). Perfectly straight snakes and ladders were easily detected in the fovea but, at an eccentricity of 6 degrees , only the snakes were detectable. The disproportionate impairment of peripheral ladder detection remained when we brought foveal performance away from ceiling by jittering the orientations of the elements. We propose that the failure to detect peripheral ladders is a form of crowding, the phenomenon observed when identification of peripherally located letters is disrupted by flanking letters. D. G. Pelli, M. Palomares, and N. J. Majaj (2004) outlined a model in which simple feature detectors are followed by integration fields, which are involved in tasks, such as letter identification, that require the outputs of several detectors. They proposed that crowding occurs because small integration fields are absent from the periphery, leading to inappropriate feature integration by large peripheral integration fields. We argue that the "association field," which has been proposed to mediate contour integration (D. J. Field, A. Hayes, & R. F. Hess, 1993), is a type of integration field. Our data are explained by an elaboration of Pelli et al.'s model, in which weak ladder integration competes with strong snake integration. In the fovea, the association fields were small, and the model integrated snakes and ladders with little interference. In the periphery, the association fields were large, and integration of ladders was severely disrupted by interference from spurious snake contours. In contrast, the model easily detected snake contours in the periphery. In a further demonstration of the possible link between contour integration and crowding, we ran our contour integration model on groups of three-letter stimuli

  11. Geodynamic significance of the TRM segment in the East African Rift: active tectonics and paleostress in western Tanzania

    NASA Astrophysics Data System (ADS)

    Delvaux, D.; Kervyn, F.; Macheyeki, A. S.; Temu, E. B.

    2012-04-01

    The Tanganyika-Rukwa-Malawi (TRM) rift segment in western Tanzania is a key sector for understanding the opening dynamics of the East African rift system (EARS). In an oblique opening model, it is considered as a dextral transfer fault zone that accommodates the general opening of the EARS in a NW-SE direction. In an orthogonal opening model, it accommodates pure dip-slip normal faulting with extension orthogonal to the rift segments and a general E-W extension for the entire EARS. We investigated the active tectonic architecture and paleostress evolution of the Ufipa plateau and adjacent Rukwa basin and in order to define their geodynamic role in the development of the EARS and highlight their pre-rift brittle tectonic history. The active fault architecture, fault-kinematic analysis and paleostress reconstruction show that the recent to active fault systems that control the rift structure develop in a pure extensional setting with extension direction orthogonal to the trend of the TRM segment. Two pre-rift brittle events are evidenced. An older brittle thrusting is related to the interaction between the Bangweulu block and the Tanzanian craton during the late Pan-African (early Paleozoic). It was followed by a transpressional inversion during the early Mesozoic. This inversion stage caused dextral strike-slip faulting along the fault systems that now control the major rift structures. It has been erroneously interpreted as related to the late Cenozoic EARS which instead is characterized by pure normal faulting.

  12. Assessing outcomes in body contouring.

    PubMed

    Klassen, Anne F; Cano, Stefan J; Scott, Amie; Tsangaris, Elena; Pusic, Andrea L

    2014-10-01

    Patient-reported outcome (PRO) instruments are questionnaires designed to measure outcomes of importance to patients from their perspective. This article describes the methods used to develop a new PRO instrument for obese patients and patients having bariatric and cosmetic body contouring surgery. The BODY-Q is composed of 19 newly designed scales that measure: (1) appearance; (2) health-related quality of life; and (3) process of care. Recommended guidelines for PRO instrument development were followed to ensure that the BODY-Q meets requirements of regulatory bodies. The BODY-Q is currently being field-tested in an international study.

  13. Both predictability and familiarity facilitate contour integration.

    PubMed

    Sassi, Michaël; Demeyer, Maarten; Machilsen, Bart; Putzeys, Tom; Wagemans, Johan

    2014-05-30

    Research has shown that contour detection is impaired in the visual periphery for snake-shaped Gabor contours but not for circular and elliptical contours. This discrepancy in findings could be due to differences in intrinsic shape properties, including shape closure and curvature variation, as well as to differences in stimulus predictability and familiarity. In a detection task using only circular contours, the target shape is both more familiar and more predictable to the observer compared with a detection task in which a different snake-shaped contour is presented on each trial. In this study, we investigated the effects of stimulus familiarity and predictability on contour integration by manipulating and disentangling the familiarity and predictability of snakelike stimuli. We manipulated stimulus familiarity by extensively training observers with one particular snake shape. Predictability was varied by alternating trial blocks with only a single target shape and trial blocks with multiple target shapes. Our results show that both predictability and familiarity facilitated contour integration, which constitutes novel behavioral evidence for the adaptivity of the contour integration mechanism in humans. If familiarity or predictability facilitated contour integration in the periphery specifically, this could explain the discrepant findings obtained with snake contours as compared with circles or ellipses. However, we found that their facilitatory effects did not differ between central and peripheral vision and thus cannot explain that particular discrepancy in the literature.

  14. A Neurocomputational account of the role of contour facilitation in brightness perception.

    PubMed

    Domijan, Dražen

    2015-01-01

    A new filling-in model is proposed in order to account for challenging brightness illusions, where inducing background elements are spatially separated from the gray target such as dungeon, cube and grating illusions, bullseye display and ring patterns. This model implements the simple idea that neural response to low-contrast contour is enhanced (facilitated) by the presence of collinear or parallel high-contrast contours in its wider neighborhood. Contour facilitation is achieved via dendritic inhibition, which enables the computation of maximum function among inputs to the node. Recurrent application of maximum function leads to the propagation of the neural signal along collinear or parallel contour segments. When a strong global-contour signal is accompanied with a weak local-contour signal at the same location, conditions are met to produce brightness assimilation within the Filling-in Layer. Computer simulations showed that the model correctly predicts brightness appearance in all of the aforementioned illusions as well as in White's effect, Benary's cross, Todorović's illusion, checkerboard contrast, contrast-contrast illusion and various variations of the White's effect. The proposed model offers new insights on how geometric factors (contour colinearity or parallelism), together with contrast magnitude contribute to the brightness perception.

  15. Age, Episodicity and Migration of Hydrothermal Activity within the Axial Valley, Endeavour Segment, Juan de Fuca Ridge

    NASA Astrophysics Data System (ADS)

    Jamieson, J. W.; Hannington, M. D.; Kelley, D. S.; Clague, D. A.; Holden, J. F.; Tivey, M. K.; Delaney, J. R.

    2011-12-01

    Hydrothermal sulfide deposits record the history of high-temperature venting along the Endeavour Segment. Active venting is currently located within five discreet vent fields, with minor diffuse venting occurring between the fields. However, inactive and/or extinct sulfide structures are found throughout the entire axial valley of the ridge segment, suggesting that hydrothermal activity has been more vigorous in the past or focused venting has migrated with time. Here, we present age constraints from U-series dating of 44 sulfide samples collected by manned submersible from between the Mothra Field in the south to Sasquatch in the north. Samples are dated using 226Ra/Ba ratios from hydrothermal barite that precipitates along with the sulfide minerals. Most samples have been collected from within or near the active vent fields. Fifteen samples from the Main Endeavour Field (MEF) show a spectrum of ages from present to 2,430 years old, indicating that this field has been continuously active for at least ~2,400 years. MEF appears to be oldest currently active field. This minimum value for the age of hydrothermal activity also provides a minimum age of the axial valley itself. Ages from thirteen samples from the High-Rise Field indicate continuous venting for at least the past ~1,250 years. These age data are used in conjunction with age constraints of the volcanic flows to develop an integrated volcanic, hydrothermal and tectonic history of the Endeavour Segment. The total volume of hydrothermal sulfide within the axial valley, determined from high-resolution bathymetry, is used in conjunction with the age constraints of the sulfide material to determine the mass accumulation rates of sulfide along the Endeavour Segment. These data can be used to calibrate the efficiency of sulfide deposition from the hydrothermal vents, and provide a time-integrated history of heat, fluid and chemical fluxes at the ridge-segment scale. The comparison of time-integrated rates with

  16. Edge enhancement nucleus and cytoplast contour detector of cervical smear images.

    PubMed

    Yang-Mao, Shys-Fan; Chan, Yung-Kuan; Chu, Yen-Ping

    2008-04-01

    This paper presents an edge enhancement nucleus and cytoplast contour (EENCC) detector to enable cutting the nucleus and cytoplast from a cervical smear cell image. To clean up noises from an image, this paper proposes a trim-meaning filter that can effectively remove impulse and Gaussian noises but still preserves the sharpness of object boundaries. In addition, a bigroup enhancer is proposed to make a clear-cut separation of the pixels lying in-between two objects. A mean vector difference enhancer is presented to suppress the gradients of noises and also to brighten the gradients of object contours. What is more, a relative-distance-error measure is put forward to evaluate the segmentation error between the extracted and target object contours. The experimental results show that all the aforementioned techniques proposed have performed impressively. Other than for cervical smear images, these proposed techniques can also be utilized in object segmentation of other images.

  17. An elastic contour matching model for tropical cyclone pattern recognition.

    PubMed

    Lee, R T; Lin, J K

    2001-01-01

    In this paper, an elastic graph dynamic link model (EGDLM) based on elastic contour matching is proposed to automate the Dvorak technique for tropical cyclone (TC) pattern interpretation from satellite images. This method integrates traditional dynamic link architecture (DLA) for neural dynamics and the active contour model (ACM) for contour extraction of TC patterns. Using satellite pictures provided by National Oceanic and Atmospheric Administration (NOAA), 120 tropical cyclone cases that appeared in the period from 1990 to 1998 were extracted for the study. An overall correct rate for TC classification was found to be above 95%. For hurricanes with distinct "eye" formation, the model reported a deviation within 3 km from the "actual eye" location, which was obtained from the aircraft measurement of minimum surface pressure by reconnaissance. Compared with the classical DLA model, the proposed model has simplified the feature representation, the network initialization, and the training process. This leads to a tremendous improvement of recognition performance by more than 1000 times.

  18. Segmentation and quantitative evaluation of brain MRI data with a multiphase 3D implicit deformable model

    NASA Astrophysics Data System (ADS)

    Angelini, Elsa D.; Song, Ting; Mensh, Brett D.; Laine, Andrew

    2004-05-01

    Segmentation of three-dimensional anatomical brain images into tissue classes has applications in both clinical and research settings. This paper presents the implementation and quantitative evaluation of a four-phase three-dimensional active contour implemented with a level set framework for automated segmentation of brain MRIs. The segmentation algorithm performs an optimal partitioning of three-dimensional data based on homogeneity measures that naturally evolves to the extraction of different tissue types in the brain. Random seed initialization was used to speed up numerical computation and avoid the need for a priori information. This random initialization ensures robustness of the method to variation of user expertise, biased a priori information and errors in input information that could be influenced by variations in image quality. Experimentation on three MRI brain data sets showed that an optimal partitioning successfully labeled regions that accurately identified white matter, gray matter and cerebrospinal fluid in the ventricles. Quantitative evaluation of the segmentation was performed with comparison to manually labeled data and computed false positive and false negative assignments of voxels for the three organs. We report high accuracy for the two comparison cases. These results demonstrate the efficiency and flexibility of this segmentation framework to perform the challenging task of automatically extracting brain tissue volume contours.

  19. Perceptual mass segmentation using eye-tracking and seed-growing

    NASA Astrophysics Data System (ADS)

    Ke, Erting; Liu, Wei; Xu, Weidong; Li, Lihua; Zheng, Bin; Zhang, Juan; Zhang, Lingnan

    2012-03-01

    In the paper, we propose a novel scheme for breast mass segmentation in mammography, which is based on visual perception and consists of two steps. Firstly, radiologists' eye-gazing data is recorded by the eye-tracker during reading and then clustered with a density-based spatial clustering of applications with noise (DBSCAN) algorithm to achieve seeds locating radiologists' regions of interest (ROIs). The seeds-based region growing (SBRG) algorithm is applied to buckle ROIs containing suspicious lesions. Secondly, in order to achieve fine lesion contour as final result, the ROIs are segmented with a multi-scale mass segmentation approach using active contour models. The result of applying the proposed method to the mammograms from both DDSM and Zhejiang Cancer Hospital shows that the achieved average of overlap rate is 0.5915 and the achieved average of misclassification rate is 0.6342. The innovative point of the proposed approach is to introduce visual perception into breast mass segmentation, which makes the result of mass segmentation meet radiologists' subjective demand.

  20. Antenna surface contour control system

    NASA Astrophysics Data System (ADS)

    Ahl, Elvin L.; Miller, James B.

    1989-03-01

    The invention is a system for automatically controlling the surface contour of a deployable and restowable antenna having a mesh reflector surface supported by a circular, folding hoop affixed to a central, telescoping column. The antenna, when deployed, forms a quad-aperture reflector with each quadrant of the mesh surface shaped to provide an offset parabolic radio frequency (RF) reflector. The hoop is supported and positioned by quartz support cords attached to the top of a column and by lower graphite hoop control cords that extend between the hoop and base of the column. The antenna, an RF reflective surface, is a gold plated molybdenum wire mesh supported on a graphite cord truss structure that includes the hoop control cords and a plurality of surface control cords attached at selected points on the surface and to the base of the column. The contour of the three-dimensional surface of the antenna is controlled by selectively adjusting the lengths of the surface control cords and the graphite hoop control cords by means of novel actuator assemblies that automatically sense and change the lengths of the lower hoop control cords and surface control cords.

  1. Antenna surface contour control system

    NASA Technical Reports Server (NTRS)

    Ahl, Elvin L. (Inventor); Miller, James B. (Inventor)

    1989-01-01

    The invention is a system for automatically controlling the surface contour of a deployable and restowable antenna having a mesh reflector surface supported by a circular, folding hoop affixed to a central, telescoping column. The antenna, when deployed, forms a quad-aperture reflector with each quadrant of the mesh surface shaped to provide an offset parabolic radio frequency (RF) reflector. The hoop is supported and positioned by quartz support cords attached to the top of a column and by lower graphite hoop control cords that extend between the hoop and base of the column. The antenna, an RF reflective surface, is a gold plated molybdenum wire mesh supported on a graphite cord truss structure that includes the hoop control cords and a plurality of surface control cords attached at selected points on the surface and to the base of the column. The contour of the three-dimensional surface of the antenna is controlled by selectively adjusting the lengths of the surface control cords and the graphite hoop control cords by means of novel actuator assemblies that automatically sense and change the lengths of the lower hoop control cords and surface control cords.

  2. Projection moire for remote contour analysis

    NASA Technical Reports Server (NTRS)

    Doty, J. L.

    1983-01-01

    Remote projection and viewing of moire contours are examined analytically for a system employing separate projection and viewing optics, with specific attention paid to the practical limitations imposed by the optical systems. It is found that planar contours are possible only when the optics are telecentric (exit pupil at infinity) but that the requirement for spatial separability of the contour fringes from extraneous fringes is independent of the specific optics and is a function only of the angle separating the two optic axes. In the nontelecentric case, the contour separation near the object is unchanged from that of the telecentric case, although the contours are distorted into low-eccentricity (near-circular) ellipses. Furthermore, the minimum contour spacing is directly related to the depth of focus through the resolution of the optics.

  3. Contouring variability of human- and deformable-generated contours in radiotherapy for prostate cancer

    NASA Astrophysics Data System (ADS)

    Gardner, Stephen J.; Wen, Ning; Kim, Jinkoo; Liu, Chang; Pradhan, Deepak; Aref, Ibrahim; Cattaneo, Richard, II; Vance, Sean; Movsas, Benjamin; Chetty, Indrin J.; Elshaikh, Mohamed A.

    2015-06-01

    This study was designed to evaluate contouring variability of human-and deformable-generated contours on planning CT (PCT) and CBCT for ten patients with low-or intermediate-risk prostate cancer. For each patient in this study, five radiation oncologists contoured the prostate, bladder, and rectum, on one PCT dataset and five CBCT datasets. Consensus contours were generated using the STAPLE method in the CERR software package. Observer contours were compared to consensus contour, and contour metrics (Dice coefficient, Hausdorff distance, Contour Distance, Center-of-Mass [COM] Deviation) were calculated. In addition, the first day CBCT was registered to subsequent CBCT fractions (CBCTn: CBCT2-CBCT5) via B-spline Deformable Image Registration (DIR). Contours were transferred from CBCT1 to CBCTn via the deformation field, and contour metrics were calculated through comparison with consensus contours generated from human contour set. The average contour metrics for prostate contours on PCT and CBCT were as follows: Dice coefficient—0.892 (PCT), 0.872 (CBCT-Human), 0.824 (CBCT-Deformed); Hausdorff distance—4.75 mm (PCT), 5.22 mm (CBCT-Human), 5.94 mm (CBCT-Deformed); Contour Distance (overall contour)—1.41 mm (PCT), 1.66 mm (CBCT-Human), 2.30 mm (CBCT-Deformed); COM Deviation—2.01 mm (PCT), 2.78 mm (CBCT-Human), 3.45 mm (CBCT-Deformed). For human contours on PCT and CBCT, the difference in average Dice coefficient between PCT and CBCT (approx. 2%) and Hausdorff distance (approx. 0.5 mm) was small compared to the variation between observers for each patient (standard deviation in Dice coefficient of 5% and Hausdorff distance of 2.0 mm). However, additional contouring variation was found for the deformable-generated contours (approximately 5.0% decrease in Dice coefficient and 0.7 mm increase in Hausdorff distance relative to human-generated contours on CBCT). Though deformable contours provide a reasonable starting point for contouring on

  4. An adipose segmentation and quantification scheme for the intra abdominal region on minipigs

    NASA Astrophysics Data System (ADS)

    Engholm, Rasmus; Dubinskiy, Aleksandr; Larsen, Rasmus; Hanson, Lars G.; Christoffersen, Berit Østergaard

    2006-03-01

    This article describes a method for automatic segmentation of the abdomen into three anatomical regions: subcutaneous, retroperitoneal and visceral. For the last two regions the amount of adipose tissue (fat) is quantified. According to recent medical research, the distinction between retroperitoneal and visceral fat is important for studying metabolic syndrome, which is closely related to diabetes. However previous work has neglected to address this point, treating the two types of fat together. We use T1-weighted three-dimensional magnetic resonance data of the abdomen of obese minipigs. The pigs were manually dissected right after the scan, to produce the "ground truth" segmentation. We perform automatic segmentation on a representative slice, which on humans has been shown to correlate with the amount of adipose tissue in the abdomen. The process of automatic fat estimation consists of three steps. First, the subcutaneous fat is removed with a modified active contour approach. The energy formulation of the active contour exploits the homogeneous nature of the subcutaneous fat and the smoothness of the boundary. Subsequently the retroperitoneal fat located around the abdominal cavity is separated from the visceral fat. For this, we formulate a cost function on a contour, based on intensities, edges, distance to center and smoothness, so as to exploit the properties of the retroperitoneal fat. We then globally optimize this function using dynamic programming. Finally, the fat content of the retroperitoneal and visceral regions is quantified based on a fuzzy c-means clustering of the intensities within the segmented regions. The segmentation proved satisfactory by visual inspection, and closely correlated with the manual dissection data. The correlation was 0.89 for the retroperitoneal fat, and 0.74 for the visceral fat.

  5. A program for contouring randomly spaced data

    NASA Technical Reports Server (NTRS)

    Hamm, R. W.; Kibler, J. F.; Morris, W. D.

    1975-01-01

    A description is given of a digital computer program which prepares contour plots of three dimensional data. The contouring technique uses a triangulation procedure. As presently configured, the program can accept up to 56,000 randomly spaced data points, although the required computer resources may be prohibitive. However, with relatively minor internal modifications, the program can handle essentially unlimited amounts of data. Up to 20 contouring intervals can be selected and contoured with either polygonal lines or smooth curves. Sample cases are illustrated. A general description of the main program and primary level subroutines is included to permit simple modifications of the program.

  6. CONTOUR. Stress Time History Postprocessor Plotting Program

    SciTech Connect

    Pelessone, D.

    1993-11-01

    CONTOUR is an in-house computer program which is used at General Atomics to generate contour plots of analysis results obtained from various finite element codes used in stress and thermal analysis of core fuel blocks. The program provides contour and fringe plots of the results in either black and white or color. The input data for CONTOUR is CONDRUM, a word addressable file generated by codes which contain element stresses and nodal displacements such as TWOD and PRINT2. TWOD is a finite element program for linear and nonlinear stress analysis of two-dimensional and axisymmetric solids. PRINT2 is an output processor code for printing data.

  7. Hydrothermal activity along the slow-spreading Lucky Strike ridge segment (Mid-Atlantic Ridge): Distribution, heatflux, and geological controls

    NASA Astrophysics Data System (ADS)

    Escartin, J.; Barreyre, T.; Cannat, M.; Garcia, R.; Gracias, N.; Deschamps, A.; Salocchi, A.; Sarradin, P. M.; Ballu, V.

    2015-12-01

    We have reviewed available visual information from the seafloor, and recently acquired microbathymetry for several traverses across the Lucky Strike segment to evaluate the distribution of hydrothermal activity. The Lucky Strike segment hosts three active hydrothermal fields: Capelinhos, Ewan, and the known Main Lucky Strike Hydrothermal Field (MLSHF). Capelinhos is located 1.3 km E of the axis and the MLSHF, and consists of a ~20 m sulfide mound with black smoker vents. Ewan is located ~1.8 km south from the MLSHF along the axial graben, and displays only diffuse flow along and around scarps of collapse structures associated with fault scarps. At the MLSHF we have identified an inactive site, thus broadening the extent of this field. Heat flux estimates from these new sites are relatively low and correspond to ~10% of the heat flux estimated for the Main field, with an integrated heatflux of 200-1200 MW. Overall, most of the flux (up to 80-90%) is associated with diffuse outflow, with the Ewan site showing solely diffuse flow and Capelinhos mostly focused flow. Microbathymetry also reveals a large, off-axis (~2.4 km) hydrothermal field, similar to the TAG mound in size, on the flanks of a rifted volcano. The association of these fields to a central volcano, and the absence of indicators of hydrothermal activity along the ridge segment, suggest that sustained hydrothermal activity is maintained by the enhanced melt supply and the associated magma chamber(s) required to build central volcanoes. Hydrothermal outflow zones at the seafloor are systematically controlled by faults, indicating that hydrothermal circulation in the shallow crust exploits permeable fault zones. Central volcanoes are thus associated with long-lived hydrothermal activity, and these sites may play a major role in the distribution and biogeography of vent communities.

  8. Creation of digital contours that approach the characteristics of cartographic contours

    USGS Publications Warehouse

    Tyler, Dean J.; Greenlee, Susan K.

    2012-01-01

    The capability to easily create digital contours using commercial off-the-shelf (COTS) software has existed for decades. Out-of-the-box raw contours are suitable for many scientific applications without pre- or post-processing; however, cartographic applications typically require additional improvements. For example, raw contours generally require smoothing before placement on a map. Cartographic contours must also conform to certain spatial/logical rules; for example, contours may not cross waterbodies. The objective was to create contours that match as closely as possible the cartographic contours produced by manual methods on the 1:24,000-scale, 7.5-minute Topographic Map series. This report outlines the basic approach, describes a variety of problems that were encountered, and discusses solutions. Many of the challenges described herein were the result of imperfect input raster elevation data and the requirement to have the contours integrated with hydrographic features from the National Hydrography Dataset (NHD).

  9. Segmentation and classification of cell cycle phases in fluorescence imaging.

    PubMed

    Ersoy, Ilker; Bunyak, Filiz; Chagin, Vadim; Cardoso, M Christina; Palaniappan, Kannappan

    2009-01-01

    Current chemical biology methods for studying spatiotemporal correlation between biochemical networks and cell cycle phase progression in live-cells typically use fluorescence-based imaging of fusion proteins. Stable cell lines expressing fluorescently tagged protein GFP-PCNA produce rich, dynamically varying sub-cellular foci patterns characterizing the cell cycle phases, including the progress during the S-phase. Variable fluorescence patterns, drastic changes in SNR, shape and position changes and abundance of touching cells require sophisticated algorithms for reliable automatic segmentation and cell cycle classification. We extend the recently proposed graph partitioning active contours (GPAC) for fluorescence-based nucleus segmentation using regional density functions and dramatically improve its efficiency, making it scalable for high content microscopy imaging. We utilize surface shape properties of GFP-PCNA intensity field to obtain descriptors of foci patterns and perform automated cell cycle phase classification, and give quantitative performance by comparing our results to manually labeled data.

  10. Cortical Contributions to Impaired Contour Integration in Schizophrenia

    PubMed Central

    Silverstein, Steven M.; Harms, Michael P.; Carter, Cameron S.; Gold, James M.; Keane, Brian P.; MacDonald, Angus; Ragland, J. Daniel; Barch, Deanna M.

    2015-01-01

    Objectives Visual perceptual organization impairments in schizophrenia (SCZ) are well established, but their neurobiological bases are not. The current study used the previously validated Jittered Orientation Visual Integration (JOVI) task, along with fMRI, to examine the neural basis of contour integration (CI), and its impairment in SCZ. CI is an aspect of perceptual organization in which multiple distinct oriented elements are grouped into a single continuous boundary or shape. Methods On the JOVI, five levels of orientational jitter were added to non-contiguous closed contour elements embedded in background noise to progressively increase the difficulty in perceiving contour elements as left- or right-pointing ovals. Multi-site fMRI data were analyzed for 56 healthy control subjects and 47 people with SCZ. Results SCZ patients demonstrated poorer CI, and this was associated with increased activation in regions involved in global shape processing and visual attention, namely the lateral occipital complex and superior parietal lobules. There were no brain regions where controls demonstrated more activation than patients. Conclusions CI impairment in this sample of outpatients with SCZ was related to excessive activation in regions associated with object processing and allocation of visual-spatial attention. There was no evidence for basic impairments in contour element linking in the fMRI data. The latter may be limited to poor outcome patients, where more extensive structural and functional changes in the occipital lobe have been observed. PMID:26160288

  11. MRI brain tumor segmentation and necrosis detection using adaptive Sobolev snakes

    NASA Astrophysics Data System (ADS)

    Nakhmani, Arie; Kikinis, Ron; Tannenbaum, Allen

    2014-03-01

    Brain tumor segmentation in brain MRI volumes is used in neurosurgical planning and illness staging. It is important to explore the tumor shape and necrosis regions at di erent points of time to evaluate the disease progression. We propose an algorithm for semi-automatic tumor segmentation and necrosis detection. Our algorithm consists of three parts: conversion of MRI volume to a probability space based on the on-line learned model, tumor probability density estimation, and adaptive segmentation in the probability space. We use manually selected acceptance and rejection classes on a single MRI slice to learn the background and foreground statistical models. Then, we propagate this model to all MRI slices to compute the most probable regions of the tumor. Anisotropic 3D di usion is used to estimate the probability density. Finally, the estimated density is segmented by the Sobolev active contour (snake) algorithm to select smoothed regions of the maximum tumor probability. The segmentation approach is robust to noise and not very sensitive to the manual initialization in the volumes tested. Also, it is appropriate for low contrast imagery. The irregular necrosis regions are detected by using the outliers of the probability distribution inside the segmented region. The necrosis regions of small width are removed due to a high probability of noisy measurements. The MRI volume segmentation results obtained by our algorithm are very similar to expert manual segmentation.

  12. [Signal processing in contour implants].

    PubMed

    Ormezzano, Y; Deleurme, C; Vormès, E; Frachet, B

    1990-01-01

    Signal processing by cochlear implants is aimed at transmitting all the acoustic information carried by the human voice, whether in its semantic, esthetic or affective aspects, as an electrical signal. The "translating" approach, which encodes the signal according to the characteristics of the sounds, can only be ideally used in multiple-canal implants. On the contrary, our experience with various single-canal prostheses shows that our patients choose one of these according to the comfort of the signal and to its reliability rather than to the complexity of signal processing: all prostheses produce approximately the same results, whatever the method implemented. The contour implant allows an easy, effective and well-tolerated fitting at low costs.

  13. Body Contouring After Bariatric Surgery.

    PubMed

    Ellison, Jo M; Steffen, Kristine J; Sarwer, David B

    2015-11-01

    Individuals who undergo bariatric surgery generally experience rapid and dramatic weight loss. While the weight loss typically confers significant health benefits, an undesirable consequence is often excessive quantities of hanging, surplus skin. Some patients undergo body-contouring surgery (BCS) in order to improve health, mobility, appearance and psychological adjustment. While the majority of post-bariatric patients desire BCS in one or more body regions, a small percentage of patients receive such surgeries. Lack of knowledge about procedures, cost and (in the USA and several other countries) difficulty obtaining insurance reimbursement likely prevents many patients from undergoing BCS. Those who do undergo BCS appear to be at heightened risk for wound-healing complications. Despite these complications, the majority of patients report satisfactory BCS outcomes. The extant literature in this area provides a great deal of information about these issues; nevertheless, additional research is needed to further inform clinical management and improve patient outcomes.

  14. Sodium Deoxycholate for Submental Contouring.

    PubMed

    Humphrey, S; Beleznay, K; Beleznay, J D A

    2016-09-01

    The chin and jaw line are integral parts of an individual's aesthetic profile, and the presence of submental fat detracts from this and can lead to displeasure with one's facial appearance. While liposuction and cosmetic surgery are regarded as the gold standard in treating submental fat, surgical intervention is not appealing to all patients and has potential surgical complications including longer recovery, and contour irregularities. Despite ample advances in aesthetic medicine to enhance the appearance of the face, very little is available in non-invasive options to reduce submental fat that has been supported by robust evidence. ATX-101, a proprietary formulation of deoxycholic acid that is synthetically derived, has been extensively explored in a vigorous clinical development program that has established the safety and efficacy of the injectable. It has recently received approval by regulatory authorities in Canada (Belkyra™) and the US (Kybella®) for the treatment of submental fat. PMID:27603325

  15. Body Contouring After Bariatric Surgery.

    PubMed

    Ellison, Jo M; Steffen, Kristine J; Sarwer, David B

    2015-11-01

    Individuals who undergo bariatric surgery generally experience rapid and dramatic weight loss. While the weight loss typically confers significant health benefits, an undesirable consequence is often excessive quantities of hanging, surplus skin. Some patients undergo body-contouring surgery (BCS) in order to improve health, mobility, appearance and psychological adjustment. While the majority of post-bariatric patients desire BCS in one or more body regions, a small percentage of patients receive such surgeries. Lack of knowledge about procedures, cost and (in the USA and several other countries) difficulty obtaining insurance reimbursement likely prevents many patients from undergoing BCS. Those who do undergo BCS appear to be at heightened risk for wound-healing complications. Despite these complications, the majority of patients report satisfactory BCS outcomes. The extant literature in this area provides a great deal of information about these issues; nevertheless, additional research is needed to further inform clinical management and improve patient outcomes. PMID:26395601

  16. Cellular image segmentation using n-agent cooperative game theory

    NASA Astrophysics Data System (ADS)

    Dimock, Ian B.; Wan, Justin W. L.

    2016-03-01

    Image segmentation is an important problem in computer vision and has significant applications in the segmentation of cellular images. Many different imaging techniques exist and produce a variety of image properties which pose difficulties to image segmentation routines. Bright-field images are particularly challenging because of the non-uniform shape of the cells, the low contrast between cells and background, and imaging artifacts such as halos and broken edges. Classical segmentation techniques often produce poor results on these challenging images. Previous attempts at bright-field imaging are often limited in scope to the images that they segment. In this paper, we introduce a new algorithm for automatically segmenting cellular images. The algorithm incorporates two game theoretic models which allow each pixel to act as an independent agent with the goal of selecting their best labelling strategy. In the non-cooperative model, the pixels choose strategies greedily based only on local information. In the cooperative model, the pixels can form coalitions, which select labelling strategies that benefit the entire group. Combining these two models produces a method which allows the pixels to balance both local and global information when selecting their label. With the addition of k-means and active contour techniques for initialization and post-processing purposes, we achieve a robust segmentation routine. The algorithm is applied to several cell image datasets including bright-field images, fluorescent images and simulated images. Experiments show that the algorithm produces good segmentation results across the variety of datasets which differ in cell density, cell shape, contrast, and noise levels.

  17. Hydrothermal activity along the slow-spreading Lucky Strike ridge segment (Mid-Atlantic Ridge): Distribution, heatflux, and geological controls

    NASA Astrophysics Data System (ADS)

    Escartin, J.; Barreyre, T.; Cannat, M.; Garcia, R.; Gracias, N.; Deschamps, A.; Salocchi, A.; Sarradin, P.-M.; Ballu, V.

    2015-12-01

    We have reviewed available visual information from the seafloor, and recently acquired microbathymetry for several traverses across the Lucky Strike segment, to evaluate the distribution of hydrothermal activity. We have identified a new on-axis site with diffuse flow, Ewan, and an active vent structure ∼1.2 km from the axis, Capelinhos. These sites are minor relative to the Main field, and our total heatflux estimate for all active sites (200-1200 MW) is only slightly higher than previously published estimates. We also identify fossil sites W of the main Lucky Strike field. A circular feature ∼200 m in diameter located on the flanks of a rifted off-axis central volcano is likely a large and inactive hydrothermal edifice, named Grunnus. We find no indicator of focused hydrothermal activity elsewhere along the segment, suggesting that the enhanced melt supply and the associated melt lenses, required to form central volcanoes, also sustain hydrothermal circulation to form and maintain large and long-lived hydrothermal fields. Hydrothermal discharge to the seafloor occurs along fault traces, suggesting focusing of hydrothermal circulation in the shallow crust along permeable fault zones.

  18. Idiopathic segmental sclerosis of vertebral bodies

    SciTech Connect

    McCarthy, E.F.; Dorfman, H.D.

    1982-12-01

    Five cases of idiopathic vetebral sclerosis are presented. The features of this condition are segmental vertebral sclerosis of a single lumbar vertebra in a young adult without disc space narrowing or alteration of vertebral contour. The differential diagnosis is discussed. Lumbar vertebra biopsies of three patients showed reactive nonspecific osteosclerosis.

  19. Tongue Motion Averaging from Contour Sequences

    ERIC Educational Resources Information Center

    Li, Min; Kambhamettu, Chandra; Stone, Maureen

    2005-01-01

    In this paper, a method to get the best representation of a speech motion from several repetitions is presented. Each repetition is a representation of the same speech captured at different times by sequence of ultrasound images and is composed of a set of 2D spatio-temporal contours. These 2D contours in different repetitions are time aligned…

  20. Interval and Contour Processing in Autism

    ERIC Educational Resources Information Center

    Heaton, Pamela

    2005-01-01

    High functioning children with autism and age and intelligence matched controls participated in experiments testing perception of pitch intervals and musical contours. The finding from the interval study showed superior detection of pitch direction over small pitch distances in the autism group. On the test of contour discrimination no group…

  1. The evidence behind noninvasive body contouring devices.

    PubMed

    Nassab, Reza

    2015-03-01

    The demand for body contouring is rapidly increasing, and interest in noninvasive approaches has also grown. The author reviewed the evidence base behind the currently available devices and methods for nonsurgical body contouring. There is little high-level evidence in the present literature to support the effectiveness of any of these devices.

  2. Information Along Contours and Object Boundaries

    ERIC Educational Resources Information Center

    Feldman, Jacob; Singh, Manish

    2005-01-01

    F. Attneave (1954) famously suggested that information along visual contours is concentrated in regions of high magnitude of curvature, rather than being distributed uniformly along the contour. Here the authors give a formal derivation of this claim, yielding an exact expression for information, in C. Shannon's (1948) sense, as a function of…

  3. Overlapping cell nuclei segmentation using a spatially adaptive active physical model.

    PubMed

    Plissiti, Marina E; Nikou, Christophoros

    2012-11-01

    A method for the segmentation of overlapping nuclei is presented, which combines local characteristics of the nuclei boundary and a priori knowledge about the expected shape of the nuclei. A deformable model whose behavior is driven by physical principles is trained on images containing a single nuclei, and attributes of the shapes of the nuclei are expressed in terms of modal analysis. Based on the estimated modal distribution and driven by the image characteristics, we develop a framework to detect and describe the unknown nuclei boundaries in images containing two overlapping nuclei. The problem of the estimation of an accurate nucleus boundary in the overlapping areas is successfully addressed with the use of appropriate weight parameters that control the contribution of the image force in the total energy of the deformable model. The proposed method was evaluated using 152 images of conventional Pap smears, each containing two overlapping nuclei. Comparisons with other segmentation methods indicate that our method produces more accurate nuclei boundaries which are closer to the ground truth.

  4. Reconstruction of the activity of point sources for the accurate characterization of nuclear waste drums by segmented gamma scanning.

    PubMed

    Krings, Thomas; Mauerhofer, Eric

    2011-06-01

    This work improves the reliability and accuracy in the reconstruction of the total isotope activity content in heterogeneous nuclear waste drums containing point sources. The method is based on χ(2)-fits of the angular dependent count rate distribution measured during a drum rotation in segmented gamma scanning. A new description of the analytical calculation of the angular count rate distribution is introduced based on a more precise model of the collimated detector. The new description is validated and compared to the old description using MCNP5 simulations of angular dependent count rate distributions of Co-60 and Cs-137 point sources. It is shown that the new model describes the angular dependent count rate distribution significantly more accurate compared to the old model. Hence, the reconstruction of the activity is more accurate and the errors are considerably reduced that lead to more reliable results. Furthermore, the results are compared to the conventional reconstruction method assuming a homogeneous matrix and activity distribution.

  5. Age Differences in Language Segmentation.

    PubMed

    Stine-Morrow, Elizabeth A L; Payne, Brennan R

    2016-01-01

    Reading bears the evolutionary footprint of spoken communication. Prosodic contour in speech helps listeners parse sentences and establish semantic focus. Readers' regulation of input mirrors the segmentation patterns of prosody, such that reading times are longer for words at the ends of syntactic constituents. As reflected in these "micropauses," older readers are often found to segment text into smaller chunks. The mechanisms underlying these micropauses are unclear, with some arguing that they derive from the mental simulation of prosodic contour and others arguing they reflect higher-level language comprehension mechanisms (e.g., conceptual integration, consolidation with existing knowledge, ambiguity resolution) that are common across modality and support the consolidation of the memory representation. The authors review evidence based on reading time and comprehension performance to suggest that (a) age differences in segmentation derive both from age-related declines in working memory, as well as from crystallized ability and knowledge, which have the potential to grow in adulthood, and that (b) shifts in segmentation patterns may be a pathway through which language comprehension is preserved in late life.

  6. Automated compromised right lung segmentation method using a robust atlas-based active volume model with sparse shape composition prior in CT.

    PubMed

    Zhou, Jinghao; Yan, Zhennan; Lasio, Giovanni; Huang, Junzhou; Zhang, Baoshe; Sharma, Navesh; Prado, Karl; D'Souza, Warren

    2015-12-01

    To resolve challenges in image segmentation in oncologic patients with severely compromised lung, we propose an automated right lung segmentation framework that uses a robust, atlas-based active volume model with a sparse shape composition prior. The robust atlas is achieved by combining the atlas with the output of sparse shape composition. Thoracic computed tomography images (n=38) from patients with lung tumors were collected. The right lung in each scan was manually segmented to build a reference training dataset against which the performance of the automated segmentation method was assessed. The quantitative results of this proposed segmentation method with sparse shape composition achieved mean Dice similarity coefficient (DSC) of (0.72, 0.81) with 95% CI, mean accuracy (ACC) of (0.97, 0.98) with 95% CI, and mean relative error (RE) of (0.46, 0.74) with 95% CI. Both qualitative and quantitative comparisons suggest that this proposed method can achieve better segmentation accuracy with less variance than other atlas-based segmentation methods in the compromised lung segmentation.

  7. β-Arrestin-Dependent Dopaminergic Regulation of Calcium Channel Activity in the Axon Initial Segment.

    PubMed

    Yang, Sungchil; Ben-Shalom, Roy; Ahn, Misol; Liptak, Alayna T; van Rijn, Richard M; Whistler, Jennifer L; Bender, Kevin J

    2016-08-01

    G-protein-coupled receptors (GPCRs) initiate a variety of signaling cascades, depending on effector coupling. β-arrestins, which were initially characterized by their ability to "arrest" GPCR signaling by uncoupling receptor and G protein, have recently emerged as important signaling effectors for GPCRs. β-arrestins engage signaling pathways that are distinct from those mediated by G protein. As such, arrestin-dependent signaling can play a unique role in regulating cell function, but whether neuromodulatory GPCRs utilize β-arrestin-dependent signaling to regulate neuronal excitability remains unclear. Here, we find that D3 dopamine receptors (D3R) regulate axon initial segment (AIS) excitability through β-arrestin-dependent signaling, modifying CaV3 voltage dependence to suppress high-frequency action potential generation. This non-canonical D3R signaling thereby gates AIS excitability via pathways distinct from classical GPCR signaling pathways.

  8. Contour and osteotomy of free fibula transplant using a ruler template.

    PubMed

    Kang, Stephen Y; Old, Matthew O; Teknos, Theodoros N

    2016-10-01

    The fibula free tissue transplant has been used in mandibular reconstruction for several decades. Various techniques exist to shape and contour the fibula to restore continuity to the segmental mandible defect. Recently, virtual surgical planning has introduced the ability to use cutting guides to contour and create osteotomies for fibula free tissue reconstruction of the mandible. In this article, we describe a practical and reproducible technique to perform template-based fibula free tissue reconstruction of the mandible without the use of cutting guides. Laryngoscope, 126:2288-2290, 2016.

  9. Evaluation of Automatic Atlas-Based Lymph Node Segmentation for Head-and-Neck Cancer

    SciTech Connect

    Stapleford, Liza J.; Lawson, Joshua D.; Perkins, Charles; Edelman, Scott; Davis, Lawrence

    2010-07-01

    Purpose: To evaluate if automatic atlas-based lymph node segmentation (LNS) improves efficiency and decreases inter-observer variability while maintaining accuracy. Methods and Materials: Five physicians with head-and-neck IMRT experience used computed tomography (CT) data from 5 patients to create bilateral neck clinical target volumes covering specified nodal levels. A second contour set was automatically generated using a commercially available atlas. Physicians modified the automatic contours to make them acceptable for treatment planning. To assess contour variability, the Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm was used to take collections of contours and calculate a probabilistic estimate of the 'true' segmentation. Differences between the manual, automatic, and automatic-modified (AM) contours were analyzed using multiple metrics. Results: Compared with the 'true' segmentation created from manual contours, the automatic contours had a high degree of accuracy, with sensitivity, Dice similarity coefficient, and mean/max surface disagreement values comparable to the average manual contour (86%, 76%, 3.3/17.4 mm automatic vs. 73%, 79%, 2.8/17 mm manual). The AM group was more consistent than the manual group for multiple metrics, most notably reducing the range of contour volume (106-430 mL manual vs. 176-347 mL AM) and percent false positivity (1-37% manual vs. 1-7% AM). Average contouring time savings with the automatic segmentation was 11.5 min per patient, a 35% reduction. Conclusions: Using the STAPLE algorithm to generate 'true' contours from multiple physician contours, we demonstrated that, in comparison with manual segmentation, atlas-based automatic LNS for head-and-neck cancer is accurate, efficient, and reduces interobserver variability.

  10. Automatic morphological characterization of nanobubbles with a novel image segmentation method and its application in the study of nanobubble coalescence.

    PubMed

    Wang, Yuliang; Wang, Huimin; Bi, Shusheng; Guo, Bin

    2015-01-01

    Nanobubbles (NBs) on hydrophobic surfaces in aqueous solvents have shown great potential in numerous applications. In this study, the morphological characterization of NBs in AFM images was carried out with the assistance of a novel image segmentation method. The method combines the classical threshold method and a modified, active contour method to achieve optimized image segmentation. The image segmentation results obtained with the classical threshold method and the proposed, modified method were compared. With the modified method, the diameter, contact angle, and radius of curvature were automatically measured for all NBs in AFM images. The influence of the selection of the threshold value on the segmentation result was discussed. Moreover, the morphological change in the NBs was studied in terms of density, covered area, and volume occurring during coalescence under external disturbance. PMID:25977866

  11. Contour mapping of spectacle lenses.

    PubMed

    Liu, L

    1994-04-01

    The measurement of spectacle lenses by conventional focimeters and automated focimeters assesses only a small region of the lens, and only the power and related data at that point are indicated. In this paper, two methods based on optical Fourier filtering and optical correlation are suggested for contour-mapping the deviations of a spectacle lens over its whole aperture. The fringe pattern appearing on the lens image depicts vividly the characteristics of the tested lens. All the related data are qualitatively seen at a glance and can be calculated from the fringe distribution. Furthermore, the optical processing of the fringes by defocusing is described; thus, the fringes can be continuously changed by shifting the illuminating point source or mask. The shift indicates the spherical power needed to decrease or increase the lens fringes. In addition, a fringe-reading technique is suggested by counting the number of the fringes within a reticle ring. Therefore, the sphere power, cylinder power, cylinder axis, prism power, and prism orientation can be obtained from the reading of the fringes, the shift position, or their combination with a high accuracy. The methods are suitable not only to sphere, spherocylinder, and prism lenses but also to multifocus and progressive power lenses. The suggestion provides a practical way to measure spectacle lenses over the whole aperture. PMID:8047340

  12. Detection and segmentation of cell nuclei in virtual microscopy images: a minimum-model approach.

    PubMed

    Wienert, Stephan; Heim, Daniel; Saeger, Kai; Stenzinger, Albrecht; Beil, Michael; Hufnagl, Peter; Dietel, Manfred; Denkert, Carsten; Klauschen, Frederick

    2012-01-01

    Automated image analysis of cells and tissues has been an active research field in medical informatics for decades but has recently attracted increased attention due to developments in computer and microscopy hardware and the awareness that scientific and diagnostic pathology require novel approaches to perform objective quantitative analyses of cellular and tissue specimens. Model-based approaches use a priori information on cell shape features to obtain the segmentation, which may introduce a bias favouring the detection of cell nuclei only with certain properties. In this study we present a novel contour-based "minimum-model" cell detection and segmentation approach that uses minimal a priori information and detects contours independent of their shape. This approach avoids a segmentation bias with respect to shape features and allows for an accurate segmentation (precision = 0.908; recall = 0.859; validation based on ∼8000 manually-labeled cells) of a broad spectrum of normal and disease-related morphological features without the requirement of prior training.

  13. Tracking fuzzy borders using geodesic curves with application to liver segmentation on planning CT

    SciTech Connect

    Yuan, Yading Chao, Ming; Sheu, Ren-Dih; Rosenzweig, Kenneth; Lo, Yeh-Chi

    2015-07-15

    Purpose: This work aims to develop a robust and efficient method to track the fuzzy borders between liver and the abutted organs where automatic liver segmentation usually suffers, and to investigate its applications in automatic liver segmentation on noncontrast-enhanced planning computed tomography (CT) images. Methods: In order to track the fuzzy liver–chestwall and liver–heart borders where oversegmentation is often found, a starting point and an ending point were first identified on the coronal view images; the fuzzy border was then determined as a geodesic curve constructed by minimizing the gradient-weighted path length between these two points near the fuzzy border. The minimization of path length was numerically solved by fast-marching method. The resultant fuzzy borders were incorporated into the authors’ automatic segmentation scheme, in which the liver was initially estimated by a patient-specific adaptive thresholding and then refined by a geodesic active contour model. By using planning CT images of 15 liver patients treated with stereotactic body radiation therapy, the liver contours extracted by the proposed computerized scheme were compared with those manually delineated by a radiation oncologist. Results: The proposed automatic liver segmentation method yielded an average Dice similarity coefficient of 0.930 ± 0.015, whereas it was 0.912 ± 0.020 if the fuzzy border tracking was not used. The application of fuzzy border tracking was found to significantly improve the segmentation performance. The mean liver volume obtained by the proposed method was 1727 cm{sup 3}, whereas it was 1719 cm{sup 3} for manual-outlined volumes. The computer-generated liver volumes achieved excellent agreement with manual-outlined volumes with correlation coefficient of 0.98. Conclusions: The proposed method was shown to provide accurate segmentation for liver in the planning CT images where contrast agent is not applied. The authors’ results also clearly

  14. Segmentation of humeral head from axial proton density weighted shoulder MR images

    NASA Astrophysics Data System (ADS)

    Sezer, Aysun; Sezer, Hasan Basri; Albayrak, Songul

    2015-01-01

    The purpose of this study is to determine the effectiveness of segmentation of axial MR proton density (PD) images of bony humeral head. PD sequence images which are included in standard shoulder MRI protocol are used instead of T1 MR images. Bony structures were reported to be successfully segmented in the literature from T1 MR images. T1 MR images give more sharp determination of bone and soft tissue border but cannot address the pathological process which takes place in the bone. In the clinical settings PD images of shoulder are used to investigate soft tissue alterations which can cause shoulder instability and are better in demonstrating edema and the pathology but have a higher noise ratio than other modalities. Moreover the alteration of humeral head intensity in patients and soft tissues in contact with the humeral head which have the very similar intensities with bone makes the humeral head segmentation a challenging problem in PD images. However segmentation of the bony humeral head is required initially to facilitate the segmentation of the soft tissues of shoulder. In this study shoulder MRI of 33 randomly selected patients were included. Speckle reducing anisotropic diffusion (SRAD) method was used to decrease noise and then Active Contour Without Edge (ACWE) and Signed Pressure Force (SPF) models were applied on our data set. Success of these methods is determined by comparing our results with manually segmented images by an expert. Applications of these methods on PD images provide highly successful results for segmentation of bony humeral head. This is the first study to determine bone contours in PD images in literature.

  15. Segmentation of thermographic images of hands using a genetic algorithm

    NASA Astrophysics Data System (ADS)

    Ghosh, Payel; Mitchell, Melanie; Gold, Judith

    2010-01-01

    This paper presents a new technique for segmenting thermographic images using a genetic algorithm (GA). The individuals of the GA also known as chromosomes consist of a sequence of parameters of a level set function. Each chromosome represents a unique segmenting contour. An initial population of segmenting contours is generated based on the learned variation of the level set parameters from training images. Each segmenting contour (an individual) is evaluated for its fitness based on the texture of the region it encloses. The fittest individuals are allowed to propagate to future generations of the GA run using selection, crossover and mutation. The dataset consists of thermographic images of hands of patients suffering from upper extremity musculo-skeletal disorders (UEMSD). Thermographic images are acquired to study the skin temperature as a surrogate for the amount of blood flow in the hands of these patients. Since entire hands are not visible on these images, segmentation of the outline of the hands on these images is typically performed by a human. In this paper several different methods have been tried for segmenting thermographic images: Gabor-wavelet-based texture segmentation method, the level set method of segmentation and our GA which we termed LSGA because it combines level sets with genetic algorithms. The results show a comparative evaluation of the segmentation performed by all the methods. We conclude that LSGA successfully segments entire hands on images in which hands are only partially visible.

  16. Bright-field cell image segmentation by principal component pursuit with an Ncut penalization

    NASA Astrophysics Data System (ADS)

    Chen, Yuehuan; Wan, Justin W. L.

    2015-03-01

    Segmentation of cells in time-lapse bright-field microscopic images is crucial in understanding cell behaviours for oncological research. However, the complex nature of the cells makes it difficult to segment cells accurately. Furthermore, poor contrast, broken cell boundaries and the halo artifact pose additional challenges to this problem. Standard segmentation techniques such as edged-based methods, watershed, or active contours result in poor segmentation. Other existing methods for bright-field images cannot provide good results without localized segmentation steps. In this paper, we present two robust mathematical models to segment bright-field cells automatically for the entire image. These models treat cell image segmentation as a background subtraction problem, which can be formulated as a Principal Component Pursuit (PCP) problem. Our first segmentation model is formulated as a PCP with nonnegative constraints. We exploit the sparse component of the PCP solution for identifying the cell pixels. However, there is no control on the quality of the sparse component and the nonzero entries can scatter all over the image, resulting in a noisy segmentation. The second model is an improvement of the first model by combining PCP with spectral clustering. Seemingly unrelated approaches, we combine the two techniques by incorporating normalized-cut in the PCP as a measure for the quality of the segmentation. These two models have been applied to a set of C2C12 cells obtained from bright-field microscopy. Experimental results demonstrate that the proposed models are effective in segmenting cells from bright-field images.

  17. Segmentation propagation for the automated quantification of ventricle volume from serial MRI

    NASA Astrophysics Data System (ADS)

    Linguraru, Marius George; Butman, John A.

    2009-02-01

    Accurate ventricle volume estimates could potentially improve the understanding and diagnosis of communicating hydrocephalus. Postoperative communicating hydrocephalus has been recognized in patients with brain tumors where the changes in ventricle volume can be difficult to identify, particularly over short time intervals. Because of the complex alterations of brain morphology in these patients, the segmentation of brain ventricles is challenging. Our method evaluates ventricle size from serial brain MRI examinations; we (i) combined serial images to increase SNR, (ii) automatically segmented this image to generate a ventricle template using fast marching methods and geodesic active contours, and (iii) propagated the segmentation using deformable registration of the original MRI datasets. By applying this deformation to the ventricle template, serial volume estimates were obtained in a robust manner from routine clinical images (0.93 overlap) and their variation analyzed.

  18. Tracking moving targets in complex environments by fusing active and passive sensors

    NASA Astrophysics Data System (ADS)

    Fitzpatrick, Ben G.; Liu, Li; Wang, Yun; Cheng, Zhanqi

    2007-04-01

    We present a novel algorithm for tracking with ladar sensors to aid in navigation, guidance and control systems, suitable for applications to unmanned air vehicles. The methods we employ are based on Bayesian segmentation, optical flow, active contour and Bayesian particle tracking. The algorithm herein holds several significant advantages over traditional tracking methods. The first step in the process is the optimal segmentation of images to enhance the targets and extract them from background clutter and noise. The Bayesian approach to segmentation allows the use of intensity (passive) and range (active) imagery to find targets. Optical flow generalizes and improves correlation techniques for locating objects within a frame, allowing for aspect angle and range changes. With optical flow, we may infer relative velocities on a pixel-by-pixel basis. Active contours are ideally suited to both target-sparse and target-rich environments. The energy approach to determining contours allows the merging and separating of potential targets in an automatic manner. Bayesian particle tracking techniques are used to track the contours over time. The algorithm is tested successfully on experimental and simulated ladar data (using both intensity and range data) as well as sequences of video imageries. The streamlined processing, from obtaining the image data (of size 805x148 pixels) to detecting the moving target to wrapping an active contour on the target, takes less than one second of clock time and provides very accurate predictions of the target location in future frames.

  19. Genome segment 6 of Antheraea mylitta cypovirus encodes a structural protein with ATPase activity

    SciTech Connect

    Chavali, Venkata R.M.; Madhurantakam, Chaithanya; Ghorai, Suvankar; Roy, Sobhan; Das, Amit K.; Ghosh, Ananta K.

    2008-07-20

    The genome segment 6 (S6) of the 11 double stranded RNA genomes from Antheraea mylitta cypovirus was converted into cDNA, cloned and sequenced. S6 consisted of 1944 nucleotides with an ORF of 607 amino acids and could encode a protein of 68 kDa, termed P68. Motif scan and molecular docking analysis of P68 showed the presence of two cystathionine beta synthase (CBS) domains and ATP binding sites. The ORF of AmCPV S6 was expressed in E. coli as His-tag fusion protein and polyclonal antibody was raised. Immunoblot analysis of virus infected gut cells and purified polyhedra using raised anti-p68 polyclonal antibody showed that S6 encodes a viral structural protein. Fluorescence and ATPase assay of soluble P68 produced in Sf-9 cells via baculovirus expression system showed its ability to bind and cleave ATP. These results suggest that P68 may bind viral RNA through CBS domains and help in replication and transcription through ATP binding and hydrolysis.

  20. Multi-segmented piezoelectric mirrors as active/adaptive optics components.

    PubMed

    Signorato, R; Hignette, O; Goulon, J

    1998-05-01

    The angular acceptance of piezoelectric (Pzt) bimorph mirrors is limited by the maximum length of commercially available Pzt ceramic plates. To overcome this limit and manufacture longer devices, several (2n + 1) 150 mm-long bimorph Pzt stacks were assembled side-to-side. Two prototype mirrors, 450 (n = 1) and 750 (n = 2) mm long, were designed, assembled, polished and optically characterized. They are fully UHV compatible and are now installed in the monochromatic section of the ESRF beamlines ID26 and ID32. Both mirrors cover the full range of required bending radii (1 km concave-3.5 km convex). Junctions between segments do not spoil the optical surface quality. The surface slope error r.m.s. can be kept well below 1 arcsec over the full bending range. Adaptive compensation for low-frequency figure errors was shown to be easy and reliable. After compensation, residual shape errors are of the order of 40 nm r.m.s. over 700 mm. PMID:15263657

  1. Active control of adaptive optics system in a large segmented mirror telescope

    NASA Astrophysics Data System (ADS)

    Nagashima, M.; Agrawal, B. N.

    2014-02-01

    For a large adaptive optics system such as a large segmented mirror telescope (SMT), it is often difficult, although not impossible, to directly apply common multi-input multi-output (MIMO) controller design methods due to the computational burden imposed by the large dimension of the system model. In this article, a practical controller design method is proposed which significantly reduces the system dimension for a system where the dimension required to represent the dynamics of the plant is much smaller than the dimension of the full plant model. The proposed method decouples the dynamic and static parts of the plant model by a modal decomposition technique to separately design a controller for each part. Two controllers are then combined using the so-called sensitivity decoupling method so that the resulting feedback loop becomes the superposition of the two individual feedback loops of the dynamic and static parts. A MIMO controller was designed by the proposed method using the H ∞ loop-shaping technique for an SMT model to be compared with other controllers proposed in the literature. Frequency-domain analysis and time-domain simulation results show the superior performance of the proposed controller.

  2. An Efficient Correction Algorithm for Eliminating Image Misalignment Effects on Co-Phasing Measurement Accuracy for Segmented Active Optics Systems.

    PubMed

    Yue, Dan; Xu, Shuyan; Nie, Haitao; Wang, Zongyang

    2016-01-01

    The misalignment between recorded in-focus and out-of-focus images using the Phase Diversity (PD) algorithm leads to a dramatic decline in wavefront detection accuracy and image recovery quality for segmented active optics systems. This paper demonstrates the theoretical relationship between the image misalignment and tip-tilt terms in Zernike polynomials of the wavefront phase for the first time, and an efficient two-step alignment correction algorithm is proposed to eliminate these misalignment effects. This algorithm processes a spatial 2-D cross-correlation of the misaligned images, revising the offset to 1 or 2 pixels and narrowing the search range for alignment. Then, it eliminates the need for subpixel fine alignment to achieve adaptive correction by adding additional tip-tilt terms to the Optical Transfer Function (OTF) of the out-of-focus channel. The experimental results demonstrate the feasibility and validity of the proposed correction algorithm to improve the measurement accuracy during the co-phasing of segmented mirrors. With this alignment correction, the reconstructed wavefront is more accurate, and the recovered image is of higher quality.

  3. An Efficient Correction Algorithm for Eliminating Image Misalignment Effects on Co-Phasing Measurement Accuracy for Segmented Active Optics Systems

    PubMed Central

    Yue, Dan; Xu, Shuyan; Nie, Haitao; Wang, Zongyang

    2016-01-01

    The misalignment between recorded in-focus and out-of-focus images using the Phase Diversity (PD) algorithm leads to a dramatic decline in wavefront detection accuracy and image recovery quality for segmented active optics systems. This paper demonstrates the theoretical relationship between the image misalignment and tip-tilt terms in Zernike polynomials of the wavefront phase for the first time, and an efficient two-step alignment correction algorithm is proposed to eliminate these misalignment effects. This algorithm processes a spatial 2-D cross-correlation of the misaligned images, revising the offset to 1 or 2 pixels and narrowing the search range for alignment. Then, it eliminates the need for subpixel fine alignment to achieve adaptive correction by adding additional tip-tilt terms to the Optical Transfer Function (OTF) of the out-of-focus channel. The experimental results demonstrate the feasibility and validity of the proposed correction algorithm to improve the measurement accuracy during the co-phasing of segmented mirrors. With this alignment correction, the reconstructed wavefront is more accurate, and the recovered image is of higher quality. PMID:26934045

  4. Extreme_SeaState_Contour_v1

    2015-10-19

    This software generates environmental contours of extreme sea states using buoy observations of significant wave height and energy period or peak period. The code transforms these observations using principal component analysis (PCA) to create an uncorrelated representation of the data. The subsequent components are modeled using probability distributions and parameter fitting functions. The inverse first-order reliability method (I-FORM) is then applied to these models in order to generate an extreme event contour based on amore » given return period (i.e., 100 years).The subsequent contour is then transformed back into the original input space defined by the variables of interest in order to create an environmental contour of extreme sea states.« less

  5. Extreme_SeaState_Contour_v1

    SciTech Connect

    2015-10-19

    This software generates environmental contours of extreme sea states using buoy observations of significant wave height and energy period or peak period. The code transforms these observations using principal component analysis (PCA) to create an uncorrelated representation of the data. The subsequent components are modeled using probability distributions and parameter fitting functions. The inverse first-order reliability method (I-FORM) is then applied to these models in order to generate an extreme event contour based on a given return period (i.e., 100 years).The subsequent contour is then transformed back into the original input space defined by the variables of interest in order to create an environmental contour of extreme sea states.

  6. Automatic segmentation of equine larynx for diagnosis of laryngeal hemiplegia

    NASA Astrophysics Data System (ADS)

    Salehin, Md. Musfequs; Zheng, Lihong; Gao, Junbin

    2013-10-01

    This paper presents an automatic segmentation method for delineation of the clinically significant contours of the equine larynx from an endoscopic image. These contours are used to diagnose the most common disease of horse larynx laryngeal hemiplegia. In this study, hierarchal structured contour map is obtained by the state-of-the-art segmentation algorithm, gPb-OWT-UCM. The conic-shaped outer boundary of equine larynx is extracted based on Pascal's theorem. Lastly, Hough Transformation method is applied to detect lines related to the edges of vocal folds. The experimental results show that the proposed approach has better performance in extracting the targeted contours of equine larynx than the results of using only the gPb-OWT-UCM method.

  7. Geomorphic signatures of active tectonics in the Trans-Yamuna segment of the western Doon valley, northwest Himalaya, India

    NASA Astrophysics Data System (ADS)

    Philip, George; Sah, Madho P.

    Being involved in the late orogenic movements of the sub-Himalaya, the Doon valley and its Quaternary formations have received considerable attention from Earth scientists in the study of active tectonics and paleoseismic events. Study of aerial photographs and satellite data, and selected field checks not only confirmed neotectonic features already reported by various authors but also revealed the presence of more such features. In response to active tectonics, these features have affected very young terraces and Quaternary sediments in the Trans-Yamuna segment of the Doon valley in the western sub-Himalaya. In the present study, an attempt has been made to understand the neotectonic implications of these movements on landforms in and around Sataun-Sirmuri Tal. Ground evidence indicates that the area has experienced at least three major tectonic impulses since the generation of the Main Boundary Thrust. The major tectonic disturbances are most likely due to co-seismic activity along the ongoing Himalayan tectonic processes. In this paper, we discuss some of the strong geomorphic signatures, such as lineament and active fault traces, pressure ridges, sag ponds, alluvial fans, river terraces and finally landslides, which are indicative of active tectonics in this area. On the basis of the present-day geomorphic configuration of this sub-Himalayan basin, a possible evolutionary history is also presented.

  8. Right-hemisphere specialization for contour grouping.

    PubMed

    Volberg, Gregor

    2014-01-01

    Previous studies often revealed a right-hemisphere specialization for processing the global level of compound visual stimuli. Here we explore whether a similar specialization exists for the detection of intersected contours defined by a chain of local elements. Subjects were presented with arrays of randomly oriented Gabor patches that could contain a global path of collinearly arranged elements in the left or in the right visual hemifield. As expected, the detection accuracy was higher for contours presented to the left visual field/right hemisphere. This difference was absent in two control conditions where the smoothness of the contour was decreased. The results demonstrate that the contour detection, often considered to be driven by lateral coactivation in primary visual cortex, relies on higher-level visual representations that differ between the hemispheres. Furthermore, because contour and non-contour stimuli had the same spatial frequency spectra, the results challenge the view that the right-hemisphere advantage in global processing depends on a specialization for processing low spatial frequencies.

  9. Isolating contour information from arbitrary images

    NASA Astrophysics Data System (ADS)

    Jobson, Daniel J.

    1989-11-01

    Aspects of natural vision (physiological and perceptual) serve as a basis for attempting the development of a general processing scheme for contour extraction. Contour information is assumed to be central to visual recognition skills. While the scheme must be regarded as highly preliminary, initial results do compare favorably with the visual perception of structure. The scheme pays special attention to the construction of a smallest scale circular difference-of-Gaussian (DOG) convolution, calibration of multiscale edge detection thresholds with the visual perception of grayscale boundaries, and contour/texture discrimination methods derived from fundamental assumptions of connectivity and the characteristics of printed text. Contour information is required to fall between a minimum connectivity limit and maximum regional spatial density limit at each scale. Results support the idea that contour information, in images possessing good image quality, is (centered at about 10 cyc/deg and 30 cyc/deg). Further, lower spatial frequency channels appear to play a major role only in contour extraction from images with serious global image defects.

  10. Isolating contour information from arbitrary images

    NASA Technical Reports Server (NTRS)

    Jobson, Daniel J.

    1989-01-01

    Aspects of natural vision (physiological and perceptual) serve as a basis for attempting the development of a general processing scheme for contour extraction. Contour information is assumed to be central to visual recognition skills. While the scheme must be regarded as highly preliminary, initial results do compare favorably with the visual perception of structure. The scheme pays special attention to the construction of a smallest scale circular difference-of-Gaussian (DOG) convolution, calibration of multiscale edge detection thresholds with the visual perception of grayscale boundaries, and contour/texture discrimination methods derived from fundamental assumptions of connectivity and the characteristics of printed text. Contour information is required to fall between a minimum connectivity limit and maximum regional spatial density limit at each scale. Results support the idea that contour information, in images possessing good image quality, is (centered at about 10 cyc/deg and 30 cyc/deg). Further, lower spatial frequency channels appear to play a major role only in contour extraction from images with serious global image defects.

  11. Group II-activated lumbosacral interneurones with an ascending projection to midlumbar segments of the cat spinal cord.

    PubMed Central

    Harrison, P J; Riddell, J S

    1989-01-01

    1. In anaesthetized cats, single-unit microelectrode recordings were made in the lateral funiculus at L6, from the axons of lumbosacral interneurones discharged by hindlimb group II muscle afferents. 2. The level of the ascending projection of these interneurones was investigated by antidromic activation of their axons in the lateral funiculus from different spinal levels. The majority of units encountered were found to have an ascending projection to at least the L4 level and, of these, most (85%) did not project beyond the L4 or L3 segments of the cord. 3. The axons studied were discharged by group II afferents primarily from knee extensor muscles. Some units were discharged in addition by cutaneous and/or joint afferents. 4. The implications of this ascending projection are discussed. PMID:2778739

  12. A segment of gamma ENaC mediates elastase activation of Na+ transport.

    PubMed

    Adebamiro, Adedotun; Cheng, Yi; Rao, U Subrahmanyeswara; Danahay, Henry; Bridges, Robert J

    2007-12-01

    The epithelial Na(+) channel (ENaC) that mediates regulated Na(+) reabsorption by epithelial cells in the kidney and lungs can be activated by endogenous proteases such as channel activating protease 1 and exogenous proteases such as trypsin and neutrophil elastase (NE). The mechanism by which exogenous proteases activate the channel is unknown. To test the hypothesis that residues on ENaC mediate protease-dependent channel activation wild-type and mutant ENaC were stably expressed in the FRT epithelial cell line using a tripromoter human ENaC construct, and protease-induced short-circuit current activation was measured in aprotinin-treated cells. The amiloride-sensitive short circuit current (I(Na)) was stimulated by aldosterone (1.5-fold) and dexamethasone (8-fold). Dexamethasone-treated cells were used for all subsequent studies. The serum protease inhibitor aprotinin decreased baseline I(Na) by approximately 50% and I(Na) could be restored to baseline control values by the exogenous addition of trypsin, NE, and porcine pancreatic elastase (PE) but not by thrombin. All protease experiments were thus performed after exposure to aprotinin. Because NE recognition of substrates occurs with a preference for binding valines at the active site, several valines in the extracellular loops of alpha and gamma ENaC were sequentially substituted with glycines. This scan yielded two valine residues in gamma ENaC at positions 182 and 193 that resulted in inhibited responses to NE when simultaneously changed to other amino acids. The mutations resulted in decreased rates of activation and decreased activated steady-state current levels. There was an approximately 20-fold difference in activation efficiency of NE against wild-type ENaC compared to a mutant with glycine substitutions at positions 182 and 193. However, the mutants remain susceptible to activation by trypsin and the related elastase, PE. Alanine is the preferred P(1) position residue for PE and substitution of

  13. A Multiphase Validation of Atlas-Based Automatic and Semiautomatic Segmentation Strategies for Prostate MRI

    SciTech Connect

    Martin, Spencer; Rodrigues, George; Bauman, Glenn; D'Souza, David; Sexton, Tracy; Palma, David; Louie, Alexander V.; Khalvati, Farzad; Tizhoosh, Hamid R.; Gaede, Stewart

    2013-01-01

    Purpose: To perform a rigorous technological assessment and statistical validation of a software technology for anatomic delineations of the prostate on MRI datasets. Methods and Materials: A 3-phase validation strategy was used. Phase I consisted of anatomic atlas building using 100 prostate cancer MRI data sets to provide training data sets for the segmentation algorithms. In phase II, 2 experts contoured 15 new MRI prostate cancer cases using 3 approaches (manual, N points, and region of interest). In phase III, 5 new physicians with variable MRI prostate contouring experience segmented the same 15 phase II datasets using 3 approaches: manual, N points with no editing, and full autosegmentation with user editing allowed. Statistical analyses for time and accuracy (using Dice similarity coefficient) endpoints used traditional descriptive statistics, analysis of variance, analysis of covariance, and pooled Student t test. Results: In phase I, average (SD) total and per slice contouring time for the 2 physicians was 228 (75), 17 (3.5), 209 (65), and 15 seconds (3.9), respectively. In phase II, statistically significant differences in physician contouring time were observed based on physician, type of contouring, and case sequence. The N points strategy resulted in superior segmentation accuracy when initial autosegmented contours were compared with final contours. In phase III, statistically significant differences in contouring time were observed based on physician, type of contouring, and case sequence again. The average relative timesaving for N points and autosegmentation were 49% and 27%, respectively, compared with manual contouring. The N points and autosegmentation strategies resulted in average Dice values of 0.89 and 0.88, respectively. Pre- and postedited autosegmented contours demonstrated a higher average Dice similarity coefficient of 0.94. Conclusion: The software provided robust contours with minimal editing required. Observed time savings were seen

  14. Objectively measured physical activity in four-year-old British children: a cross-sectional analysis of activity patterns segmented across the day

    PubMed Central

    2014-01-01

    Background Little is known about preschool-aged children’s levels of physical activity (PA) over the course of the day. Using time-stamped data, we describe the levels and patterns of PA in a population-based sample of four-year-old British children. Methods Within the Southampton Women’s Survey the PA levels of 593 4-year-old children (51% female) were measured using (Actiheart) accelerometry for up to 7 days. Three outcome measures: minutes spent sedentary (<20 cpm); in light (LPA: ≥20 – 399 cpm) and in moderate-to-vigorous activity (MVPA: ≥400 cpm) were derived. Average daily activity levels were calculated and then segmented across the day (morning, afternoon and evening). MVPA was log-transformed. Two-level random intercept models were used to analyse associations between activity level and temporal and demographic factors. Results Children were active for 67% (mean 568.5 SD 79.5 minutes) of their daily registered time on average, with 88% of active time spent in LPA. All children met current UK guidelines of 180 minutes of daily activity. There were no differences in children’s average daily levels of sedentary activity and LPA by temporal and demographic factors: differences did emerge when activity was segmented across the day. Sex differences were largest in the morning, with girls being more sedentary, spending fewer minutes in LPA and 18% less time in MVPA than boys. Children were more sedentary and less active (LPA and MVPA) in the morning if they attended childcare full-time compared to part-time, and on weekend mornings compared to weekdays. The reverse was true for weekend afternoons and evenings. Children with more educated mothers were less active in the evenings. Children were less sedentary and did more MVPA on summer evenings compared to winter evenings. Conclusions Preschool-aged children meet current physical activity guidelines, but with the majority of their active time spent in LPA, investigation of the importance of activity

  15. Segmentation of brain tumors in MRI images using multi-scale gradient vector flow.

    PubMed

    Kazerooni, Anahita Fathi; Ahmadian, Alireza; Serej, Nassim Dadashi; Rad, Hamidreza Saligheh; Saberi, Hooshang; Yousefi, Hossein; Farnia, Parastoo

    2011-01-01

    The gradient vector flow (GVF) algorithm has been used extensively as an efficient method for medical image segmentation. This algorithm suffers from poor robustness against noise as well as lack of convergence in small scale details and concavities. As a cure to this problem, in this paper the idea of multi scale is applied to the traditional GVF algorithm for segmentation of brain tumors in MRI images. Using this idea, the active contour is evolved with respect to scaled edge maps in a multi scale manner. The edge detection performance of the modified GVF algorithm is further enhanced by applying a threshold-based edge detector to improve the edge map. The Bspline snake is selected for representation of the active contour, due to its ability to capture corners and its local control. The results showed an improvement of 30% in the accuracy of tumor segmentation against traditional GVF and 10 % as compared to Bspline GVF in the presence of noise, besides the repeatability of the algorithm in contrast to traditional GVF. The clinical evaluation also proved the accuracy and sensitivity of the proposed method as 92.8% and 95.4%, respectively. PMID:22256190

  16. Can acute low back pain result from segmental spinal buckling during sub-maximal activities? A review of the current literature.

    PubMed

    Preuss, Richard; Fung, Joyce

    2005-02-01

    This paper provides a review of the current literature supporting the hypothesis that segmental spine buckling resulting in tissue damage may be a primary cause of sudden onset low back pain, even during activities that are sub-maximal with respect to loading and muscle activation. While a temporal link exists, it is supported primarily by anecdotal and clinical reports. More pertinent to this review is the biological plausibility of segmental spine buckling as a mechanism of acute injury, supported by modelling studies as well as current knowledge of tissue mechanics and neurophysiology. One antithesis, however, is the low incidence of low back injuries reported during sub-maximal tasks. In order to account for this discrepancy, several predisposing factors are addressed, both constant and situation-dependent, which may contribute to the occurrence of segmental spinal buckling during sub-maximal activities. PMID:15681264

  17. [The motor activity study segment as pilot study of The Child and Adolescent Health Survey].

    PubMed

    Kahl, H; Emmel, J

    2002-12-01

    In the Health Survey for Children and Adolescents the examination of motor activity is one aspect of physical health covered by the study. This underlines the importance of physical activity for physical development in early years. This first representative child and adolescent study for Germany intends to obtain data on motor activity and to allow for the implementation of specific intervention programmes encouraging physical activity. The specific general conditions under which the survey is conducted restrict the selection and scope of possible instruments to a minimal programme, including fitness tests, strength in combination with endurance and coordinative skills as well as flexibility. In a pilot study the suitability, feasibility and the obtained evidence of selected single motor tests were tested. This article explains the choice of instruments and methods used in the examination of physical fitness. It also discusses methodological difficulties which affect the standardisation of tests and the requirements regarding personnel. A major concern of the pilot study was the evaluation of tested instruments with regard to gender and age differences. For the main survey the following tests are recommended: coordination (balancing backwards, one-leg-footing, sideway jumping), perseverance (sit-ups, push-ups), and flexibility (trunk bending).

  18. DNA interaction, antitumor and antimicrobial activities of three-dimensional chitosan ring produced from the body segments of a diplopod.

    PubMed

    Kaya, Murat; Akyuz, Bahar; Bulut, Esra; Sargin, Idris; Tan, Gamze; Erdonmez, Demet; Maheta, Mansi; Satkauskas, Saulius; Mickevičius, Saulius

    2016-08-01

    Commercially available chitins and the chitin isolated from mushrooms, insect cuticles, shells of shrimp, crab and crayfish reported in the literature are in forms of powder, flake or granule. Three-dimensional chitins have been only known from the sponges but still three-dimensional chitosan has not been reported yet. In this study, we produced three-dimensional chitin and chitosan rings from the body segments of a diplopod species (Julus terrestris). Obtained chitin and chitosan rings were characterized (by FT-IR, SEM, TGA, XRD, dilute solution viscometry and EA) and compared with commercial chitin and chitosan. The interactions with plasmid DNA was studied at varying concentrations of chitosan (0.04, 0.4 and 4mg/mL). Antitumor activity tests were conducted (L929 and HeLa), low cytotoxicity and high antiproliferative activity was observed. Antimicrobial activities of J. terrestris chitosan were investigated on twelve microorganisms and maximum inhibition (15.6±1.154mm) was recorded for common human pathogen Staphylococcus aureus. PMID:27112853

  19. DNA interaction, antitumor and antimicrobial activities of three-dimensional chitosan ring produced from the body segments of a diplopod.

    PubMed

    Kaya, Murat; Akyuz, Bahar; Bulut, Esra; Sargin, Idris; Tan, Gamze; Erdonmez, Demet; Maheta, Mansi; Satkauskas, Saulius; Mickevičius, Saulius

    2016-08-01

    Commercially available chitins and the chitin isolated from mushrooms, insect cuticles, shells of shrimp, crab and crayfish reported in the literature are in forms of powder, flake or granule. Three-dimensional chitins have been only known from the sponges but still three-dimensional chitosan has not been reported yet. In this study, we produced three-dimensional chitin and chitosan rings from the body segments of a diplopod species (Julus terrestris). Obtained chitin and chitosan rings were characterized (by FT-IR, SEM, TGA, XRD, dilute solution viscometry and EA) and compared with commercial chitin and chitosan. The interactions with plasmid DNA was studied at varying concentrations of chitosan (0.04, 0.4 and 4mg/mL). Antitumor activity tests were conducted (L929 and HeLa), low cytotoxicity and high antiproliferative activity was observed. Antimicrobial activities of J. terrestris chitosan were investigated on twelve microorganisms and maximum inhibition (15.6±1.154mm) was recorded for common human pathogen Staphylococcus aureus.

  20. Continuity, segmentation and faulting type of active fault zones of the 2016 Kumamoto earthquake inferred from analyses of a gravity gradient tensor

    NASA Astrophysics Data System (ADS)

    Matsumoto, Nayuta; Yoshihiro, Hiramatsu; Sawada, Akihiro

    2016-10-01

    We analyze Bouguer anomalies in/around the focal region of the 2016 Kumamoto earthquake to examine features, such as continuity, segmentation and faulting type, of the active fault zones related to the earthquake. Several derivatives and structural parameters calculated from a gravity gradient tensor are applied to highlight the features. First horizontal and vertical derivatives, as well as a normalized total horizontal derivative, characterize well the continuous subsurface fault structure along the Futagawa fault zone. On the other hand, the Hinagu fault zone is not clearly detected by these derivatives, especially in the case of the Takano-Shirahata segment, suggesting a difference of cumulative vertical displacement between the two fault zones. The normalized total horizontal derivative and the dimensionality index indicate a discontinuity of the subsurface structure of the Hinagu fault zone, that is, a segment boundary between the Takano-Shirahata and the Hinagu segments. The aftershock distribution does not extend beyond this segment boundary. In other words, this segment boundary controls the southern end of the rupture area of the foreshock. We also recognize normal fault structures dipping to the northwest in some areas of the fault zones from estimations of dip angles.[Figure not available: see fulltext.

  1. Communicative functions integrate segments in prosodies and prosodies in segments.

    PubMed

    Kohler, Klaus J

    2011-01-01

    This paper takes a new look at the traditionally established divide between sounds and prosodies, viewing it as a useful heuristics in language descriptions that focus on the segmental make- up of words. It pleads for a new approach that bridges this reified compartmentalization of speech in a more global communicative perspective. Data are presented from a German perception experiment in the framework of the Semantic Differential that shows interdependence of f0 contours and the spectral characteristics of a following fricative segment, for the expression of semantic functions along the scales questioning - asserting, excited - calm, forceful - not forceful, contrary - agreeable. The results lead to the conclusion that segments shape prosodies and are shaped by them in varying ways in the coding of semantic functions. This implies that the analysis of sentence prosodies needs to integrate the manifestation of segments, just as the analysis of segments needs to consider their prosodic embedding. In communicative interaction, speakers set broad prosodic time windows of varying sizes, and listeners respond to them. So, future phonetic research needs to concentrate on speech analysis in such windows.

  2. Fluid Chemistry and Dissolved Gasses on the Endeavour Segment from 1991 to 2005: Lasting Effects of Volcanic Activity on Field and Segment Scales

    NASA Astrophysics Data System (ADS)

    Love, B. A.; Lilley, M. D.

    2006-12-01

    A time series analysis of dissolved gas data including over 350 samples from the Endeavour Segment of the Juan de Fuca Ridge reveals several interesting patterns. At the main field most species are quite stable between 1991-1998 and the perturbations in fluid chemistry that accompanied the magmatic event in 1999 are well documented. (Lilley et al., 2003; Seyfried et al., 2004) However after the event, some areas, especially the southern portion of the main field, seem to have returned not to their pre-event concentrations but settled to new levels for some species. These changes may indicate a shift in subsurface fluid flow or phase separation which can be more easily interpreted as part of this long time series data set. When the data are examined on the regional scale, methane concentrations in particular point to a difference in fluid chemistry between the southern fields (Mothra and Main) and northern fields (High Rise, Salty Dawg, and Sasquatch). This difference has become more marked after 1999 and may point to a change in fluid interaction with a proposed subsurface sedimentary source.

  3. Segmentation of uterine fibroid ultrasound images using a dynamic statistical shape model in HIFU therapy.

    PubMed

    Ni, Bo; He, Fazhi; Yuan, ZhiYong

    2015-12-01

    Segmenting the lesion areas from ultrasound (US) images is an important step in the intra-operative planning of high-intensity focused ultrasound (HIFU). However, accurate segmentation remains a challenge due to intensity inhomogeneity, blurry boundaries in HIFU US images and the deformation of uterine fibroids caused by patient's breathing or external force. This paper presents a novel dynamic statistical shape model (SSM)-based segmentation method to accurately and efficiently segment the target region in HIFU US images of uterine fibroids. For accurately learning the prior shape information of lesion boundary fluctuations in the training set, the dynamic properties of stochastic differential equation and Fokker-Planck equation are incorporated into SSM (referred to as SF-SSM). Then, a new observation model of lesion areas (named to RPFM) in HIFU US images is developed to describe the features of the lesion areas and provide a likelihood probability to the prior shape given by SF-SSM. SF-SSM and RPFM are integrated into active contour model to improve the accuracy and robustness of segmentation in HIFU US images. We compare the proposed method with four well-known US segmentation methods to demonstrate its superiority. The experimental results in clinical HIFU US images validate the high accuracy and robustness of our approach, even when the quality of the images is unsatisfactory, indicating its potential for practical application in HIFU therapy.

  4. Portable FORTRAN contour-plotting subprogram

    SciTech Connect

    Haskell, K.H.

    1983-07-01

    In this report we discuss a contour plotting Fortran subprogram. While contour plotting subroutines are available in many commercial plotting packages, this routine has the following advantages: (1) since it uses the Weasel and VDI plot routines developed at Sandia, it occupies little storage and can be used on most of the Sandia time-sharing systems as part of a larger program. In the past, the size of plotting packages often forced a user to perform plotting operations in a completely separate program; (2) the contour computation algorithm is efficient and robust, and computes accurate contours for sets of data with low resolution; and (3) the subprogram is easy to use. A simple contour plot can be produced with a minimum of information provided by a user in one Fortran subroutine call. Through the use of a wide variety of subroutine options, many additional features can be used. These include such items as plot titles, grid lines, placement of text on the page, etc. The subroutine is written in portable Fortran 77, and is designed to run on any system which supports the Weasel and VDI plot packages. It also uses routines from the SLATEC mathematical subroutine library.

  5. Microearthquake activity, lithospheric structure, and deformation modes at an amagmatic ultraslow spreading Southwest Indian Ridge segment

    NASA Astrophysics Data System (ADS)

    Schmid, Florian; Schlindwein, Vera

    2016-07-01

    While nascent oceanic lithosphere at slow to fast spreading mid-ocean ridges (MOR) is relatively well studied, much less is known about the lithospheric structure and properties at ultraslow MORs. Here we present microearthquake data from a 1 year ocean bottom seismometer deployment at the amagmatic, oblique supersegment of the ultraslow spreading Southwest Indian Ridge. A refraction seismic experiment was performed to constrain upper lithosphere P-velocities and results were used to construct a 1D velocity model for earthquake location. Earthquake foci were located individually and subsequently relocated relative to each other to sharpen the image of seismically active structures. Frequent earthquake activity extends to 31 km beneath the seafloor, indicating an exceptionally thick brittle lithosphere and an undulating brittle-ductile transition that implies significant variations in the along-axis thermal structure of the lithosphere. We observe a strong relation between petrology, microseismicity distribution, and topography along the ridge axis: Peridotite-dominated areas associate with deepest hypocenters, vast volumes of lithosphere that deforms aseismically as a consequence of alteration, and the deepest axial rift valley. Areas of basalt exposure correspond to shallower hypocenters, shallower and more rugged axial seafloor. Focal mechanisms deviate from pure extension and are spatially variable. Earthquakes form an undulating band of background seismicity and do not delineate discrete detachment faults as common on slow spreading ridges. Instead, the seismicity band sharply terminates to the south, immediately beneath the rift boundary. Considering the deep alteration, large steep boundary faults might be present but are entirely aseismic.

  6. Generic method for automatic bladder segmentation on cone beam CT using a patient-specific bladder shape model

    SciTech Connect

    Schoot, A. J. A. J. van de Schooneveldt, G.; Wognum, S.; Stalpers, L. J. A.; Rasch, C. R. N.; Bel, A.; Hoogeman, M. S.; Chai, X.

    2014-03-15

    Purpose: The aim of this study is to develop and validate a generic method for automatic bladder segmentation on cone beam computed tomography (CBCT), independent of gender and treatment position (prone or supine), using only pretreatment imaging data. Methods: Data of 20 patients, treated for tumors in the pelvic region with the entire bladder visible on CT and CBCT, were divided into four equally sized groups based on gender and treatment position. The full and empty bladder contour, that can be acquired with pretreatment CT imaging, were used to generate a patient-specific bladder shape model. This model was used to guide the segmentation process on CBCT. To obtain the bladder segmentation, the reference bladder contour was deformed iteratively by maximizing the cross-correlation between directional grey value gradients over the reference and CBCT bladder edge. To overcome incorrect segmentations caused by CBCT image artifacts, automatic adaptations were implemented. Moreover, locally incorrect segmentations could be adapted manually. After each adapted segmentation, the bladder shape model was expanded and new shape patterns were calculated for following segmentations. All available CBCTs were used to validate the segmentation algorithm. The bladder segmentations were validated by comparison with the manual delineations and the segmentation performance was quantified using the Dice similarity coefficient (DSC), surface distance error (SDE) and SD of contour-to-contour distances. Also, bladder volumes obtained by manual delineations and segmentations were compared using a Bland-Altman error analysis. Results: The mean DSC, mean SDE, and mean SD of contour-to-contour distances between segmentations and manual delineations were 0.87, 0.27 cm and 0.22 cm (female, prone), 0.85, 0.28 cm and 0.22 cm (female, supine), 0.89, 0.21 cm and 0.17 cm (male, supine) and 0.88, 0.23 cm and 0.17 cm (male, prone), respectively. Manual local adaptations improved the segmentation

  7. Distribution of topical ocular nepafenac and its active metabolite amfenac to the posterior segment of the eye.

    PubMed

    Chastain, James E; Sanders, Mark E; Curtis, Michael A; Chemuturi, Nagendra V; Gadd, Martha E; Kapin, Michael A; Markwardt, Kerry L; Dahlin, David C

    2016-04-01

    Nepafenac ophthalmic suspensions, 0.1% (NEVANAC(®)) and 0.3% (ILEVRO™), are topical nonsteroidal anti-inflammatory drug (NSAID) products approved in the United States, Europe and various other countries to treat pain and inflammation associated with cataract surgery. NEVANAC is also approved in Europe for the reduction in the risk of postoperative macular edema (ME) associated with cataract surgery in diabetic patients. The efficacy against ME suggests that topical administration leads to distribution of nepafenac or its active metabolite amfenac to the posterior segment of the eye. This article evaluates the ocular distribution of nepafenac and amfenac and the extent of local delivery to the posterior segment of the eye, following topical ocular instillation in animal models. Nepafenac ophthalmic suspension was instilled unilaterally in New Zealand White rabbits as either a single dose (0.1%; one drop) or as multiple doses (0.3%, one drop, once-daily for 4 days, or 0.1% one drop, three-times daily for 3 days and one morning dose on day 4). Nepafenac (0.3%) was also instilled unilaterally in cynomolgus monkeys as multiple doses (one drop, three-times daily for 7 days). Nepafenac and amfenac concentrations in harvested ocular tissues were measured using high-performance liquid chromatography/mass spectrometry. Locally-distributed compound concentrations were determined as the difference in levels between dosed and undosed eyes. In single-dosed rabbit eyes, peak concentrations of locally-distributed nepafenac and amfenac showed a trend of sclera > choroid > retina. Nepafenac peak levels in sub-samples posterior to the eye equator and inclusive of the posterior pole (E-PP) were 55.1, 4.03 and 2.72 nM, respectively, at 0.25 or 0.50 h, with corresponding amfenac peak levels of 41.9, 3.10 and 0.705 nM at 1 or 4 h. By comparison, peak levels in sclera, choroid and retina sub-samples in a band between the ora serrata and the equator (OS-E) were 13- to 40-fold

  8. Shifting boundaries of retinoic acid activity control hindbrain segmental gene expression.

    PubMed

    Sirbu, Ioan Ovidiu; Gresh, Lionel; Barra, Jacqueline; Duester, Gregg

    2005-06-01

    Retinoic acid (RA) generated by Raldh2 in paraxial mesoderm is required for specification of the posterior hindbrain, including restriction of Hoxb1 expression to presumptive rhombomere 4 (r4). Hoxb1 expression requires 3' and 5' RA response elements for widespread induction up to r4 and for r3/r5 repression, but RA has previously been detected only from r5-r8, and vHnf1 is required for repression of Hoxb1 posterior to r4 in zebrafish. We demonstrate in mouse embryos that an RA signal initially travels from the paraxial mesoderm to r3, forming a boundary next to the r2 expression domain of Cyp26a1 (which encodes an RA-degrading enzyme). After Hoxb1 induction, the RA boundary quickly shifts to r4/r5, coincident with induction of Cyp26c1 in r4. A functional role for Cyp26c1 in RA degradation was established through examination of RA-treated embryos. Analysis of Raldh2-/- and vHnf1-/- embryos supports a direct role for RA in Hoxb1 induction up to r4 and repression in r3/r5, as well as an indirect role for RA in Hoxb1 repression posterior to r4 via RA induction of vHnf1 up to the r4/r5 boundary. Our findings suggest that Raldh2 and Cyp26 generate shifting boundaries of RA activity, such that r3-r4 receives a short pulse of RA and r5-r8 receives a long pulse of RA. These two pulses of RA activity function to establish expression of Hoxb1 and vHnf1 on opposite sides of the r4/r5 boundary.

  9. Detection of activated parietal epithelial cells on the glomerular tuft distinguishes early focal segmental glomerulosclerosis from minimal change disease.

    PubMed

    Smeets, Bart; Stucker, Fabien; Wetzels, Jack; Brocheriou, Isabelle; Ronco, Pierre; Gröne, Hermann-Josef; D'Agati, Vivette; Fogo, Agnes B; van Kuppevelt, Toin H; Fischer, Hans-Peter; Boor, Peter; Floege, Jürgen; Ostendorf, Tammo; Moeller, Marcus J

    2014-12-01

    In rodents, parietal epithelial cells (PECs) migrating onto the glomerular tuft participate in the formation of focal segmental glomerulosclerosis (FSGS) lesions. We investigated whether immunohistologic detection of PEC markers in the initial biopsies of human patients with first manifestation of idiopathic nephrotic syndrome with no immune complexes can improve the sensitivity to detect sclerotic lesions compared with standard methods. Ninety-five renal biopsies were stained for claudin-1 (PEC marker), CD44 (activated PECs), and LKIV69 (PEC matrix); 38 had been diagnosed as early primary FSGS and 57 as minimal change disease. PEC markers were detected on the tuft in 87% of the biopsies of patients diagnosed as primary FSGS. PEC markers were detected in FSGS lesions from the earliest stages of disease. In minimal change disease, no PEC activation was observed by immunohistology. However, in 25% of biopsies originally diagnosed as minimal change disease the presence of small lesions indicative of a sclerosing process were detected, which were undetectable on standard periodic acid-Schiff staining, even though only a single histologic section for each PEC marker was evaluated. Staining for LKIV69 detected lesions with the highest sensitivity. Two novel PEC markers A-kinase anchor protein 12 and annexin A3 exhibited similar sensitivity. In summary, detection of PECs on the glomerular tuft by immunostaining improves the differentiation between minimal change disease and primary FSGS and may serve to guide clinical decision making.

  10. Modified contour-improved perturbation theory

    SciTech Connect

    Cvetic, Gorazd; Loewe, Marcelo; Martinez, Cristian; Valenzuela, Cristian

    2010-11-01

    The semihadronic tau decay width allows a clean extraction of the strong coupling constant at low energies. We present a modification of the standard ''contour-improved'' method based on a derivative expansion of the Adler function. The new approach has some advantages compared to contour-improved perturbation theory. The renormalization scale dependence is weaker by more than a factor of 2 and the last term of the expansion is reduced by about 10%, while the renormalization scheme dependence remains approximately equal. The extracted QCD coupling at the tau mass scale is by 2% lower than the contour-improved value. We find {alpha}{sub s}(M{sub Z}{sup 2})=0.1211{+-}0.0010.

  11. Body contouring using 635-nm low level laser therapy.

    PubMed

    Nestor, Mark S; Newburger, Jessica; Zarraga, Matthew B

    2013-03-01

    Noninvasive body contouring has become one of the fastest-growing areas of esthetic medicine. Many patients appear to prefer nonsurgical less-invasive procedures owing to the benefits of fewer side effects and shorter recovery times. Increasingly, 635-nm low-level laser therapy (LLLT) has been used in the treatment of a variety of medical conditions and has been shown to improve wound healing, reduce edema, and relieve acute pain. Within the past decade, LLLT has also emerged as a new modality for noninvasive body contouring. Research has shown that LLLT is effective in reducing overall body circumference measurements of specifically treated regions, including the hips, waist, thighs, and upper arms, with recent studies demonstrating the long-term effectiveness of results. The treatment is painless, and there appears to be no adverse events associated with LLLT. The mechanism of action of LLLT in body contouring is believed to stem from photoactivation of cytochrome c oxidase within hypertrophic adipocytes, which, in turn, affects intracellular secondary cascades, resulting in the formation of transitory pores within the adipocytes' membrane. The secondary cascades involved may include, but are not limited to, activation of cytosolic lipase and nitric oxide. Newly formed pores release intracellular lipids, which are further metabolized. Future studies need to fully outline the cellular and systemic effects of LLLT as well as determine optimal treatment protocols.

  12. Seismic activity in the transitional segment of Southern Andes after Maule 2010 megathrust earthquake

    NASA Astrophysics Data System (ADS)

    González, Diego; Lupi, Matteo; Bataille, Klaus

    2016-04-01

    It has been shown that after large magnitude earthquakes the region of volcanic arc affected by the megathrust slip is marked by an increase of volcanic activity in the following decades. The Mw = 8.8 Maule 2010 earthquake induced a rupture zone about 500 km long spanning from 33.5°S to 38.5°S. GPS and InSar data show that several volcanic edifices in the Southern Andes underwent a rapid subsidence (from days to months) after the Maule earthquake. To identify the post seismic deformation taking place in the volcanic arc after the Maule earthquake we deployed 20 seismic stations from November 2013 to March 2015 from 35°S to 39°S. We recorded ˜ 600 seismic events larger than Mw = 2.0, concentrated along the slab and beneath the volcanic chain. No events were detected at depths greater than 60 km beneath the volcanic arc. After a preliminary localization, the crustal events were relocated using an improved 1D velocity model. For the largest seismic events we inverted for moment tensor solutions. The moment tensor solution suggest a dominant N-NNE dextral strike-slip local stress field regime. This is in agreement with the direction of ancient geological structures inferred in the basement that were suggested to be reactivated by supra-lithostatic fluid pressures.

  13. The CONTOUR remote imager and spectrometer (CRISP)

    NASA Astrophysics Data System (ADS)

    Warren, Jeffery W.; Heffernan, Kevin J.; Conard, Steven J.; Bell, James F., III; Cochran, Anita L.; Boldt, John D.; Bowman, Alice F.; Darlington, E. H.; Deluzio, Anthony; Fiore, Daniel; Fort, Dennis E.; Garcia, David; Grey, Matthew P.; Gotwols, Bruce L.; Harch, Ann P.; Hayes, John R.; Heyler, Gene A.; Howser, Linda M.; Humm, David C.; Izenberg, Noam R.; Kosakowski, Kris E.; Lees, W. J.; Lohr, D. A.; Luther, Holger M.; Mehoke, Douglas S.; Murchie, Scott L.; Reiter, R. Alan; Rider, Brian; Rogers, G. D.; Sampath, Deepak; Schaefer, Edward D.; Spisz, Thomas S.; Strohbehn, Kim; Svenson, Scott; Taylor, Howard W.; Thompson, Patrick L.; Veverka, Joseph; Williams, Robert L.; Wilson, Paul

    2004-02-01

    The CONTOUR Remote Imager and Spectrometer (CRISP) was a multi-function optical instrument developed for the Comet Nucleus Tour Spacecraft (CONTOUR). CONTOUR was a NASA Discovery class mission launched on July 3, 2002. This paper describes the design, fabrication, and testing of CRISP. Unfortunately, the CONTOUR spacecraft was destroyed on August 15, 2002 during the firing of the solid rocket motor that injected it into heliocentric orbit. CRISP was designed to return high quality science data from the solid nucleus at the heart of a comet. To do this during close range (order 100 km) and high speed (order 30 km/sec) flybys, it had an autonomous nucleus acquisition and tracking system which included a one axis tracking mirror mechanism and the ability to control the rotation of the spacecraft through a closed loop interface to the guidance and control system. The track loop was closed using the same images obtained for scientific investigations. A filter imaging system was designed to obtain multispectral and broadband images at resolutions as good as 4 meters per pixel. A near IR imaging spectrometer (or hyperspectral imager) was designed to obtain spectral signatures out to 2.5 micrometers with resolution of better than 100 meters spatially. Because of the high flyby speeds, CRISP was designed as a highly automated instrument with close coupling to the spacecraft, and was intended to obtain its best data in a very short period around closest approach. CRISP was accompanied in the CONTOUR science payload by CFI, the CONTOUR Forward Imager. CFI was optimized for highly sensitive observations at greater ranges. The two instruments provided highly complementary optical capabilities, while providing some degree of functional redundancy.

  14. Pull-push level sets: a new term to encode prior knowledge for the segmentation of teeth images

    NASA Astrophysics Data System (ADS)

    de Luis Garcia, Rodrigo; San Jose Estepar, Raul; Alberola-Lopez, Carlos

    2005-04-01

    This paper presents a novel level set method for contour detection in multiple-object scenarios applied to the segmentation of teeth images. Teeth segmentation from 2D images of dental plaster cast models is a difficult problem because it is necessary to independently segment several objects that have very badly defined borders between them. Current methods for contour detection which only employ image information cannot successfully segment such structures. Being therefore necessary to use prior knowledge about the problem domain, current approaches in the literature are limited to the extraction of shape information of individual objects, whereas the key factor in such a problem are the relative positions of the different objects composing the anatomical structure. Therefore, we propose a novel method for introducing such information into a level set framework. This results in a new energy term which can be explained as a regional term that takes into account the relative positions of the different objects, and consequently creates an attraction or repulsion force that favors a determined configuration. The proposed method is compared with balloon and GVF snakes, as well as with the Geodesic Active Regions model, showing accurate results.

  15. Evaluation of Anatomical and Functional Hip Joint Center Methods: The Effects of Activity Type, Gender, and Proximal Reference Segment.

    PubMed

    McGibbon, C A; Fowler, J; Chase, S; Steeves, K; Landry, J; Mohamed, A

    2016-01-01

    Accurate hip joint center (HJC) location is critical when studying hip joint biomechanics. The HJC is often determined from anatomical methods, but functional methods are becoming increasingly popular. Several studies have examined these methods using simulations and in vivo gait data, but none has studied high-range of motion activities, such a chair rise, nor has HJC prediction been compared between males and females. Furthermore, anterior superior iliac spine (ASIS) marker visibility during chair rise can be problematic, requiring a sacral cluster as an alternative proximal segment; but functional HJC has not been explored using this approach. For this study, the quality of HJC measurement was based on the joint gap error (JGE), which is the difference in global HJC between proximal and distal reference segments. The aims of the present study were to: (1) determine if JGE varies between pelvic and sacral referenced HJC for functional and anatomical methods, (2) investigate which functional calibration motion results in the lowest JGE and if the JGE varies depending on movement type (gait versus chair rise) and gender, and (3) assess whether the functional HJC calibration results in lower JGE than commonly used anatomical approaches and if it varies with movement type and gender. Data were collected on 39 healthy adults (19 males and 20 females) aged 14-50 yr old. Participants performed four hip "calibration" tests (arc, cross, star, and star-arc), as well as gait and chair rise (activities of daily living (ADL)). Two common anatomical methods were used to estimate HJC and were compared to HJC computed using a published functional method with the calibration motions above, when using pelvis or sacral cluster as the proximal reference. For ADL trials, functional methods resulted in lower JGE (12-19 mm) compared to anatomical methods (13-34 mm). It was also found that women had significantly higher JGE compared to men and JGE was significantly higher for

  16. Evaluation of Anatomical and Functional Hip Joint Center Methods: The Effects of Activity Type, Gender, and Proximal Reference Segment.

    PubMed

    McGibbon, C A; Fowler, J; Chase, S; Steeves, K; Landry, J; Mohamed, A

    2016-01-01

    Accurate hip joint center (HJC) location is critical when studying hip joint biomechanics. The HJC is often determined from anatomical methods, but functional methods are becoming increasingly popular. Several studies have examined these methods using simulations and in vivo gait data, but none has studied high-range of motion activities, such a chair rise, nor has HJC prediction been compared between males and females. Furthermore, anterior superior iliac spine (ASIS) marker visibility during chair rise can be problematic, requiring a sacral cluster as an alternative proximal segment; but functional HJC has not been explored using this approach. For this study, the quality of HJC measurement was based on the joint gap error (JGE), which is the difference in global HJC between proximal and distal reference segments. The aims of the present study were to: (1) determine if JGE varies between pelvic and sacral referenced HJC for functional and anatomical methods, (2) investigate which functional calibration motion results in the lowest JGE and if the JGE varies depending on movement type (gait versus chair rise) and gender, and (3) assess whether the functional HJC calibration results in lower JGE than commonly used anatomical approaches and if it varies with movement type and gender. Data were collected on 39 healthy adults (19 males and 20 females) aged 14-50 yr old. Participants performed four hip "calibration" tests (arc, cross, star, and star-arc), as well as gait and chair rise (activities of daily living (ADL)). Two common anatomical methods were used to estimate HJC and were compared to HJC computed using a published functional method with the calibration motions above, when using pelvis or sacral cluster as the proximal reference. For ADL trials, functional methods resulted in lower JGE (12-19 mm) compared to anatomical methods (13-34 mm). It was also found that women had significantly higher JGE compared to men and JGE was significantly higher for

  17. Off-axis low coherence interferometry contouring

    NASA Astrophysics Data System (ADS)

    Delacrétaz, Yves; Pavillon, Nicolas; Lang, Florian; Depeursinge, Christian

    2009-12-01

    In this article we present a method to achieve tri-dimensional contouring of macroscopic objects. A modified reference wave speckle interferometer is used in conjunction with a source of reduced coherence. The depth signal is given by the envelope of the interference signal, directly determined by the coherence length of the source. Fringes are detected in the interferogram obtained by a single shot and are detected by means of adequate filtering. With the approach based on off-axis configuration, a contour line can be extracted from a single acquisition, thus allowing to use the system in harsh environment.

  18. Whole vertebral bone segmentation method with a statistical intensity-shape model based approach

    NASA Astrophysics Data System (ADS)

    Hanaoka, Shouhei; Fritscher, Karl; Schuler, Benedikt; Masutani, Yoshitaka; Hayashi, Naoto; Ohtomo, Kuni; Schubert, Rainer

    2011-03-01

    An automatic segmentation algorithm for the vertebrae in human body CT images is presented. Especially we focused on constructing and utilizing 4 different statistical intensity-shape combined models for the cervical, upper / lower thoracic and lumbar vertebrae, respectively. For this purpose, two previously reported methods were combined: a deformable model-based initial segmentation method and a statistical shape-intensity model-based precise segmentation method. The former is used as a pre-processing to detect the position and orientation of each vertebra, which determines the initial condition for the latter precise segmentation method. The precise segmentation method needs prior knowledge on both the intensities and the shapes of the objects. After PCA analysis of such shape-intensity expressions obtained from training image sets, vertebrae were parametrically modeled as a linear combination of the principal component vectors. The segmentation of each target vertebra was performed as fitting of this parametric model to the target image by maximum a posteriori estimation, combined with the geodesic active contour method. In the experimental result by using 10 cases, the initial segmentation was successful in 6 cases and only partially failed in 4 cases (2 in the cervical area and 2 in the lumbo-sacral). In the precise segmentation, the mean error distances were 2.078, 1.416, 0.777, 0.939 mm for cervical, upper and lower thoracic, lumbar spines, respectively. In conclusion, our automatic segmentation algorithm for the vertebrae in human body CT images showed a fair performance for cervical, thoracic and lumbar vertebrae.

  19. High-Throughput Prostate Cancer Gland Detection, Segmentation, and Classification from Digitized Needle Core Biopsies

    NASA Astrophysics Data System (ADS)

    Xu, Jun; Sparks, Rachel; Janowczyk, Andrew; Tomaszewski, John E.; Feldman, Michael D.; Madabhushi, Anant

    We present a high-throughput computer-aided system for the segmentation and classification of glands in high resolution digitized images of needle core biopsy samples of the prostate. It will allow for rapid and accurate identification of suspicious regions on these samples. The system includes the following three modules: 1) a hierarchical frequency weighted mean shift normalized cut (HNCut) for initial detection of glands; 2) a geodesic active contour (GAC) model for gland segmentation; and 3) a diffeomorphic based similarity (DBS) feature extraction for classification of glands as benign or cancerous. HNCut is a minimally supervised color based detection scheme that combines the frequency weighted mean shift and normalized cuts algorithms to detect the lumen region of candidate glands. A GAC model, initialized using the results of HNCut, uses a color gradient based edge detection function for accurate gland segmentation. Lastly, DBS features are a set of morphometric features derived from the nonlinear dimensionality reduction of a dissimilarity metric between shape models. The system integrates these modules to enable the rapid detection, segmentation, and classification of glands on prostate biopsy images. Across 23 H & E stained prostate studies of whole-slides, 105 regions of interests (ROIs) were selected for the evaluation of segmentation and classification. The segmentation results were evaluated on 10 ROIs and compared to manual segmentation in terms of mean distance (2.6 ±0.2 pixels), overlap (62±0.07%), sensitivity (85±0.01%), specificity (94±0.003%) and positive predictive value (68±0.08%). Over 105 ROIs, the classification accuracy for glands automatically segmented was (82.5 ±9.10%) while the accuracy for glands manually segmented was (82.89 ±3.97%); no statistically significant differences were identified between the classification results.

  20. Technical report on semiautomatic segmentation using the Adobe Photoshop.

    PubMed

    Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae; Lee, Yong Sook; Har, Dong-Hwan

    2005-12-01

    The purpose of this research is to enable users to semiautomatically segment the anatomical structures in magnetic resonance images (MRIs), computerized tomographs (CTs), and other medical images on a personal computer. The segmented images are used for making 3D images, which are helpful to medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was scanned to make 557 MRIs. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL and manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a similar manner, 13 anatomical structures in 8,590 anatomical images were segmented. Proper segmentation was verified by making 3D images from the segmented images. Semiautomatic segmentation using Adobe Photoshop is expected to be widely used for segmentation of anatomical structures in various medical images.

  1. The velocity snake: Deformable contour for tracking in spatio-velocity space

    SciTech Connect

    Peterfreund, N.

    1997-06-01

    The author presents a new active contour model for boundary tracking and position prediction of nonrigid objects, which results from applying a velocity control to the class of elastodynamical contour models, known as snakes. The proposed control term minimizes an energy dissipation function which measures the difference between the contour velocity and the apparent velocity of the image. Treating the image video-sequence as continuous measurements along time, it is shown that the proposed control results in an unbiased tracking. This is in contrast to the original snake model which is proven to be biased due to the image (object) velocity, thus resulting in high sensitivity to image clutter. The motion estimation further allows for position prediction of nonrigid boundaries. Based on the proposed control approach, the author proposes a new class of real time tracking contours, varying from models with batch-mode control estimation to models with real time adaptive controllers.

  2. Radiographic and Anatomic Basis for Prostate Contouring Errors and Methods to Improve Prostate Contouring Accuracy

    SciTech Connect

    McLaughlin, Patrick W.; Evans, Cheryl M.S.; Feng, Mary; Narayana, Vrinda

    2010-02-01

    Purpose: Use of highly conformal radiation for prostate cancer can lead to both overtreatment of surrounding normal tissues and undertreatment of the prostate itself. In this retrospective study we analyzed the radiographic and anatomic basis of common errors in computed tomography (CT) contouring and suggest methods to correct them. Methods and Materials: Three hundred patients with prostate cancer underwent CT and magnetic resonance imaging (MRI). The prostate was delineated independently on the data sets. CT and MRI contours were compared by use of deformable registration. Errors in target delineation were analyzed and methods to avoid such errors detailed. Results: Contouring errors were identified at the prostatic apex, mid gland, and base on CT. At the apex, the genitourinary diaphragm, rectum, and anterior fascia contribute to overestimation. At the mid prostate, the anterior and lateral fasciae contribute to overestimation. At the base, the bladder and anterior fascia contribute to anterior overestimation. Transition zone hypertrophy and bladder neck variability contribute to errors of overestimation and underestimation at the superior base, whereas variable prostate-to-seminal vesicle relationships with prostate hypertrophy contribute to contouring errors at the posterior base. Conclusions: Most CT contouring errors can be detected by (1) inspection of a lateral view of prostate contours to detect projection from the expected globular form and (2) recognition of anatomic structures (genitourinary diaphragm) on the CT scans that are clearly visible on MRI. This study shows that many CT prostate contouring errors can be improved without direct incorporation of MRI data.

  3. Cell segmentation in time-lapse fluorescence microscopy with temporally varying sub-cellular fusion protein patterns.

    PubMed

    Bunyak, Filiz; Palaniappan, Kannappan; Chagin, Vadim; Cardoso, M

    2009-01-01

    Fluorescently tagged proteins such as GFP-PCNA produce rich dynamically varying textural patterns of foci distributed in the nucleus. This enables the behavioral study of sub-cellular structures during different phases of the cell cycle. The varying punctuate patterns of fluorescence, drastic changes in SNR, shape and position during mitosis and abundance of touching cells, however, require more sophisticated algorithms for reliable automatic cell segmentation and lineage analysis. Since the cell nuclei are non-uniform in appearance, a distribution-based modeling of foreground classes is essential. The recently proposed graph partitioning active contours (GPAC) algorithm supports region descriptors and flexible distance metrics. We extend GPAC for fluorescence-based cell segmentation using regional density functions and dramatically improve its efficiency for segmentation from O(N(4)) to O(N(2)), for an image with N(2) pixels, making it practical and scalable for high throughput microscopy imaging studies.

  4. The Great 2006 and 2007 Kuril Earthquakes, Forearc Segmentation and Seismic Activity of the Central Kuril Islands Region

    NASA Astrophysics Data System (ADS)

    Baranov, B. V.; Ivashchenko, A. I.; Dozorova, K. A.

    2015-12-01

    We present a structural study of the Central Kuril Islands forearc region, where the great megathrust tsunamigenic earthquake ( M w 8.3) occurred on November 15, 2006. Based on new bathymetry and seismic profiles obtained during two research cruises of R/V Akademik Lavrentiev in 2005 and 2006, ten crustal segments with along-arc length ranging from 30 to 100 km, separated by NS- and NW-trending transcurrent faults were identified within the forearc region. The transcurrent faults may serve as barriers impeding stress transfer between the neighboring segments, so that stress accumulated within separate forearc segments is usually released by earthquakes of moderate-to-strong magnitudes. However, the great November 15, 2006 earthquake ruptured seven of the crustal segments probably following a 226-year gap since the last great earthquake in 1780. The geographic extent of earthquake rupture zones, aftershock areas and earthquake clusters correlate well with forearc crustal segments identified using the geophysical data. Based on segmented structure of the Central Kuril Islands forearc region, we consider and discuss three scenarios of a great earthquake occurrence within this area. Although the margin is segmented, we suggest that a rupture could occupy the entire seismic gap with a total length of about 500 km. In such a case, the earthquake magnitude M w might exceed 8.5, and such an event might generate tsunami waves significantly exceeding in height to those produced by the great 2006-2007 Kuril earthquakes.

  5. Contour junctions underlie neural representations of scene categories in high-level human visual cortex.

    PubMed

    Choo, Heeyoung; Walther, Dirk B

    2016-07-15

    Humans efficiently grasp complex visual environments, making highly consistent judgments of entry-level category despite their high variability in visual appearance. How does the human brain arrive at the invariant neural representations underlying categorization of real-world environments? We here show that the neural representation of visual environments in scene-selective human visual cortex relies on statistics of contour junctions, which provide cues for the three-dimensional arrangement of surfaces in a scene. We manipulated line drawings of real-world environments such that statistics of contour orientations or junctions were disrupted. Manipulated and intact line drawings were presented to participants in an fMRI experiment. Scene categories were decoded from neural activity patterns in the parahippocampal place area (PPA), the occipital place area (OPA) and other visual brain regions. Disruption of junctions but not orientations led to a drastic decrease in decoding accuracy in the PPA and OPA, indicating the reliance of these areas on intact junction statistics. Accuracy of decoding from early visual cortex, on the other hand, was unaffected by either image manipulation. We further show that the correlation of error patterns between decoding from the scene-selective brain areas and behavioral experiments is contingent on intact contour junctions. Finally, a searchlight analysis exposes the reliance of visually active brain regions on different sets of contour properties. Statistics of contour length and curvature dominate neural representations of scene categories in early visual areas and contour junctions in high-level scene-selective brain regions.

  6. Analysis of the structural behaviour of colonic segments by inflation tests: Experimental activity and physio-mechanical model.

    PubMed

    Carniel, Emanuele L; Mencattelli, Margherita; Bonsignori, Gabriella; Fontanella, Chiara G; Frigo, Alessandro; Rubini, Alessandro; Stefanini, Cesare; Natali, Arturo N

    2015-11-01

    A coupled experimental and computational approach is provided for the identification of the structural behaviour of gastrointestinal regions, accounting for both elastic and visco-elastic properties. The developed procedure is applied to characterize the mechanics of gastrointestinal samples from pig colons. Experimental data about the structural behaviour of colonic segments are provided by inflation tests. Different inflation processes are performed according to progressively increasing top pressure conditions. Each inflation test consists of an air in-flow, according to an almost constant increasing pressure rate, such as 3.5 mmHg/s, up to a prescribed top pressure, which is held constant for about 300 s to allow the development of creep phenomena. Different tests are interspersed by 600 s of rest to allow the recovery of the tissues' mechanical condition. Data from structural tests are post-processed by a physio-mechanical model in order to identify the mechanical parameters that interpret both the non-linear elastic behaviour of the sample, as the instantaneous pressure-stretch trend, and the time-dependent response, as the stretch increase during the creep processes. The parameters are identified by minimizing the discrepancy between experimental and model results. Different sets of parameters are evaluated for different specimens from different pigs. A statistical analysis is performed to evaluate the distribution of the parameters and to assess the reliability of the experimental and computational activities.

  7. Automatic segmentation of the lungs using robust level sets.

    PubMed

    Silveira, Margarida; Nascimento, Jacinto; Marques, Jorge

    2007-01-01

    This paper presents a method for the automatic segmentation of the lungs in X-ray computed tomography (CT) images. The proposed technique is based on the use of a robust geometric active contour that is initialized around the lungs, automatically splits in two, and performs outlier rejection during the curve evolution. The technique starts by grey-level thresholding of the images followed by edge detection. Then the edge connected points are organized into strokes and classified as valid or invalid. A confidence degree (weight) is assigned to each stroke and updated during the evolution process with the valid strokes receiving a high confidence degree and the confidence degrees of the outlier strokes tending to zero. These weights depend on the distance between the stroke points and the curve and also on the stroke size. Initialization of the curve is fully automatic. Experimental results show the effectiveness of the proposed technique.

  8. Multineuronal vectorization is more efficient than time-segmental vectorization for information extraction from neuronal activities in the inferior temporal cortex.

    PubMed

    Kaneko, Hidekazu; Tamura, Hiroshi; Tate, Shunta; Kawashima, Takahiro; Suzuki, Shinya S; Fujita, Ichiro

    2010-08-01

    In order for patients with disabilities to control assistive devices with their own neural activity, multineuronal spike trains must be efficiently decoded because only limited computational resources can be used to generate prosthetic control signals in portable real-time applications. In this study, we compare the abilities of two vectorizing procedures (multineuronal and time-segmental) to extract information from spike trains during the same total neuron-seconds. In the multineuronal vectorizing procedure, we defined a response vector whose components represented the spike counts of one to five neurons. In the time-segmental vectorizing procedure, a response vector consisted of components representing a neuron's spike counts for one to five time-segment(s) of a response period of 1 s. Spike trains were recorded from neurons in the inferior temporal cortex of monkeys presented with visual stimuli. We examined whether the amount of information of the visual stimuli carried by these neurons differed between the two vectorizing procedures. The amount of information calculated with the multineuronal vectorizing procedure, but not the time-segmental vectorizing procedure, significantly increased with the dimensions of the response vector. We conclude that the multineuronal vectorizing procedure is superior to the time-segmental vectorizing procedure in efficiently extracting information from neuronal signals.

  9. Left-ventricle segmentation in real-time 3D echocardiography using a hybrid active shape model and optimal graph search approach

    NASA Astrophysics Data System (ADS)

    Zhang, Honghai; Abiose, Ademola K.; Campbell, Dwayne N.; Sonka, Milan; Martins, James B.; Wahle, Andreas

    2010-03-01

    Quantitative analysis of the left ventricular shape and motion patterns associated with left ventricular mechanical dyssynchrony (LVMD) is essential for diagnosis and treatment planning in congestive heart failure. Real-time 3D echocardiography (RT3DE) used for LVMD analysis is frequently limited by heavy speckle noise or partially incomplete data, thus a segmentation method utilizing learned global shape knowledge is beneficial. In this study, the endocardial surface of the left ventricle (LV) is segmented using a hybrid approach combining active shape model (ASM) with optimal graph search. The latter is used to achieve landmark refinement in the ASM framework. Optimal graph search translates the 3D segmentation into the detection of a minimum-cost closed set in a graph and can produce a globally optimal result. Various information-gradient, intensity distributions, and regional-property terms-are used to define the costs for the graph search. The developed method was tested on 44 RT3DE datasets acquired from 26 LVMD patients. The segmentation accuracy was assessed by surface positioning error and volume overlap measured for the whole LV as well as 16 standard LV regions. The segmentation produced very good results that were not achievable using ASM or graph search alone.

  10. Transmembrane segments of complement receptor 3 do not participate in cytotoxic activities but determine receptor structure required for action of Bordetella adenylate cyclase toxin.

    PubMed

    Wald, Tomas; Osickova, Adriana; Masin, Jiri; Liskova, Petra M; Petry-Podgorska, Inga; Matousek, Tomas; Sebo, Peter; Osicka, Radim

    2016-04-01

    Adenylate cyclase toxin-hemolysin (CyaA, ACT or AC-Hly) of the whooping cough agent Bordetella pertussis penetrates phagocytes expressing the integrin complement receptor 3 (CR3, CD11b/CD18, α(M)β(2) or Mac-1). CyaA translocates its adenylate cyclase (AC) enzyme domain into cell cytosol and catalyzes unregulated conversion of ATP to cAMP, thereby subverting cellular signaling. In parallel, CyaA forms small cation-selective membrane pores that permeabilize cells for potassium efflux, contributing to cytotoxicity of CyaA and eventually provoking colloid-osmotic cell lysis. To investigate whether the single-pass α-helical transmembrane segments of CR3 subunits CD11b and CD18 do directly participate in AC domain translocation and/or pore formation by the toxin, we expressed in CHO cells variants of CR3 that contained artificial transmembrane segments, or lacked the transmembrane segment(s) at all. The results demonstrate that the transmembrane segments of CR3 are not directly involved in the cytotoxic activities of CyaA but serve for maintaining CR3 in a conformation that is required for efficient toxin binding and action. PMID:26802078

  11. RANSAC-based EM algorithm for robust detection and segmentation of cylindrical fragments from calibrated C-arm images

    NASA Astrophysics Data System (ADS)

    Zheng, Guoyan; Dong, Xiao; Zhang, Xuan

    2006-03-01

    Automated identification, pose and size estimation of cylindrical fragments from registered C-arm images is highly desirable in various computer-assisted, fluoroscopy-based applications including long bone fracture reduction and intramedullary nailing, where the pose and size of bone fragment need to be accurately estimated for a better treatment. In this paper, a RANSAC-based EM algorithm for robust detection and segmentation of cylindrical fragments from calibrated C-arm images is presented. By detection, we mean that the axes and the radii of the principal fragments will be automatically determined. And by segmentation, we mean that the contour of the fragment projection onto each image plane will be automatically extracted. Benefited from the cylindrical shape of the fragments, we formulate the detection problem as an optimal process for fitting parameterized three-dimensional (3D) cylinder model to images. A RANSAC-based EM algorithm is proposed to find the optimal solution by converting the fragment detection procedure to an iterative closest point (ICP) matching procedure. The outer projection boundary of the estimated cylinder model is then fed to a region-based active contour model to robustly extract the contour of the fragment projection. The proposed algorithm has been successfully applied to real patient data with/without external objects, yielding promising results.

  12. DTI segmentation using an information theoretic tensor dissimilarity measure.

    PubMed

    Wang, Zhizhou; Vemuri, Baba C

    2005-10-01

    In recent years, diffusion tensor imaging (DTI) has become a popular in vivo diagnostic imaging technique in Radiological sciences. In order for this imaging technique to be more effective, proper image analysis techniques suited for analyzing these high dimensional data need to be developed. In this paper, we present a novel definition of tensor "distance" grounded in concepts from information theory and incorporate it in the segmentation of DTI. In a DTI, the symmetric positive definite (SPD) diffusion tensor at each voxel can be interpreted as the covariance matrix of a local Gaussian distribution. Thus, a natural measure of dissimilarity between SPD tensors would be the Kullback-Leibler (KL) divergence or its relative. We propose the square root of the J-divergence (symmetrized KL) between two Gaussian distributions corresponding to the diffusion tensors being compared and this leads to a novel closed form expression for the "distance" as well as the mean value of a DTI. Unlike the traditional Frobenius norm-based tensor distance, our "distance" is affine invariant, a desirable property in segmentation and many other applications. We then incorporate this new tensor "distance" in a region based active contour model for DTI segmentation. Synthetic and real data experiments are shown to depict the performance of the proposed model.

  13. Contour Mapping for Pools and Ponds.

    ERIC Educational Resources Information Center

    Berry, Noel

    1985-01-01

    Simple jigs (positioning devices) to make contour mapping tasks easier and more accurate are easily constructed from 5mm-thick acetate sheets. These plastic holders are used with meter sticks to provide scanning guides to measure pools and ponds. Instructions for making the jigs and sample results are included. (DH)

  14. Expectations for Melodic Contours Transcend Pitch

    PubMed Central

    Graves, Jackson E.; Micheyl, Christophe; Oxenham, Andrew J.

    2015-01-01

    The question of what makes a good melody has interested composers, music theorists, and psychologists alike. Many of the observed principles of good “melodic continuation” involve melodic contour – the pattern of rising and falling pitch within a sequence. Previous work has shown that contour perception can extend beyond pitch to other auditory dimensions, such as brightness and loudness. Here, we show with two experiments that the generalization of contour perception to non-traditional dimensions also extends to melodic expectations. In the first experiment, subjective ratings for three-tone sequences that vary in brightness or loudness conformed to the same general contour-based expectations as pitch sequences. In the second experiment, we modified the sequence of melody presentation such that melodies with the same beginning were blocked together. This change produced substantively different results, but the patterns of ratings remained similar across the three auditory dimensions. Taken together, these results suggest that 1) certain well-known principles of melodic expectation (such as the expectation for a reversal following a skip) are dependent on long-term context, and 2) these expectations are not unique to the dimension of pitch and may instead reflect more general principles of perceptual organization. PMID:25365571

  15. Contour completion through depth interferes with stereoacuity

    NASA Technical Reports Server (NTRS)

    Vreven, Dawn; McKee, Suzanne P.; Verghese, Preeti

    2002-01-01

    Local disparity signals must interact in visual cortex to represent boundaries and surfaces of three-dimensional (3D) objects. We investigated how disparity signals interact in 3D contours and in 3D surfaces generated from the contours. We compared flat (single disparity) stimuli with curved (multi-disparity) stimuli. We found no consistent differences in sensitivity to contours vs. surfaces; for equivalent amounts of disparity, however, observers were more sensitive to flat stimuli than curved stimuli. Poor depth sensitivity for curved stimuli cannot be explained by the larger range of disparities present in the curved surface, nor by disparity averaging, nor by poor sensitivity to the largest disparity in the stimulus. Surprisingly, sensitivity to surfaces curved in depth was improved by removing portions of the surface and thus removing disparity information. Stimulus configuration had a profound effect on stereo thresholds that cannot be accounted for by disparity-energy models of V1 processing. We suggest that higher-level 3D contour or 3D shape mechanisms are involved.

  16. Molding Compound For Inspection Of Internal Contours

    NASA Technical Reports Server (NTRS)

    Adams, Jim; Ricklefs, Steve

    1988-01-01

    Material clean, sets rapidly, and easy to use. Silicone elastomer, Citrocon or equivalent, commonly used in dentistry, in combination with mold-release agent (Also see MFS-29240), speeds and facilitates making of impressions of interior surfaces so surface contours examined. Elastomer easily moved around in cavity until required location found.

  17. Automatic Contour Tracking in Ultrasound Images

    ERIC Educational Resources Information Center

    Li, Min; Kambhamettu, Chandra; Stone, Maureen

    2005-01-01

    In this paper, a new automatic contour tracking system, EdgeTrak, for the ultrasound image sequences of human tongue is presented. The images are produced by a head and transducer support system (HATS). The noise and unrelated high-contrast edges in ultrasound images make it very difficult to automatically detect the correct tongue surfaces. In…

  18. contbin: Contour binning and accumulative smoothing

    NASA Astrophysics Data System (ADS)

    Sanders, Jeremy S.

    2016-09-01

    Contbin bins X-ray data using contours on an adaptively smoothed map. The generated bins closely follow the surface brightness, and are ideal where the surface brightness distribution is not smooth, or the spectral properties are expected to follow surface brightness. Color maps can be used instead of surface brightness maps.

  19. Contour-measuring tool for composite layups

    NASA Technical Reports Server (NTRS)

    Fontes, M. J.

    1981-01-01

    Simple handtool helps form contours and complex shapes from laminae of resin-impregnated fabric. Tool, which consists of yoke having ballpoint pen and spindle and gage, is placed so that it straddles model. As toll is moved, pen draws constant thickness focus that is used as template.

  20. Aircraft noise source and contour estimation

    NASA Technical Reports Server (NTRS)

    Dunn, D. G.; Peart, N. A.

    1973-01-01

    Calculation procedures are presented for predicting the noise-time histories and noise contours (footprints) of five basic types of aircraft; turbojet, turofan, turboprop, V/STOL, and helicopter. The procedures have been computerized to facilitate prediction of the noise characteristics during takeoffs, flyovers, and/or landing operations.

  1. Contoured Orifice for Silicon-Ribbon Die

    NASA Technical Reports Server (NTRS)

    Mackintosh, B. H.

    1985-01-01

    Die configuration encourages purity and stable growth. Contour of die orifice changes near ribbon edges. As result, silicon ribbon has nearly constant width and little carbon contamination. Die part of furnace being developed to produce high-quality, low-cost material for solar cells.

  2. Improved discrimination in photographic density contouring

    NASA Technical Reports Server (NTRS)

    Godding, R. A.

    1974-01-01

    Density discrimination can be accomplished through use of special photographic contouring material which has two sensitive layers (one negative, one positive) on single support. Process will be of interest to investigators who require finer discrimination of densities of original photograph for purposes such as identification of crops and analysis of energy levels of radiating objects.

  3. Multimodality medical image fusion: probabilistic quantification, segmentation, and registration

    NASA Astrophysics Data System (ADS)

    Wang, Yue J.; Freedman, Matthew T.; Xuan, Jian Hua; Zheng, Qinfen; Mun, Seong K.

    1998-06-01

    Multimodality medical image fusion is becoming increasingly important in clinical applications, which involves information processing, registration and visualization of interventional and/or diagnostic images obtained from different modalities. This work is to develop a multimodality medical image fusion technique through probabilistic quantification, segmentation, and registration, based on statistical data mapping, multiple feature correlation, and probabilistic mean ergodic theorems. The goal of image fusion is to geometrically align two or more image areas/volumes so that pixels/voxels representing the same underlying anatomical structure can be superimposed meaningfully. Three steps are involved. To accurately extract the regions of interest, we developed the model supported Bayesian relaxation labeling, and edge detection and region growing integrated algorithms to segment the images into objects. After identifying the shift-invariant features (i.e., edge and region information), we provided an accurate and robust registration technique which is based on matching multiple binary feature images through a site model based image re-projection. The image was initially segmented into specified number of regions. A rough contour can be obtained by delineating and merging some of the segmented regions. We applied region growing and morphological filtering to extract the contour and get rid of some disconnected residual pixels after segmentation. The matching algorithm is implemented as follows: (1) the centroids of PET/CT and MR images are computed and then translated to the center of both images. (2) preliminary registration is performed first to determine an initial range of scaling factors and rotations, and the MR image is then resampled according to the specified parameters. (3) the total binary difference of the corresponding binary maps in both images is calculated for the selected registration parameters, and the final registration is achieved when the

  4. Segmentation of laser range image for pipe anomaly detection

    NASA Astrophysics Data System (ADS)

    Liu, Zheng; Krys, Dennis

    2010-04-01

    Laser-based scanning can provide a precise surface profile. It has been widely applied to the inspection of pipe inner walls and is often used along with other types of sensors, like sonar and close-circuit television (CCTV). These measurements can be used for pipe deterioration modeling and condition assessment. Geometric information needs to be extracted to characterize anomalies in the pipe profile. Since the laser scanning measures the distance, segmentation with a threshold is a straightforward way to isolate the anomalies. However, threshold with a fixed distance value does not work well for the laser range image due to the intensity inhomogeneity, which is caused the uncontrollable factors during the inspection. Thus, a local binary fitting (LBF) active contour model is employed in this work to process the laser range image and an image phase congruency algorithm is adopted to provide the initial contour as required by the LBF method. The combination of these two approaches can successfully detect the anomalies from a laser range image.

  5. Precision of Myocardial Contour Estimation from Tagged MR Images with a “Black-Blood” Technique1

    PubMed Central

    Croisille, P.; Guttman, M. A.; Atalar, E.; McVeigh, E. R.; Zerhouni, E. A.

    2007-01-01

    Rationale and Objectives The authors determined whether blood presaturation of tagged magnetic resonance (MR) images affects identification of left ventricular endocardial borders. Materials and Methods Three healthy volunteers underwent MR imaging performed with a breath-hold segmented spoiled gradient-recalled-echo sequence with tissue tagging. Two saturation pulses (in the basal and apical regions) were used to generate black-blood images. Manual segmentation of endocardial contours on black-blood and white-blood images was performed independently by five observers. Results Endocardial borders were better identified on black-blood images compared with white-blood images, especially in the early systolic phases. Interobserver variability in contour estimation was significantly higher for white-blood images (P < .001) and was twice that for corresponding black-blood images during early systole. Contour variability appeared to be affected mainly by tag-to-myocardium contrast (P = .009) and myocardium-to-chamber contrast (P = .05). Conclusion Blood presaturation of tagged MR images improves reliability of contour segmentation. PMID:9484541

  6. Fast retinal layer segmentation of spectral domain optical coherence tomography images

    NASA Astrophysics Data System (ADS)

    Zhang, Tianqiao; Song, Zhangjun; Wang, Xiaogang; Zheng, Huimin; Jia, Fucang; Wu, Jianhuang; Li, Guanglin; Hu, Qingmao

    2015-09-01

    An approach to segment macular layer thicknesses from spectral domain optical coherence tomography has been proposed. The main contribution is to decrease computational costs while maintaining high accuracy via exploring Kalman filtering, customized active contour, and curve smoothing. Validation on 21 normal volumes shows that 8 layer boundaries could be segmented within 5.8 s with an average layer boundary error <2.35 μm. It has been compared with state-of-the-art methods for both normal and age-related macular degeneration cases to yield similar or significantly better accuracy and is 37 times faster. The proposed method could be a potential tool to clinically quantify the retinal layer boundaries.

  7. Fast retinal layer segmentation of spectral domain optical coherence tomography images.

    PubMed

    Zhang, Tianqiao; Song, Zhangjun; Wang, Xiaogang; Zheng, Huimin; Jia, Fucang; Wu, Jianhuang; Li, Guanglin; Hu, Qingmao

    2015-01-01

    An approach to segment macular layer thicknesses from spectral domain optical coherence tomography has been proposed. The main contribution is to decrease computational costs while maintaining high accuracy via exploring Kalman filtering, customized active contour, and curve smoothing. Validation on 21 normal volumes shows that 8 layer boundaries could be segmented within 5.8 s with an average layer boundary error <2.35 μm. It has been compared with state-of-the-art methods for both normal and age-related macular degeneration cases to yield similar or significantly better accuracy and is 37 times faster. The proposed method could be a potential tool to clinically quantify the retinal layer boundaries. PMID:26385655

  8. Extracting contours of oval-shaped objects by Hough transform and minimal path algorithms

    NASA Astrophysics Data System (ADS)

    Tleis, Mohamed; Verbeek, Fons J.

    2014-04-01

    Circular and oval-like objects are very common in cell and micro biology. These objects need to be analyzed, and to that end, digitized images from the microscope are used so as to come to an automated analysis pipeline. It is essential to detect all the objects in an image as well as to extract the exact contour of each individual object. In this manner it becomes possible to perform measurements on these objects, i.e. shape and texture features. Our measurement objective is achieved by probing contour detection through dynamic programming. In this paper we describe a method that uses Hough transform and two minimal path algorithms to detect contours of (ovoid-like) objects. These algorithms are based on an existing grey-weighted distance transform and a new algorithm to extract the circular shortest path in an image. The methods are tested on an artificial dataset of a 1000 images, with an F1-score of 0.972. In a case study with yeast cells, contours from our methods were compared with another solution using Pratt's figure of merit. Results indicate that our methods were more precise based on a comparison with a ground-truth dataset. As far as yeast cells are concerned, the segmentation and measurement results enable, in future work, to retrieve information from different developmental stages of the cell using complex features.

  9. Segmentation of the thrombus of giant intracranial aneurysms from CT angiography scans with lattice Boltzmann method.

    PubMed

    Chen, Yu; Navarro, Laurent; Wang, Yan; Courbebaisse, Guy

    2014-01-01

    Computed Tomography Angiography (CTA) plays an essential role in the diagnosis, treatment evaluation, and monitoring of cerebral aneurysms. Segmentation of CTA medical images of giant intracranial aneurysms (GIA) provides quantitative measurements of thrombus and aneurysms geometrical characteristics allowing 3D reconstruction. In fact, GIA demonstrated neuroradiological features and propensity of partial or total spontaneous intra-aneurysmal thrombosis generating a thrombus. Despite intensive researches on medical image segmentation, aneurysm (Lumen, Thrombus, and Parent Blood Vessels) segmentation remains as a difficult problem that has not been yet resolved. In this paper, we proposed a Lattice Boltzmann Geodesic Active Contour Method (LBGM) for aneurysm segmentation in CTA images in order to estimate both the volumes of the thrombus and the aneurysm. Although the noise in the CTA images is very strong and the edges of the thrombus are not so different than the surrounding tissues, the aneurysms are segmented effectively. Based on these results, a method using a dome-neck aspect ratio (AR) parameter for the evaluation of the Spontaneous Thrombosis (ST) phenomena demonstrates the promising potentiality of this LBGM for clinical applications. PMID:24077409

  10. Tumor Burden Analysis on Computed Tomography by Automated Liver and Tumor Segmentation

    PubMed Central

    Linguraru, Marius George; Richbourg, William J.; Liu, Jianfei; Watt, Jeremy M.; Pamulapati, Vivek; Wang, Shijun; Summers, Ronald M.

    2013-01-01

    The paper presents the automated computation of hepatic tumor burden from abdominal CT images of diseased populations with images with inconsistent enhancement. The automated segmentation of livers is addressed first. A novel three-dimensional (3D) affine invariant shape parameterization is employed to compare local shape across organs. By generating a regular sampling of the organ's surface, this parameterization can be effectively used to compare features of a set of closed 3D surfaces point-to-point, while avoiding common problems with the parameterization of concave surfaces. From an initial segmentation of the livers, the areas of atypical local shape are determined using training sets. A geodesic active contour corrects locally the segmentations of the livers in abnormal images. Graph cuts segment the hepatic tumors using shape and enhancement constraints. Liver segmentation errors are reduced significantly and all tumors are detected. Finally, support vector machines and feature selection are employed to reduce the number of false tumor detections. The tumor detection true position fraction of 100% is achieved at 2.3 false positives/case and the tumor burden is estimated with 0.9% error. Results from the test data demonstrate the method's robustness to analyze livers from difficult clinical cases to allow the temporal monitoring of patients with hepatic cancer. PMID:22893379

  11. Rule-based fuzzy vector median filters for 3D phase contrast MRI segmentation

    NASA Astrophysics Data System (ADS)

    Sundareswaran, Kartik S.; Frakes, David H.; Yoganathan, Ajit P.

    2008-02-01

    Recent technological advances have contributed to the advent of phase contrast magnetic resonance imaging (PCMRI) as standard practice in clinical environments. In particular, decreased scan times have made using the modality more feasible. PCMRI is now a common tool for flow quantification, and for more complex vector field analyses that target the early detection of problematic flow conditions. Segmentation is one component of this type of application that can impact the accuracy of the final product dramatically. Vascular segmentation, in general, is a long-standing problem that has received significant attention. Segmentation in the context of PCMRI data, however, has been explored less and can benefit from object-based image processing techniques that incorporate fluids specific information. Here we present a fuzzy rule-based adaptive vector median filtering (FAVMF) algorithm that in combination with active contour modeling facilitates high-quality PCMRI segmentation while mitigating the effects of noise. The FAVMF technique was tested on 111 synthetically generated PC MRI slices and on 15 patients with congenital heart disease. The results were compared to other multi-dimensional filters namely the adaptive vector median filter, the adaptive vector directional filter, and the scalar low pass filter commonly used in PC MRI applications. FAVMF significantly outperformed the standard filtering methods (p < 0.0001). Two conclusions can be drawn from these results: a) Filtering should be performed after vessel segmentation of PC MRI; b) Vector based filtering methods should be used instead of scalar techniques.

  12. Automatic liver contouring for radiotherapy treatment planning.

    PubMed

    Li, Dengwang; Liu, Li; Kapp, Daniel S; Xing, Lei

    2015-10-01

    To develop automatic and efficient liver contouring software for planning 3D-CT and four-dimensional computed tomography (4D-CT) for application in clinical radiation therapy treatment planning systems.The algorithm comprises three steps for overcoming the challenge of similar intensities between the liver region and its surrounding tissues. First, the total variation model with the L1 norm (TV-L1), which has the characteristic of multi-scale decomposition and an edge-preserving property, is used for removing the surrounding muscles and tissues. Second, an improved level set model that contains both global and local energy functions is utilized to extract liver contour information sequentially. In the global energy function, the local correlation coefficient (LCC) is constructed based on the gray level co-occurrence matrix both of the initial liver region and the background region. The LCC can calculate the correlation of a pixel with the foreground and background regions, respectively. The LCC is combined with intensity distribution models to classify pixels during the evolutionary process of the level set based method. The obtained liver contour is used as the candidate liver region for the following step. In the third step, voxel-based texture characterization is employed for refining the liver region and obtaining the final liver contours.The proposed method was validated based on the planning CT images of a group of 25 patients undergoing radiation therapy treatment planning. These included ten lung cancer patients with normal appearing livers and ten patients with hepatocellular carcinoma or liver metastases. The method was also tested on abdominal 4D-CT images of a group of five patients with hepatocellular carcinoma or liver metastases. The false positive volume percentage, the false negative volume percentage, and the dice similarity coefficient between liver contours obtained by a developed algorithm and a current standard delineated by the expert group

  13. Automatic liver contouring for radiotherapy treatment planning

    NASA Astrophysics Data System (ADS)

    Li, Dengwang; Liu, Li; Kapp, Daniel S.; Xing, Lei

    2015-09-01

    To develop automatic and efficient liver contouring software for planning 3D-CT and four-dimensional computed tomography (4D-CT) for application in clinical radiation therapy treatment planning systems. The algorithm comprises three steps for overcoming the challenge of similar intensities between the liver region and its surrounding tissues. First, the total variation model with the L1 norm (TV-L1), which has the characteristic of multi-scale decomposition and an edge-preserving property, is used for removing the surrounding muscles and tissues. Second, an improved level set model that contains both global and local energy functions is utilized to extract liver contour information sequentially. In the global energy function, the local correlation coefficient (LCC) is constructed based on the gray level co-occurrence matrix both of the initial liver region and the background region. The LCC can calculate the correlation of a pixel with the foreground and background regions, respectively. The LCC is combined with intensity distribution models to classify pixels during the evolutionary process of the level set based method. The obtained liver contour is used as the candidate liver region for the following step. In the third step, voxel-based texture characterization is employed for refining the liver region and obtaining the final liver contours. The proposed method was validated based on the planning CT images of a group of 25 patients undergoing radiation therapy treatment planning. These included ten lung cancer patients with normal appearing livers and ten patients with hepatocellular carcinoma or liver metastases. The method was also tested on abdominal 4D-CT images of a group of five patients with hepatocellular carcinoma or liver metastases. The false positive volume percentage, the false negative volume percentage, and the dice similarity coefficient between liver contours obtained by a developed algorithm and a current standard delineated by the expert group

  14. [External contour acquisition system for radiotherapy: an original solution].

    PubMed

    Létourneau, D; Brochet, F; Bohémier, R; Gagnon, J

    2000-01-01

    A contour acquisition system has been designed in radiotherapy at the Sagamie Hospital complex (Chicoutimi, Québec) to measure the external contours of the patients who do not need a CT exam. This measuring system can produce transversal, sagittal or coronal patient contours in the treatment position. The absolute accuracy of the system is +/- 1 mm. The contours produced by this equipment can be transferred electronically or on paper to the planning system.

  15. Automatic Delineation of the Myocardial Wall from CT Images via Shape Segmentation and Variational Region Growing

    PubMed Central

    Zhu, Liangjia; Gao, Yi; Appia, Vikram; Yezzi, Anthony; Arepalli, Chesnal; Faber, Tracy; Stillman, Arthur; Tannenbaum, Allen

    2014-01-01

    Prognosis and diagnosis of cardiac diseases frequently require quantitative evaluation of the ventricle volume, mass, and ejection fraction. The delineation of the myocardial wall is involved in all of these evaluations, which is a challenging task due to large variations in myocardial shapes and image quality. In this work, we present an automatic method for extracting the myocardial wall of the left and right ventricles from cardiac CT images. In the method, the left and right ventricles are located sequentially, in which each ventricle is detected by first identifying the endocardium and then segmenting the epicardium. To this end, the endocardium is localized by utilizing its geometric features obtained on-line from a CT image. After that, a variational region-growing model is employed to extract the epicardium of the ventricles. In particular, the location of the endocardium of the left ventricle is determined via using an active contour model on the blood-pool surface. To localize the right ventricle, the active contour model is applied on a heart surface extracted based on the left ventricle segmentation result. The robustness and accuracy of the proposed approach is demonstrated by experimental results from 33 human and 12 pig CT images. PMID:23744658

  16. Placental fetal stem segmentation in a sequence of histology images

    NASA Astrophysics Data System (ADS)

    Athavale, Prashant; Vese, Luminita A.

    2012-02-01

    Recent research in perinatal pathology argues that analyzing properties of the placenta may reveal important information on how certain diseases progress. One important property is the structure of the placental fetal stems. Analysis of the fetal stems in a placenta could be useful in the study and diagnosis of some diseases like autism. To study the fetal stem structure effectively, we need to automatically and accurately track fetal stems through a sequence of digitized hematoxylin and eosin (H&E) stained histology slides. There are many problems in successfully achieving this goal. A few of the problems are: large size of images, misalignment of the consecutive H&E slides, unpredictable inaccuracies of manual tracing, very complicated texture patterns of various tissue types without clear characteristics, just to name a few. In this paper we propose a novel algorithm to achieve automatic tracing of the fetal stem in a sequence of H&E images, based on an inaccurate manual segmentation of a fetal stem in one of the images. This algorithm combines global affine registration, local non-affine registration and a novel 'dynamic' version of the active contours model without edges. We first use global affine image registration of all the images based on displacement, scaling and rotation. This gives us approximate location of the corresponding fetal stem in the image that needs to be traced. We then use the affine registration algorithm "locally" near this location. At this point, we use a fast non-affine registration based on L2-similarity measure and diffusion regularization to get a better location of the fetal stem. Finally, we have to take into account inaccuracies in the initial tracing. This is achieved through a novel dynamic version of the active contours model without edges where the coefficients of the fitting terms are computed iteratively to ensure that we obtain a unique stem in the segmentation. The segmentation thus obtained can then be used as an

  17. 47 CFR 73.311 - Field strength contours.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 4 2011-10-01 2011-10-01 false Field strength contours. 73.311 Section 73.311... Broadcast Stations § 73.311 Field strength contours. (a) Applications for FM broadcast authorizations must show the field strength contours required by FCC Form 301 or FCC Form 340, as appropriate. (b)...

  18. 47 CFR 73.311 - Field strength contours.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 4 2012-10-01 2012-10-01 false Field strength contours. 73.311 Section 73.311... Broadcast Stations § 73.311 Field strength contours. (a) Applications for FM broadcast authorizations must show the field strength contours required by FCC Form 301 or FCC Form 340, as appropriate. (b)...

  19. 47 CFR 73.311 - Field strength contours.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 4 2010-10-01 2010-10-01 false Field strength contours. 73.311 Section 73.311... Broadcast Stations § 73.311 Field strength contours. (a) Applications for FM broadcast authorizations must show the field strength contours required by FCC Form 301 or FCC Form 340, as appropriate. (b)...

  20. 47 CFR 73.311 - Field strength contours.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 47 Telecommunication 4 2013-10-01 2013-10-01 false Field strength contours. 73.311 Section 73.311... Broadcast Stations § 73.311 Field strength contours. (a) Applications for FM broadcast authorizations must show the field strength contours required by FCC Form 301 or FCC Form 340, as appropriate. (b)...

  1. 47 CFR 73.311 - Field strength contours.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 47 Telecommunication 4 2014-10-01 2014-10-01 false Field strength contours. 73.311 Section 73.311... Broadcast Stations § 73.311 Field strength contours. (a) Applications for FM broadcast authorizations must show the field strength contours required by FCC Form 301 or FCC Form 340, as appropriate. (b)...

  2. TH-C-18A-02: Machine Learning and STAPLE Based Simultaneous Longitudinal Segmentation of Bone and Marrow Structures From Dual Energy CT

    SciTech Connect

    Fehr, D; Schmidtlein, C; Hwang, S; Deasy, J; Veeraraghavan, H

    2014-06-15

    Purpose: To develop a fully-automatic longitudinal bone and marrow segmentation method in the pelvic region from dual energy computed tomography (DECT). Methods: We developed a two-step automatic bone and marrow segmentation method for simultaneous longitudinal evaluation of patients with metastatic bone disease using dual energy CT (DECT). Our approach transforms the DECT images into a multi-material decomposition (MMD) model that represents the voxels as a mixture of multiple materials. A support vector machine (SVM) was trained using a single scan. In the first step of the longitudinal segmentation the trained SVM model detects bone and marrow structures on all available longitudinal scans. Segmentation is further refined through active contour segmentation. In the second step, the segmentations from the individual scans are merged by employing the simultaneous truth and performance level estimation (STAPLE) algorithm. The scans are registered using affine and deformable registration. We found that our approach improves the segmentation in all the scans under reliable registration performance between the same scans. Improving registration was not under the scope of this work. Results: We applied our approach to segment bone and marrow in DECT scans in the pelvic regions for multiple patients. Each patient had three to five follow up scans. All the patients in the analysis had artificial metal prostheses which introduced challenges for the registration. Our algorithm achieved reasonable accurate segmentation despite the presence of metal artifacts and high-density oral contrast in neighboring structures. Our approach obtained an overall segmentation accuracy of 80% using DICE metric. Conclusion: We developed a two-step automatic longitudinal segmentation technique for bone and marrow region structures in the pelvic areas from dual energy CT. Our approach achieves robust segmentation despite the presence of confounding structures with similar intensities as the

  3. Contour detection combined with depth information

    NASA Astrophysics Data System (ADS)

    Xiao, Jie; Cai, Chao

    2015-12-01

    Many challenging computer vision problems have been proven to benefit from the incorporation of depth information, to name a few, semantic labellings, pose estimations and even contour detection. Different objects have different depths from a single monocular image. The depth information of one object is coherent and the depth information of different objects may vary discontinuously. Meanwhile, there exists a broad non-classical receptive field (NCRF) outside the classical receptive field (CRF). The response of the central neuron is affected not only by the stimulus inside the CRF, but also modulated by the stimulus surrounding it. The contextual modulation is mediated by horizontal connections across the visual cortex. Based on the findings and researches, a biological-inspired contour detection model which combined with depth information is proposed in this paper.

  4. Contour forming of metals by laser peening

    DOEpatents

    Hackel, Lloyd; Harris, Fritz

    2002-01-01

    A method and apparatus are provided for forming shapes and contours in metal sections by generating laser induced compressive stress on the surface of the metal workpiece. The laser process can generate deep compressive stresses to shape even thick components without inducing unwanted tensile stress at the metal surface. The precision of the laser-induced stress enables exact prediction and subsequent contouring of parts. A light beam of 10 to 100 J/pulse is imaged to create an energy fluence of 60 to 200 J/cm.sup.2 on an absorptive layer applied over a metal surface. A tamping layer of water is flowed over the absorptive layer. The absorption of laser light causes a plasma to form and consequently creates a shock wave that induces a deep residual compressive stress into the metal. The metal responds to this residual stress by bending.

  5. Thermal contouring of forestry data: Wallops Island

    NASA Technical Reports Server (NTRS)

    Thomson, F.

    1972-01-01

    The contouring of 8-13.5 micrometer thermal data collected over a forestry site in Virginia is described. The data were collected at an altitude of 1000 ft above terrain on November 4, 1970. The site was covered on three approximately parallel lines. The purpose of the contouring was to attempt to delineate pine trees attacked by southern pine bark beetle, and to map other important terrain categories. Special processing steps were required to achieve the correct aspect ratio of the thermal data. The reference for the correction procedure was color infrared photography. Data form and quality are given, processing steps are outlined, a brief interpretation of results is given, and conclusion are presented.

  6. Liver segmentation for CT images using GVF snake

    SciTech Connect

    Liu Fan; Zhao Binsheng; Kijewski, Peter K.; Wang Liang; Schwartz, Lawrence H.

    2005-12-15

    Accurate liver segmentation on computed tomography (CT) images is a challenging task especially at sites where surrounding tissues (e.g., stomach, kidney) have densities similar to that of the liver and lesions reside at the liver edges. We have developed a method for semiautomatic delineation of the liver contours on contrast-enhanced CT images. The method utilizes a snake algorithm with a gradient vector flow (GVF) field as its external force. To improve the performance of the GVF snake in the segmentation of the liver contour, an edge map was obtained with a Canny edge detector, followed by modifications using a liver template and a concavity removal algorithm. With the modified edge map, for which unwanted edges inside the liver were eliminated, the GVF field was computed and an initial liver contour was formed. The snake algorithm was then applied to obtain the actual liver contour. This algorithm was extended to segment the liver volume in a slice-by-slice fashion, where the result of the preceding slice constrained the segmentation of the adjacent slice. 551 two-dimensional liver images from 20 volumetric images with colorectal metastases spreading throughout the livers were delineated using this method, and also manually by a radiologist for evaluation. The difference ratio, which is defined as the percentage ratio of mismatching volume between the computer and the radiologist's results, ranged from 2.9% to 7.6% with a median value of 5.3%.

  7. Wearable Multi-Frequency and Multi-Segment Bioelectrical Impedance Spectroscopy for Unobtrusively Tracking Body Fluid Shifts during Physical Activity in Real-Field Applications: A Preliminary Study

    PubMed Central

    Villa, Federica; Magnani, Alessandro; Maggioni, Martina A.; Stahn, Alexander; Rampichini, Susanna; Merati, Giampiero; Castiglioni, Paolo

    2016-01-01

    Bioelectrical Impedance Spectroscopy (BIS) allows assessing the composition of body districts noninvasively and quickly, potentially providing important physiological/clinical information. However, neither portable commercial instruments nor more advanced wearable prototypes simultaneously satisfy the demanding needs of unobtrusively tracking body fluid shifts in different segments simultaneously, over a broad frequency range, for long periods and with high measurements rate. These needs are often required to evaluate exercise tests in sports or rehabilitation medicine, or to assess gravitational stresses in aerospace medicine. Therefore, the aim of this work is to present a new wearable prototype for monitoring multi-segment