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Sample records for active contour segmentation

  1. Hyperspectral image segmentation using active contours

    NASA Astrophysics Data System (ADS)

    Lee, Cheolha P.; Snyder, Wesley E.

    2004-08-01

    Multispectral or hyperspectral image processing has been studied as a possible approach to automatic target recognition (ATR). Hundreds of spectral bands may provide high data redundancy, compensating the low contrast in medium wavelength infrared (MWIR) and long wavelength infrared (LWIR) images. Thus, the combination of spectral (image intensity) and spatial (geometric feature) information analysis could produce a substantial improvement. Active contours provide segments with continuous boundaries, while edge detectors based on local filtering often provide discontinuous boundaries. The segmentation by active contours depends on geometric feature of the object as well as image intensity. However, the application of active contours to multispectral images has been limited to the cases of simply textured images with low number of frames. This paper presents a supervised active contour model, which is applicable to vector-valued images with non-homogeneous regions and high number of frames. In the training stage, histogram models of target classes are estimated from sample vector-pixels. In the test stage, contours are evolved based on two different metrics: the histogram models of the corresponding segments and the histogram models estimated from sample target vector-pixels. The proposed segmentation method integrates segmentation and model-based pattern matching using supervised segmentation and multi-phase active contour model, while traditional methods apply pattern matching only after the segmentation. The proposed algorithm is implemented with both synthetic and real multispectral images, and shows desirable segmentation and classification results even in images with non-homogeneous regions.

  2. Vascular active contour for vessel tree segmentation.

    PubMed

    Shang, Yanfeng; Deklerck, Rudi; Nyssen, Edgard; Markova, Aneta; de Mey, Johan; Yang, Xin; Sun, Kun

    2011-04-01

    In this paper, a novel active contour model is proposed for vessel tree segmentation. First, we introduce a region competition-based active contour model exploiting the gaussian mixture model, which mainly segments thick vessels. Second, we define a vascular vector field to evolve the active contour along its center line into the thin and weak vessels. The vector field is derived from the eigenanalysis of the Hessian matrix of the image intensity in a multiscale framework. Finally, a dual curvature strategy, which uses a vesselness measure-dependent function selecting between a minimal principal curvature and a mean curvature criterion, is added to smoothen the surface of the vessel without changing its shape. The developed model is used to extract the liver and lung vessel tree as well as the coronary artery from high-resolution volumetric computed tomography images. Comparisons are made with several classical active contour models and manual extraction. The experiments show that our model is more accurate and robust than these classical models and is, therefore, more suited for automatic vessel tree extraction. PMID:21138795

  3. Image Segmentation With Cage Active Contours.

    PubMed

    Garrido, Lluís; Guerrieri, Marité; Igual, Laura

    2015-12-01

    In this paper, we present a framework for image segmentation based on parametrized active contours. The evolving contour is parametrized according to a reduced set of control points that form a closed polygon and have a clear visual interpretation. The parametrization, called mean value coordinates, stems from the techniques used in computer graphics to animate virtual models. Our framework allows to easily formulate region-based energies to segment an image. In particular, we present three different local region-based energy terms: 1) the mean model; 2) the Gaussian model; 3) and the histogram model. We show the behavior of our method on synthetic and real images and compare the performance with state-of-the-art level set methods. PMID:26316128

  4. 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

  5. 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

  6. 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.

  7. 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

  8. Pupil segmentation using active contour with shape prior

    NASA Astrophysics Data System (ADS)

    Ukpai, Charles O.; Dlay, Satnam S.; Woo, Wai L.

    2015-03-01

    Iris segmentation is the process of defining the valid part of the eye image used for further processing (feature extraction, matching and decision making). Segmentation of the iris mostly starts with pupil boundary segmentation. Most pupil segmentation techniques are based on the assumption that the pupil is circular shape. In this paper, we propose a new pupil segmentation technique which combines shape, location and spatial information for accurate and efficient segmentation of the pupil. Initially, the pupil's position and radius is estimated using a statistical approach and circular Hough transform. In order to segment the irregular boundary of the pupil, an active contour model is initialized close to the estimated boundary using information from the first step and segmentation is achieved using energy minimization based active contour. Pre-processing and post-processing were carried out to remove noise and occlusions respectively. Experimental results on CASIA V1.0 and 4.0 shows that the proposed method is highly effective at segmenting irregular boundaries of the pupil.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. A vessel active contour model for vascular segmentation.

    PubMed

    Tian, Yun; Chen, Qingli; Wang, Wei; Peng, Yu; Wang, Qingjun; Duan, Fuqing; 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

  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. Efficient thermal image segmentation through integration of nonlinear enhancement with unsupervised active contour model

    NASA Astrophysics Data System (ADS)

    Albalooshi, Fatema A.; Krieger, Evan; Sidike, Paheding; Asari, Vijayan K.

    2015-03-01

    Thermal images are exploited in many areas of pattern recognition applications. Infrared thermal image segmentation can be used for object detection by extracting regions of abnormal temperatures. However, the lack of texture and color information, low signal-to-noise ratio, and blurring effect of thermal images make segmenting infrared heat patterns a challenging task. Furthermore, many segmentation methods that are used in visible imagery may not be suitable for segmenting thermal imagery mainly due to their dissimilar intensity distributions. Thus, a new method is proposed to improve the performance of image segmentation in thermal imagery. The proposed scheme efficiently utilizes nonlinear intensity enhancement technique and Unsupervised Active Contour Models (UACM). The nonlinear intensity enhancement improves visual quality by combining dynamic range compression and contrast enhancement, while the UACM incorporates active contour evolutional function and neural networks. The algorithm is tested on segmenting different objects in thermal images and it is observed that the nonlinear enhancement has significantly improved the segmentation performance.

  18. 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

  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. 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

  1. Automatic retinal vessel segmentation based on active contours method in Doppler spectral-domain optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Liu, Wenzhong; Liu, Tan; Song, Wei; Yi, Ji; Zhang, Hao F.

    2013-01-01

    We achieved fast and automatic retinal vessel segmentation by employing the active contours method in Doppler spectral-domain optical coherence tomography (SD-OCT). In a typical OCT B-scan image, we first extracted the phase variations between adjacent A-lines and removed bulk motion. Then we set the initial contour as the boundary of the whole image and iterated until all of the segmented vessel contours became stabilized. Using a typical office computer, the whole segmentation took no more than 50 s, making real-time retinal vessel segmentation possible. We tested the active contours method segmentation in both controlled phantom and in vivo rodent eye images.

  2. 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.

  3. 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.

  4. 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

  5. Active-contour-based image segmentation using machine learning techniques.

    PubMed

    Etyngier, Patrick; Ségonne, Florent; Keriven, Renaud

    2007-01-01

    We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a category of shapes as a finite dimensional manifold which we approximate using Diffusion maps. Our method computes a Delaunay triangulation of the reduced space, considered as Euclidean, and uses the resulting space partition to identify the closest neighbors of any given shape based on its Nyström extension. We derive a non-linear shape prior term designed to attract a shape towards the shape prior manifold at given constant embedding. Results on shapes of ventricle nuclei demonstrate the potential of our method for segmentation tasks. PMID:18051143

  6. A Novel Active Contour Model for MRI Brain Segmentation used in Radiotherapy Treatment Planning

    PubMed Central

    Mostaar, Ahmad; Houshyari, Mohammad; Badieyan, Saeedeh

    2016-01-01

    Introduction Brain image segmentation is one of the most important clinical tools used in radiology and radiotherapy. But accurate segmentation is a very difficult task because these images mostly contain noise, inhomogeneities, and sometimes aberrations. The purpose of this study was to introduce a novel, locally statistical active contour model (ACM) for magnetic resonance image segmentation in the presence of intense inhomogeneity with the ability to determine the position of contour and energy diagram. Methods A Gaussian distribution model with different means and variances was used for inhomogeneity, and a moving window was used to map the original image into another domain in which the intensity distributions of inhomogeneous objects were still Gaussian but were better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying a bias field by the original signal within the window. Then, a statistical energy function is defined for each local region. Also, to evaluate the performance of our method, experiments were conducted on MR images of the brain for segment tumors or normal tissue as visualization and energy functions. Results In the proposed method, we were able to determine the size and position of the initial contour and to count iterations to have a better segmentation. The energy function for 20 to 430 iterations was calculated. The energy function was reduced by about 5 and 7% after 70 and 430 iterations, respectively. These results showed that, with increasing iterations, the energy function decreased, but it decreased faster during the early iterations, after which it decreased slowly. Also, this method enables us to stop the segmentation based on the threshold that we define for the energy equation. Conclusion An active contour model based on the energy function is a useful tool for medical image segmentation. The proposed method combined the information about neighboring pixels that

  7. A Partition-Based Active Contour Model Incorporating Local Information for Image Segmentation

    PubMed Central

    Wu, Jiaji; 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. PMID:25147868

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

    PubMed

    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

  9. A 3D interactive multi-object segmentation tool using local robust statistics driven active contours.

    PubMed

    Gao, Yi; Kikinis, Ron; Bouix, Sylvain; Shenton, Martha; Tannenbaum, Allen

    2012-08-01

    Extracting anatomical and functional significant structures renders one of the important tasks for both the theoretical study of the medical image analysis, and the clinical and practical community. In the past, much work has been dedicated only to the algorithmic development. Nevertheless, for clinical end users, a well designed algorithm with an interactive software is necessary for an algorithm to be utilized in their daily work. Furthermore, the software would better be open sourced in order to be used and validated by not only the authors but also the entire community. Therefore, the contribution of the present work is twofolds: first, we propose a new robust statistics based conformal metric and the conformal area driven multiple active contour framework, to simultaneously extract multiple targets from MR and CT medical imagery in 3D. Second, an open source graphically interactive 3D segmentation tool based on the aforementioned contour evolution is implemented and is publicly available for end users on multiple platforms. In using this software for the segmentation task, the process is initiated by the user drawn strokes (seeds) in the target region in the image. Then, the local robust statistics are used to describe the object features, and such features are learned adaptively from the seeds under a non-parametric estimation scheme. Subsequently, several active contours evolve simultaneously with their interactions being motivated by the principles of action and reaction-this not only guarantees mutual exclusiveness among the contours, but also no longer relies upon the assumption that the multiple objects fill the entire image domain, which was tacitly or explicitly assumed in many previous works. In doing so, the contours interact and converge to equilibrium at the desired positions of the desired multiple objects. Furthermore, with the aim of not only validating the algorithm and the software, but also demonstrating how the tool is to be used, we provide

  10. 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.

  11. 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.

  12. 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.

  13. Segmenting multiple overlapping objects via a hybrid active contour model incorporating shape priors: applications to digital pathology

    NASA Astrophysics Data System (ADS)

    Ali, Sahirzeeshan; Madabhushi, Anant

    2011-03-01

    Active contours and active shape models (ASM) have been widely employed in image segmentation. A major limitation of active contours, however, is in their (a) inability to resolve boundaries of intersecting objects and to (b) handle occlusion. Multiple overlapping objects are typically segmented out as a single object. On the other hand, ASMs are limited by point correspondence issues since object landmarks need to be identified across multiple objects for initial object alignment. ASMs are also are constrained in that they can usually only segment a single object in an image. In this paper, we present a novel synergistic boundary and region-based active contour model that incorporates shape priors in a level set formulation. We demonstrate an application of these synergistic active contour models using multiple level sets to segment nuclear and glandular structures on digitized histopathology images of breast and prostate biopsy specimens. Unlike previous related approaches, our model is able to resolve object overlap and separate occluded boundaries of multiple objects simultaneously. The energy functional of the active contour is comprised of three terms. The first term comprises the prior shape term, modeled on the object of interest, thereby constraining the deformation achievable by the active contour. The second term, a boundary based term detects object boundaries from image gradients. The third term drives the shape prior and the contour towards the object boundary based on region statistics. The results of qualitative and quantitative evaluation on 100 prostate and 14 breast cancer histology images for the task of detecting and segmenting nuclei, lymphocytes, and glands reveals that the model easily outperforms two state of the art segmentation schemes (Geodesic Active Contour (GAC) and Roussons shape based model) and resolves up to 92% of overlapping/occluded lymphocytes and nuclei on prostate and breast cancer histology images.

  14. 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

  15. 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. PMID:27168599

  16. 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.

  17. 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.

  18. 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. PMID:26956730

  19. 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

  20. 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

  1. Universality in the merging dynamics of parametric active contours: a study in MRI based lung segmentation

    NASA Astrophysics Data System (ADS)

    Chattopadhyay, Amit K.; Ray, Nilanjan; Acton, Scott T.

    2005-06-01

    Measurement of lung ventilation is one of the most reliable techniques in diagnosing pulmonary diseases. The time-consuming and bias-prone traditional methods using hyperpolarized H3He and 1H magnetic resonance imageries have recently been improved by an automated technique based on 'multiple active contour evolution'. This method involves a simultaneous evolution of multiple initial conditions, called 'snakes', eventually leading to their 'merging' and is entirely independent of the shapes and sizes of snakes or other parametric details. The objective of this paper is to show, through a theoretical analysis, that the functional dynamics of merging as depicted in the active contour method has a direct analogue in statistical physics and this explains its 'universality'. We show that the multiple active contour method has an universal scaling behaviour akin to that of classical nucleation in two spatial dimensions. We prove our point by comparing the numerically evaluated exponents with an equivalent thermodynamic model.

  2. Segmenting the thoracic, abdominal and pelvic musculature on CT scans combining atlas-based model and active contour model

    NASA Astrophysics Data System (ADS)

    Zhang, Weidong; Liu, Jiamin; Yao, Jianhua; Summers, Ronald M.

    2013-03-01

    Segmentation of the musculature is very important for accurate organ segmentation, analysis of body composition, and localization of tumors in the muscle. In research fields of computer assisted surgery and computer-aided diagnosis (CAD), muscle segmentation in CT images is a necessary pre-processing step. This task is particularly challenging due to the large variability in muscle structure and the overlap in intensity between muscle and internal organs. This problem has not been solved completely, especially for all of thoracic, abdominal and pelvic regions. We propose an automated system to segment the musculature on CT scans. The method combines an atlas-based model, an active contour model and prior segmentation of fat and bones. First, body contour, fat and bones are segmented using existing methods. Second, atlas-based models are pre-defined using anatomic knowledge at multiple key positions in the body to handle the large variability in muscle shape. Third, the atlas model is refined using active contour models (ACM) that are constrained using the pre-segmented bone and fat. Before refining using ACM, the initialized atlas model of next slice is updated using previous atlas. The muscle is segmented using threshold and smoothed in 3D volume space. Thoracic, abdominal and pelvic CT scans were used to evaluate our method, and five key position slices for each case were selected and manually labeled as the reference. Compared with the reference ground truth, the overlap ratio of true positives is 91.1%+/-3.5%, and that of false positives is 5.5%+/-4.2%.

  3. 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. PMID:26516767

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

    PubMed Central

    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. PMID:26516767

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. Constraint factor graph cut–based active contour method for automated cellular image segmentation in RNAi screening

    PubMed Central

    CHEN, C.; LI, H.; ZHOU, X.; WONG, S. T. C.

    2010-01-01

    Summary Image-based, high throughput genome-wide RNA interference (RNAi) experiments are increasingly carried out to facilitate the understanding of gene functions in intricate biological processes. Automated screening of such experiments generates a large number of images with great variations in image quality, which makes manual analysis unreasonably time-consuming. Therefore, effective techniques for automatic image analysis are urgently needed, in which segmentation is one of the most important steps. This paper proposes a fully automatic method for cells segmentation in genome-wide RNAi screening images. The method consists of two steps: nuclei and cytoplasm segmentation. Nuclei are extracted and labelled to initialize cytoplasm segmentation. Since the quality of RNAi image is rather poor, a novel scale-adaptive steerable filter is designed to enhance the image in order to extract long and thin protrusions on the spiky cells. Then, constraint factor GCBAC method and morphological algorithms are combined to be an integrated method to segment tight clustered cells. Compared with the results obtained by using seeded watershed and the ground truth, that is, manual labelling results by experts in RNAi screening data, our method achieves higher accuracy. Compared with active contour methods, our method consumes much less time. The positive results indicate that the proposed method can be applied in automatic image analysis of multi-channel image screening data. PMID:18445146

  11. 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.

  12. Active Segmentation

    PubMed Central

    Mishra, Ajay; Aloimonos, Yiannis

    2009-01-01

    The human visual system observes and understands a scene/image by making a series of fixations. Every fixation point lies inside a particular region of arbitrary shape and size in the scene which can either be an object or just a part of it. We define as a basic segmentation problem the task of segmenting that region containing the fixation point. Segmenting the region containing the fixation is equivalent to finding the enclosing contour- a connected set of boundary edge fragments in the edge map of the scene - around the fixation. This enclosing contour should be a depth boundary. We present here a novel algorithm that finds this bounding contour and achieves the segmentation of one object, given the fixation. The proposed segmentation framework combines monocular cues (color/intensity/texture) with stereo and/or motion, in a cue independent manner. The semantic robots of the immediate future will be able to use this algorithm to automatically find objects in any environment. The capability of automatically segmenting objects in their visual field can bring the visual processing to the next level. Our approach is different from current approaches. While existing work attempts to segment the whole scene at once into many areas, we segment only one image region, specifically the one containing the fixation point. Experiments with real imagery collected by our active robot and from the known databases 1 demonstrate the promise of the approach. PMID:20686671

  13. Contour-Driven Atlas-Based Segmentation.

    PubMed

    Wachinger, Christian; Fritscher, Karl; Sharp, Greg; Golland, Polina

    2015-12-01

    We propose new methods for automatic segmentation of images based on an atlas of manually labeled scans and contours in the image. First, we introduce a Bayesian framework for creating initial label maps from manually annotated training images. Within this framework, we model various registration- and patch-based segmentation techniques by changing the deformation field prior. Second, we perform contour-driven regression on the created label maps to refine the segmentation. Image contours and image parcellations give rise to non-stationary kernel functions that model the relationship between image locations. Setting the kernel to the covariance function in a Gaussian process establishes a distribution over label maps supported by image structures. Maximum a posteriori estimation of the distribution over label maps conditioned on the outcome of the atlas-based segmentation yields the refined segmentation. We evaluate the segmentation in two clinical applications: the segmentation of parotid glands in head and neck CT scans and the segmentation of the left atrium in cardiac MR angiography images. PMID:26068202

  14. 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. PMID:24957548

  15. 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

  16. 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.

  17. 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

  18. Segmentation of the endocardial wall of the left atrium using local region-based active contours and statistical shape learning

    NASA Astrophysics Data System (ADS)

    Gao, Yi; Gholami, Behnood; MacLeod, Robert S.; Blauer, Joshua; Haddad, Wassim M.; Tannenbaum, Allen R.

    2010-03-01

    Atrial fibrillation, a cardiac arrhythmia characterized by unsynchronized electrical activity in the atrial chambers of the heart, is a rapidly growing problem in modern societies. One treatment, referred to as catheter ablation, targets specific parts of the left atrium for radio frequency ablation using an intracardiac catheter. Magnetic resonance imaging has been used for both pre- and and post-ablation assessment of the atrial wall. Magnetic resonance imaging can aid in selecting the right candidate for the ablation procedure and assessing post-ablation scar formations. Image processing techniques can be used for automatic segmentation of the atrial wall, which facilitates an accurate statistical assessment of the region. As a first step towards the general solution to the computer-assisted segmentation of the left atrial wall, in this paper we use shape learning and shape-based image segmentation to identify the endocardial wall of the left atrium in the delayed-enhancement magnetic resonance images.

  19. 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

  20. Computer-assisted segmentation of videocapsule images using alpha-divergence-based active contour in the framework of intestinal pathologies detection.

    PubMed

    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

  1. 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

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

    PubMed

    Zarpalas, Dimitrios; 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

  3. Localizing Region-Based Active Contours

    PubMed Central

    Lankton, Shawn; Tannenbaum, Allen

    2009-01-01

    In this paper, we propose a natural framework that allows any region-based segmentation energy to be re-formulated in a local way. We consider local rather than global image statistics and evolve a contour based on local information. Localized contours are capable of segmenting objects with heterogeneous feature profiles that would be difficult to capture correctly using a standard global method. The presented technique is versatile enough to be used with any global region-based active contour energy and instill in it the benefits of localization. We describe this framework and demonstrate the localization of three well-known energies in order to illustrate how our framework can be applied to any energy. We then compare each localized energy to its global counterpart to show the improvements that can be achieved. Next, an in-depth study of the behaviors of these energies in response to the degree of localization is given. Finally, we show results on challenging images to illustrate the robust and accurate segmentations that are possible with this new class of active contour models. PMID:18854247

  4. A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

    NASA Astrophysics Data System (ADS)

    Wu, T. Y.; Lin, S. F.

    2013-10-01

    Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

  5. 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

  6. 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.

  7. 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

  8. Multi-object geodesic active contours (MOGAC).

    PubMed

    Lucas, Blake C; Kazhdan, Michael; Taylor, Russell H

    2012-01-01

    An emerging topic is to build image segmentation systems that can segment hundreds to thousands of objects (i.e. cell segmentation\\tracking, full brain parcellation, full body segmentation, etc.). Multi-object Level Set Methods (MLSM) perform this task with the benefit of sub-pixel precision. However, current implementations of MLSM are not as computationally or memory efficient as their region growing and graph cut counterparts which lack sub-pixel precision. To address this performance gap, we present a novel parallel implementation of MLSM that leverages the sparse properties of the algorithm to minimize its memory footprint for multiple objects. The new method, Multi-Object Geodesic Active Contours (MOGAC), can represent N objects with just two functions: a label mask image and unsigned distance field. The time complexity of the algorithm is shown to be O((M (power)d)/P) for M (power)d pixels and P processing units in dimension d = {2,3}, independent of the number of objects. Results are presented for 2D and 3D image segmentation problems. PMID:23286074

  9. 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

  10. Multiresolution active contour model applied on lung and colon images

    NASA Astrophysics Data System (ADS)

    Dehmeshki, Jamshid; Siddique, Musib; Wong, Wing; Chis Ster, Irina

    2004-05-01

    This paper deploys a wavelet based scale-space approach to extract the boundary of the object of interest in medical CT images. The classical approach of the active contour models consists of starting with an initial contour, to deform it under the action of some forces attracting the contour towards the edges by means of a set of forces. The mathematical model involves in the minimisation of an objective function called energy functional, which depends on the geometry of the contour as well as of the image characteristics. Various strategies could be used for the formulation of the energy functional and its optimisation. In this study, a wavelet based scale-space approach has been adopted. The coarsest scale is able to enlarge the capture region surrounding an object and avoids the trapping of contour into weak edges. The finer scales are used to refine the contour as close as possible to the boundary of the object. An adaptive scale coefficient for the balloon energy has been introduced. Four levels of resolution have been applied in order to get reproducibility of the contour despite poor different initialisations. The scheme has been applied to segment the regions of interest in CT lung and colon images. The result has been shown to be accurate and reproducible for the cases containing fat, holes and other small high intensity objects inside lung nodules as well as colon polyps.

  11. Groups of adjacent contour segments for object detection.

    PubMed

    Ferrari, V; Fevrier, L; Jurie, F; Schmid, C

    2008-01-01

    We present a family of scale-invariant local shape features formed by chains of k connected, roughly straight contour segments (kAS), and their use for object class detection. kAS are able to cleanly encode pure fragments of an object boundary, without including nearby clutter. Moreover, they offer an attractive compromise between information content and repeatability, and encompass a wide variety of local shape structures. We also define a translation and scale invariant descriptor encoding the geometric configuration of the segments within a kAS, making kAS easy to reuse in other frameworks, for example as a replacement or addition to interest points. Software for detecting and describing kAS is released on lear.inrialpes.fr/software. We demonstrate the high performance of kAS within a simple but powerful sliding-window object detection scheme. Through extensive evaluations, involving eight diverse object classes and more than 1400 images, we 1) study the evolution of performance as the degree of feature complexity k varies and determine the best degree; 2) show that kAS substantially outperform interest points for detecting shape-based classes; 3) compare our object detector to the recent, state-of-the-art system by Dalal and Triggs [4]. PMID:18000323

  12. 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.

  13. Prostate segmentation algorithm using dyadic wavelet transform and discrete dynamic contour

    NASA Astrophysics Data System (ADS)

    Chiu, Bernard; Freeman, George H.; Salama, M. M. A.; Fenster, Aaron

    2004-11-01

    Knowing the location and the volume of the prostate is important for ultrasound-guided prostate brachytherapy, a commonly used prostate cancer treatment method. The prostate boundary must be segmented before a dose plan can be obtained. However, manual segmentation is arduous and time consuming. This paper introduces a semi-automatic segmentation algorithm based on the dyadic wavelet transform (DWT) and the discrete dynamic contour (DDC). A spline interpolation method is used to determine the initial contour based on four user-defined initial points. The DDC model then refines the initial contour based on the approximate coefficients and the wavelet coefficients generated using the DWT. The DDC model is executed under two settings. The coefficients used in these two settings are derived using smoothing functions with different sizes. A selection rule is used to choose the best contour based on the contours produced in these two settings. The accuracy of the final contour produced by the proposed algorithm is evaluated by comparing it with the manual contour outlined by an expert observer. A total of 114 2D TRUS images taken for six different patients scheduled for brachytherapy were segmented using the proposed algorithm. The average difference between the contour segmented using the proposed algorithm and the manually outlined contour is less than 3 pixels.

  14. Prostate segmentation algorithm using dyadic wavelet transform and discrete dynamic contour.

    PubMed

    Chiu, Bernard; Freeman, George H; Salama, M M A; Fenster, Aaron

    2004-11-01

    Knowing the location and the volume of the prostate is important for ultrasound-guided prostate brachytherapy, a commonly used prostate cancer treatment method. The prostate boundary must be segmented before a dose plan can be obtained. However, manual segmentation is arduous and time consuming. This paper introduces a semi-automatic segmentation algorithm based on the dyadic wavelet transform (DWT) and the discrete dynamic contour (DDC). A spline interpolation method is used to determine the initial contour based on four user-defined initial points. The DDC model then refines the initial contour based on the approximate coefficients and the wavelet coefficients generated using the DWT. The DDC model is executed under two settings. The coefficients used in these two settings are derived using smoothing functions with different sizes. A selection rule is used to choose the best contour based on the contours produced in these two settings. The accuracy of the final contour produced by the proposed algorithm is evaluated by comparing it with the manual contour outlined by an expert observer. A total of 114 2D TRUS images taken for six different patients scheduled for brachytherapy were segmented using the proposed algorithm. The average difference between the contour segmented using the proposed algorithm and the manually outlined contour is less than 3 pixels. PMID:15584529

  15. Dependence of Shape-Based Descriptors and Mass Segmentation Areas on Initial Contour Placement Using the Chan-Vese Method on Digital Mammograms

    PubMed Central

    Acho, S. N.; Rae, W. I. D.

    2015-01-01

    Variation in signal intensity within mass lesions and missing boundary information are intensity inhomogeneities inherent in digital mammograms. These inhomogeneities render the performance of a deformable contour susceptible to the location of its initial position and may lead to poor segmentation results for these images. We investigate the dependence of shape-based descriptors and mass segmentation areas on initial contour placement with the Chan-Vese segmentation method and compare these results to the active contours with selective local or global segmentation model. For each mass lesion, final contours were obtained by propagation of a proposed initial level set contour and by propagation of a manually drawn contour enclosing the region of interest. Differences in shape-based descriptors were quantified using absolute percentage differences, Euclidean distances, and Bland-Altman analysis. Segmented areas were evaluated with the area overlap measure. Differences were dependent upon the characteristics of the mass margins. Boundary moments presented large percentage differences. Pearson correlation analysis showed statistically significant correlations between shape-based descriptors from both initial locations. In conclusion, boundary moments of digital mass lesions are sensitive to the placement of initial level set contours while shape-based descriptors such as Fourier descriptors, shape convexity, and shape rectangularity exhibit a certain degree of robustness to changes in the location of the initial level set contours for both segmentation algorithms. PMID:26379762

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. Contour detection and completion for inpainting and segmentation based on topological gradient and fast marching algorithms.

    PubMed

    Auroux, Didier; Cohen, Laurent D; Masmoudi, Mohamed

    2011-01-01

    We combine in this paper the topological gradient, which is a powerful method for edge detection in image processing, and a variant of the minimal path method in order to find connected contours. The topological gradient provides a more global analysis of the image than the standard gradient and identifies the main edges of an image. Several image processing problems (e.g., inpainting and segmentation) require continuous contours. For this purpose, we consider the fast marching algorithm in order to find minimal paths in the topological gradient image. This coupled algorithm quickly provides accurate and connected contours. We present then two numerical applications, to image inpainting and segmentation, of this hybrid algorithm. PMID:22194734

  1. Automatic 4D Reconstruction of Patient-Specific Cardiac Mesh with 1-to-1 Vertex Correspondence from Segmented Contours Lines

    PubMed Central

    Lim, Chi Wan; Su, Yi; Yeo, Si Yong; Ng, Gillian Maria; Nguyen, Vinh Tan; Zhong, Liang; Tan, Ru San; Poh, Kian Keong; Chai, Ping

    2014-01-01

    We propose an automatic algorithm for the reconstruction of patient-specific cardiac mesh models with 1-to-1 vertex correspondence. In this framework, a series of 3D meshes depicting the endocardial surface of the heart at each time step is constructed, based on a set of border delineated magnetic resonance imaging (MRI) data of the whole cardiac cycle. The key contribution in this work involves a novel reconstruction technique to generate a 4D (i.e., spatial–temporal) model of the heart with 1-to-1 vertex mapping throughout the time frames. The reconstructed 3D model from the first time step is used as a base template model and then deformed to fit the segmented contours from the subsequent time steps. A method to determine a tree-based connectivity relationship is proposed to ensure robust mapping during mesh deformation. The novel feature is the ability to handle intra- and inter-frame 2D topology changes of the contours, which manifests as a series of merging and splitting of contours when the images are viewed either in a spatial or temporal sequence. Our algorithm has been tested on five acquisitions of cardiac MRI and can successfully reconstruct the full 4D heart model in around 30 minutes per subject. The generated 4D heart model conforms very well with the input segmented contours and the mesh element shape is of reasonably good quality. The work is important in the support of downstream computational simulation activities. PMID:24743555

  2. Contour-Driven Regression for Label Inference in Atlas-Based Segmentation

    PubMed Central

    Wachinger, Christian; Sharp, Gregory C.; Golland, Polina

    2014-01-01

    We present a novel method for inferring tissue labels in atlas-based image segmentation using Gaussian process regression. Atlas-based segmentation results in probabilistic label maps that serve as input to our method. We introduce a contour-driven prior distribution over label maps to incorporate image features of the input scan into the label inference problem. The mean function of the Gaussian process posterior distribution yields the MAP estimate of the label map and is used in the subsequent voting. We demonstrate improved segmentation accuracy when our approach is combined with two different patch-based segmentation techniques. We focus on the segmentation of parotid glands in CT scans of patients with head and neck cancer, which is important for radiation therapy planning. PMID:24505763

  3. 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

  4. Prostate contours delineation using interactive directional active contours model and parametric shape prior model.

    PubMed

    Derraz, Foued; Forzy, Gérard; Delebarre, Arnaud; Taleb-Ahmed, Abdelmalik; Oussalah, Mourad; Peyrodie, Laurent; Verclytte, Sebastien

    2015-11-01

    Prostate contours delineation on Magnetic Resonance (MR) images is a challenging and important task in medical imaging with applications of guiding biopsy, surgery and therapy. While a fully automated method is highly desired for this application, it can be a very difficult task due to the structure and surrounding tissues of the prostate gland. Traditional active contours-based delineation algorithms are typically quite successful for piecewise constant images. Nevertheless, when MR images have diffuse edges or multiple similar objects (e.g. bladder close to prostate) within close proximity, such approaches have proven to be unsuccessful. In order to mitigate these problems, we proposed a new framework for bi-stage contours delineation algorithm based on directional active contours (DAC) incorporating prior knowledge of the prostate shape. We first explicitly addressed the prostate contour delineation problem based on fast globally DAC that incorporates both statistical and parametric shape prior model. In doing so, we were able to exploit the global aspects of contour delineation problem by incorporating a user feedback in contours delineation process where it is shown that only a small amount of user input can sometimes resolve ambiguous scenarios raised by DAC. In addition, once the prostate contours have been delineated, a cost functional is designed to incorporate both user feedback interaction and the parametric shape prior model. Using data from publicly available prostate MR datasets, which includes several challenging clinical datasets, we highlighted the effectiveness and the capability of the proposed algorithm. Besides, the algorithm has been compared with several state-of-the-art methods. PMID:26009857

  5. 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

  6. 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.

  7. Exploiting information geometry to improve the convergence of nonparametric active contours.

    PubMed

    Pereyra, Marcelo; Batatia, Hadj; McLaughlin, Steve

    2015-03-01

    This paper presents a fast converging Riemannian steepest descent method for nonparametric statistical active contour models, with application to image segmentation. Unlike other fast algorithms, the proposed method is general and can be applied to any statistical active contour model from the exponential family, which comprises most of the models considered in the literature. This is achieved by first identifying the intrinsic statistical manifold associated with this class of active contours, and then constructing a steepest descent on that manifold. A key contribution of this paper is to derive a general and tractable closed-form analytic expression for the manifold's Riemannian metric tensor, which allows computing discrete gradient flows efficiently. The proposed methodology is demonstrated empirically and compared with other state of the art approaches on several standard test images, a phantom positron-emission-tomography scan and a B-mode echography of in-vivo human dermis. PMID:25532177

  8. 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

  9. 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

  10. Research of Active Contour Model in Aerial Images

    NASA Astrophysics Data System (ADS)

    Kun, Wang; Li, Guo

    With the development of computer and aviation technology, the aerial image is facing an important issue is how to automate, including aerial images of the automatic extraction of the target. In this paper, the issue of aerial images to study the active contour model is introduced, that is, Snake model, to achieve the target aerial image of the semi-automatic contour extraction method. Snake model used the unique characteristic of the energy minimization, carried out on the image contour extraction, to obtain a clear, consistent and accurate image contour. The model is defined through the energy minimization of the function, given in the initial position of artificial circumstances, through the iterative calculation of Snake model will eventually form the minimum energy function has been described in the outline of the target partition. The results indicate that Snake model for aerial images of the edge contour extraction, verification, concluded that the Snake-based edge detection methods could be more objectively and accurately extract the edge of the outline of aerial images.

  11. 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). PMID:17355059

  12. 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

  13. 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

  14. 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

  15. 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

  16. Brain extraction from cerebral MRI volume using a hybrid level set based active contour neighborhood model

    PubMed Central

    2013-01-01

    Background The extraction of brain tissue from cerebral MRI volume is an important pre-procedure for neuroimage analyses. The authors have developed an accurate and robust brain extraction method using a hybrid level set based active contour neighborhood model. Methods The method uses a nonlinear speed function in the hybrid level set model to eliminate boundary leakage. When using the new hybrid level set model an active contour neighborhood model is applied iteratively in the neighborhood of brain boundary. A slice by slice contour initial method is proposed to obtain the neighborhood of the brain boundary. The method was applied to the internet brain MRI data provided by the Internet Brain Segmentation Repository (IBSR). Results In testing, a mean Dice similarity coefficient of 0.95±0.02 and a mean Hausdorff distance of 12.4±4.5 were obtained when performing our method across the IBSR data set (18 × 1.5 mm scans). The results obtained using our method were very similar to those produced using manual segmentation and achieved the smallest mean Hausdorff distance on the IBSR data. Conclusions An automatic method of brain extraction from cerebral MRI volume was achieved and produced competitively accurate results. PMID:23587217

  17. 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.

  18. Computer aided weld defect delineation using statistical parametric active contours in radiographic inspection.

    PubMed

    Goumeidane, Aicha Baya; Nacereddine, Nafaa; Khamadja, Mohammed

    2015-01-01

    A perfect knowledge of a defect shape is determinant for the analysis step in automatic radiographic inspection. Image segmentation is carried out on radiographic images and extract defects indications. This paper deals with weld defect delineation in radiographic images. The proposed method is based on a new statistics-based explicit active contour. An association of local and global modeling of the image pixels intensities is used to push the model to the desired boundaries. Furthermore, other strategies are proposed to accelerate its evolution and make the convergence speed depending only on the defect size as selecting a band around the active contour curve. The experimental results are very promising, since experiments on synthetic and radiographic images show the ability of the proposed model to extract a piece-wise homogenous object from very inhomogeneous background, even in a bad quality image. PMID:26410464

  19. Left Ventricle Segmentation Using Model Fitting and Active Surfaces

    PubMed Central

    Tay, Peter C.; Li, Bing; Garson, Chris D.; Acton, Scott T.; Hossack, John A.

    2010-01-01

    A method to perform 4D (3D over time) segmentation of the left ventricle of a mouse heart using a set of B mode cine slices acquired in vivo from a series of short axis scans is described. We incorporate previously suggested methods such as temporal propagation, the gradient vector flow active surface, superquadric models, etc. into our proposed 4D segmentation of the left ventricle. The contributions of this paper are incorporation of a novel despeckling method and the use of locally fitted superellipsoid models to provide a better initialization for the active surface segmentation algorithm. Average distances of the improved surface segmentation to a manually segmented surface throughout the entire cardiac cycle and cross-sectional contours are provided to demonstrate the improvements produced by the proposed 4D segmentation. PMID:20300558

  20. Automatic segmentation of mitochondria in EM data using pairwise affinity factorization and graph-based contour searching.

    PubMed

    Ghita, Ovidiu; Dietlmeier, Julia; Whelan, Paul F

    2014-10-01

    In this paper, we investigate the segmentation of closed contours in subcellular data using a framework that primarily combines the pairwise affinity grouping principles with a graph partitioning contour searching approach. One salient problem that precluded the application of these methods to large scale segmentation problems is the onerous computational complexity required to generate comprehensive representations that include all pairwise relationships between all pixels in the input data. To compensate for this problem, a practical solution is to reduce the complexity of the input data by applying an over-segmentation technique prior to the application of the computationally demanding strands of the segmentation process. This approach opens the opportunity to build specific shape and intensity models that can be successfully employed to extract the salient structures in the input image which are further processed to identify the cycles in an undirected graph. The proposed framework has been applied to the segmentation of mitochondria membranes in electron microscopy data which are characterized by low contrast and low signal-to-noise ratio. The algorithm has been quantitatively evaluated using two datasets where the segmentation results have been compared with the corresponding manual annotations. The performance of the proposed algorithm has been measured using standard metrics, such as precision and recall, and the experimental results indicate a high level of segmentation accuracy. PMID:25134083

  1. 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

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

    PubMed

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

    2007-08-01

    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

  3. 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

  4. 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

  5. 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%.

  6. Identification of the breast boundary in mammograms using active contour models.

    PubMed

    Ferrari, R J; Rangayyan, R M; Desautels, J E L; Borges, R A; Frère, A F

    2004-03-01

    A method for the identification of the breast boundary in mammograms is presented. The method can be used in the preprocessing stage of a system for computer-aided diagnosis (CAD) of breast cancer and also in the reduction of image file size in picture archiving and communication system applications. The method started with modification of the contrast of the original image. A binarisation procedure was then applied to the image, and the chain-code algorithm was used to find an approximate breast contour. Finally, the identification of the true breast boundary was performed by using the approximate contour as the input to an active contour model algorithm specially tailored for this purpose. After demarcation of the breast boundary, all artifacts outside the breast region were eliminated. The method was applied to 84 medio-lateral oblique mammograms from the Mini-MIAS database. Evaluation of the detected breast boundary was performed based upon the percentage of false-positive and false-negative pixels determined by a quantitative comparison between the contours identified by a radiologist and those identified by the proposed method. The average false positive and false negative rates were 0.41% and 0.58%, respectively. The two radiologists who evaluated the results considered the segmentation results to be acceptable for CAD purposes. PMID:15125150

  7. 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.

  8. Shoreline Mapping with Integrated HSI-DEM using Active Contour Method

    NASA Astrophysics Data System (ADS)

    Sukcharoenpong, Anuchit

    Shoreline mapping has been a critical task for federal/state agencies and coastal communities. It supports important applications such as nautical charting, coastal zone management, and legal boundary determination. Current attempts to incorporate data from hyperspectral imagery to increase the efficiency and efficacy of shoreline mapping have been limited due to the complexity in processing its data as well as its inferior spatial resolution when compared to multispectral imagery or to sensors such as LiDAR. As advancements in remote-sensing technologies increase sensor capabilities, the ability to exploit the spectral formation carried in hyperspectral images becomes more imperative. This work employs a new approach to extracting shorelines from AVIRIS hyperspectral images by combination with a LiDAR-based DEM using a multiphase active contour segmentation technique. Several techniques, such as study of object spectra and knowledge-based segmentation for initial contour generation, have been employed in order to achieve a sub-pixel level of accuracy and maintain low computational expenses. Introducing a DEM into hyperspectral image segmentation proves to be a useful tool to eliminate misclassifications and improve shoreline positional accuracy. Experimental results show that mapping shorelines from hyperspectral imagery and a DEM can be a promising approach as many further applications can be developed to exploit the rich information found in hyperspectral imagery.

  9. 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.

  10. 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

  11. 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

  12. Application of active contours for photochromic tracer flow extraction.

    PubMed

    Androutsos, D; Trahanias, P E; Venetsanopoulos, A N

    1997-06-01

    This paper addresses the implementation of image processing and computer vision techniques to automate tracer flow extraction in images obtained by the photochromic dye technique. This task is important in modeled arterial blood flow studies. Currently, it is performed via manual application of B-spline curve fitting. However, this is a tedious and error-prone procedure and its results are nonreproducible. In the proposed approach, active contours, snakes, are employed in a new curve-fitting method for tracer flow extraction in photochromic images. An algorithm implementing snakes is introduced to automate extraction. Utilizing correlation matching, the algorithm quickly locates and localizes all flow traces in the images. The feasibility of the method for tracer flow extraction is demonstrated. Moreover, results regarding the automation algorithm are presented showing its accuracy and effectiveness. The proposed approach for tracer flow extraction has potential for real-system application. PMID:9184890

  13. B-spline active rays segmentation of microcalcifications in mammography

    SciTech Connect

    Arikidis, Nikolaos S.; Skiadopoulos, Spyros; Karahaliou, Anna; Likaki, Eleni; Panayiotakis, George; Costaridou, Lena

    2008-11-15

    Accurate segmentation of microcalcifications in mammography is crucial for the quantification of morphologic properties by features incorporated in computer-aided diagnosis schemes. A novel segmentation method is proposed implementing active rays (polar-transformed active contours) on B-spline wavelet representation to identify microcalcification contour point estimates in a coarse-to-fine strategy at two levels of analysis. An iterative region growing method is used to delineate the final microcalcification contour curve, with pixel aggregation constrained by the microcalcification contour point estimates. A radial gradient-based method was also implemented for comparative purposes. The methods were tested on a dataset consisting of 149 mainly pleomorphic microcalcification clusters originating from 130 mammograms of the DDSM database. Segmentation accuracy of both methods was evaluated by three radiologists, based on a five-point rating scale. The radiologists' average accuracy ratings were 3.96{+-}0.77, 3.97{+-}0.80, and 3.83{+-}0.89 for the proposed method, and 2.91{+-}0.86, 2.10{+-}0.94, and 2.56{+-}0.76 for the radial gradient-based method, respectively, while the differences in accuracy ratings between the two segmentation methods were statistically significant (Wilcoxon signed-ranks test, p<0.05). The effect of the two segmentation methods in the classification of benign from malignant microcalcification clusters was also investigated. A least square minimum distance classifier was employed based on cluster features reflecting three morphological properties of individual microcalcifications (area, length, and relative contrast). Classification performance was evaluated by means of the area under ROC curve (A{sub z}). The area and length morphologic features demonstrated a statistically significant (Mann-Whitney U-test, p<0.05) higher patient-based classification performance when extracted from microcalcifications segmented by the proposed method (0

  14. 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. PMID:26766207

  15. 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.

  16. Cell spreading analysis with directed edge profile-guided level set active contours.

    PubMed

    Ersoy, I; Bunyak, F; Palaniappan, K; Sun, M; Forgacs, G

    2008-01-01

    Cell adhesion and spreading within the extracellular matrix (ECM) plays an important role in cell motility, cell growth and tissue organization. Measuring cell spreading dynamics enables the investigation of cell mechanosensitivity to external mechanical stimuli, such as substrate rigidity. A common approach to measure cell spreading dynamics is to take time lapse images and quantify cell size and perimeter as a function of time. In our experiments, differences in cell characteristics between different treatments are subtle and require accurate measurements of cell parameters across a large population of cells to ensure an adequate sample size for statistical hypothesis testing. This paper presents a new approach to estimate accurate cell boundaries with complex shapes by applying a modified geodesic active contour level set method that directly utilizes the halo effect typically seen in phase contrast microscopy. Contour evolution is guided by edge profiles in a perpendicular direction to ensure convergence to the correct cell boundary. The proposed approach is tested on bovine aortic endothelial cell images under different treatments, and demonstrates accurate segmentation for a wide range of cell sizes and shapes compared to manual ground truth. PMID:18979769

  17. 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

  18. 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…

  19. 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

  20. 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

  1. Tubular Enhanced Geodesic Active Contours for Continuum Robot Detection using 3D Ultrasound

    PubMed Central

    Ren, Hongliang; Dupont, Pierre E.

    2013-01-01

    Three dimensional ultrasound is a promising imaging modality for minimally invasive robotic surgery. As the robots are typically metallic, they interact strongly with the sound waves in ways that are not modeled by the ultrasound system’s signal processing algorithms. Consequently, they produce substantial imaging artifacts that can make image guidance difficult, even for experienced surgeons. This paper introduces a new approach for detecting curved continuum robots in 3D ultrasound images. The proposed approach combines geodesic active contours with a speed function that is based on enhancing the “tubularity” of the continuum robot. In particular, it takes advantage of the known robot diameter along its length. It also takes advantage of the fact that the robot surface facing the ultrasound probe provides the most accurate image. This method, termed Tubular Enhanced Geodesic Active Contours (TEGAC), is demonstrated through ex vivo intracardiac experiments to offer superior performance compared to conventional active contours. PMID:24231880

  2. 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.

  3. Segmentation of the Left Ventricle in Myocardial Perfusion SPECT Using Active Shape Model

    NASA Astrophysics Data System (ADS)

    Tan, Wooi-Haw; Besar, Rosli

    In the quantification of myocardial perfusion SPECT (MPS), numerous processes are involved. Automation is desired as it will considerably reduce the laboriousness of the underlying tasks. In this paper, we propose a segmentation scheme for the delineation of left ventricle (LV) using the Active Shape Models. Our scheme will reduce the labour-intensiveness in MPS quantification, while still allowing interactive guidance from the medical experts. The proposed scheme has been applied on clinical MPS tomograms in which it has successfully delineated the LV in 94% of the test data. In addition, it has also shown to be more suitable for LV segmentation than the rivaling Active Contour Model.

  4. 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.

  5. A contour-based approach to multisensor image registration.

    PubMed

    Li, H; Manjunath, B S; Mitra, S K

    1995-01-01

    Image registration is concerned with the establishment of correspondence between images of the same scene. One challenging problem in this area is the registration of multispectral/multisensor images. In general, such images have different gray level characteristics, and simple techniques such as those based on area correlations cannot be applied directly. On the other hand, contours representing region boundaries are preserved in most cases. The authors present two contour-based methods which use region boundaries and other strong edges as matching primitives. The first contour matching algorithm is based on the chain-code correlation and other shape similarity criteria such as invariant moments. Closed contours and the salient segments along the open contours are matched separately. This method works well for image pairs in which the contour information is well preserved, such as the optical images from Landsat and Spot satellites. For the registration of the optical images with synthetic aperture radar (SAR) images, the authors propose an elastic contour matching scheme based on the active contour model. Using the contours from the optical image as the initial condition, accurate contour locations in the SAR image are obtained by applying the active contour model. Both contour matching methods are automatic and computationally quite efficient. Experimental results with various kinds of image data have verified the robustness of the algorithms, which have outperformed manual registration in terms of root mean square error at the control points. PMID:18289982

  6. Finding parametric representations of the cortical sulci using an active contour model.

    PubMed

    Vaillant, M; Davatzikos, C

    1997-09-01

    The cortical sulci are brain structures resembling thin convoluted ribbons embedded in three dimensions. The importance of the sulci lies primarily in their relation to the cytoarchitectonic and functional organization of the underlying cortex and in their utilization as features in non-rigid registration methods. This paper presents a methodology for extracting parametric representations of the cerebral sulcus from magnetic resonance images. The proposed methodology is based on deformable models utilizing characteristics of the cortical shape. Specifically, a parametric representation of a sulcus is determined by the motion of an active contour along the medial surface of the corresponding cortical fold. The active contour is initialized along the outer boundary of the brain and deforms toward the deep root of a sulcus under the influence of an external force field, restricting it to lie along the medial surface of the particular cortical fold. A parametric representation of the medial surface of the sulcus is obtained as the active contour traverses the sulcus. Based on the first fundamental form of this representation, the location and degree of an interruption of a sulcus can be readily quantified; based on its second fundamental form, shape properties of the sulcus can be determined. This methodology is tested on magnetic resonance images and it is applied to three medical imaging problems: quantitative morphological analysis of the central sulcus; mapping of functional activation along the primary motor cortex and non-rigid registration of brain images. PMID:9873912

  7. 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

  8. 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.

  9. 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

  10. 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

  11. Automatic bootstrapping and tracking of object contours.

    PubMed

    Chiverton, John; Xie, Xianghua; Mirmehdi, Majid

    2012-03-01

    A new fully automatic object tracking and segmentation framework is proposed. The framework consists of a motion-based bootstrapping algorithm concurrent to a shape-based active contour. The shape-based active contour uses finite shape memory that is automatically and continuously built from both the bootstrap process and the active-contour object tracker. A scheme is proposed to ensure that the finite shape memory is continuously updated but forgets unnecessary information. Two new ways of automatically extracting shape information from image data given a region of interest are also proposed. Results demonstrate that the bootstrapping stage provides important motion and shape information to the object tracker. This information is found to be essential for good (fully automatic) initialization of the active contour. Further results also demonstrate convergence properties of the content of the finite shape memory and similar object tracking performance in comparison with an object tracker with unlimited shape memory. Tests with an active contour using a fixed-shape prior also demonstrate superior performance for the proposed bootstrapped finite-shape-memory framework and similar performance when compared with a recently proposed active contour that uses an alternative online learning model. PMID:21908256

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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)

  17. 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.

  18. Active-shape-model-based segmentation of abdominal aortic aneurysms in CTA images

    NASA Astrophysics Data System (ADS)

    de Bruijne, Marleen; van Ginneken, Bram; Niessen, Wiro J.; Maintz, J. B. Antoine; Viergever, Max A.

    2002-05-01

    An automated method for the segmentation of thrombus in abdominal aortic aneurysms from CTA data is presented. The method is based on Active Shape Model (ASM) fitting in sequential slices, using the contour obtained in one slice as the initialisation in the adjacent slice. The optimal fit is defined by maximum correlation of grey value profiles around the contour in successive slices, in contrast to the original ASM scheme as proposed by Cootes and Taylor, where the correlation with profiles from training data is maximised. An extension to the proposed approach prevents the inclusion of low-intensity tissue and allows the model to refine to nearby edges. The applied shape models contain either one or two image slices, the latter explicitly restricting the shape change from slice to slice. To evaluate the proposed methods a leave-one-out experiment was performed, using six datasets containing 274 slices to segment. Both adapted ASM schemes yield significantly better results than the original scheme (p<0.0001). The extended slice correlation fit of a one-slice model showed best overall performance. Using one manually delineated image slice as a reference, on average a number of 29 slices could be automatically segmented with an accuracy within the bounds of manual inter-observer variability.

  19. 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

  20. Automated detection of lung tumors in PET/CT images using active contour filter

    NASA Astrophysics Data System (ADS)

    Teramoto, Atsushi; Adachi, Hayato; Tsujimoto, Masakazu; Fujita, Hiroshi; Takahashi, Katsuaki; Yamamuro, Osamu; Tamaki, Tsuneo; Nishio, Masami; Kobayashi, Toshiki

    2015-03-01

    In a previous study, we developed a hybrid tumor detection method that used both computed tomography (CT) and positron emission tomography (PET) images. However, similar to existing computer-aided detection (CAD) schemes, it was difficult to detect low-contrast lesions that touch to the normal organs such as the chest wall or blood vessels in the lung. In the current study, we proposed a novel lung tumor detection method that uses active contour filters to detect the nodules deemed "difficult" in previous CAD schemes. The proposed scheme detects lung tumors using both CT and PET images. As for the detection in CT images, the massive region was first enhanced using an active contour filter (ACF), which is a type of contrast enhancement filter that has a deformable kernel shape. The kernel shape involves closed curves that are connected by several nodes that move iteratively in order to enclose the massive region. The final output of ACF is the difference between the maximum pixel value on the deformable kernel, and pixel value on the center of the filter kernel. Subsequently, the PET images were binarized to detect the regions of increased uptake. The results were integrated, followed by the false positive reduction using 21 characteristic features and three support vector machines. In the experiment, we evaluated the proposed method using 100 PET/CT images. More than half of nodules missed using previous methods were accurately detected. The results indicate that our method may be useful for the detection of lung tumors using PET/CT images.

  1. 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. PMID:26786063

  2. 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

  3. Sunspots and Coronal Bright Points Tracking using a Hybrid Algorithm of PSO and Active Contour Model

    NASA Astrophysics Data System (ADS)

    Dorotovic, I.; Shahamatnia, E.; Lorenc, M.; Rybansky, M.; Ribeiro, R. A.; Fonseca, J. M.

    2014-02-01

    In the last decades there has been a steady increase of high-resolution data, from ground-based and space-borne solar instruments, and also of solar data volume. These huge image archives require efficient automatic image processing software tools capable of detecting and tracking various features in the solar atmosphere. Results of application of such tools are essential for studies of solar activity evolution, climate change understanding and space weather prediction. The follow up of interplanetary and near-Earth phenomena requires, among others, automatic tracking algorithms that can determine where a feature is located, on successive images taken along the period of observation. Full-disc solar images, obtained both with the ground-based solar telescopes and the instruments onboard the satellites, provide essential observational material for solar physicists and space weather researchers for better understanding the Sun, studying the evolution of various features in the solar atmosphere, and also investigating solar differential rotation by tracking such features along time. Here we demonstrate and discuss the suitability of applying a hybrid Particle Swarm Optimization (PSO) algorithm and Active Contour model for tracking and determining the differential rotation of sunspots and coronal bright points (CBPs) on a set of selected solar images. The results obtained confirm that the proposed approach constitutes a promising tool for investigating the evolution of solar activity and also for automating tracking features on massive solar image archives.

  4. 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.

  5. Early processing in human LOC is highly responsive to illusory contours but not to salient regions

    PubMed Central

    Shpaner, Marina; Murray, Micah M.; Foxe, John J.

    2011-01-01

    Human electrophysiological studies support a model whereby sensitivity to so-called illusory contour stimuli is first seen within the lateral occipital complex. A challenge to this model posits that the lateral occipital complex is a general site for crude region-based segmentation, based on findings of equivalent hemodynamic activations in the lateral occipital complex to illusory contour and so-called salient region stimuli, a stimulus class that lacks the classic bounding contours of illusory contours. Using high-density electrical mapping of visual evoked potentials, we show that early lateral occipital cortex activity is substantially stronger to illusory contour than to salient region stimuli, while later lateral occipital complex activity is stronger to salient region than to illusory contour stimuli. Our results suggest that equivalent hemodynamic activity to illusory contour and salient region stimuli likely reflects temporally integrated responses, a result of the poor temporal resolution of hemodynamic imaging. The temporal precision of visual evoked potentials is critical for establishing viable models of completion processes and visual scene analysis. We propose that crude spatial segmentation analyses, which are insensitive to illusory contours, occur first within dorsal visual regions, not lateral occipital complex, and that initial illusory contour sensitivity is a function of the lateral occipital complex. PMID:19895562

  6. 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

  7. 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.

  8. 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.

  9. Assessment of carotid diameter and wall thickness in ultrasound images using active contours improved by a multiresolution technique

    NASA Astrophysics Data System (ADS)

    Gutierrez, Marco A.; Pilon, Paulo E.; Lage, Silvia G.; Kopel, Liliane; Carvalho, Ricardo T.; Furuie, Sergio S.

    2002-04-01

    Carotid vessel ultrasound imaging is a reliable non-invasive technique to measure the arterial morphology. Vessel diameter, intima-media thickness (IMT) of the far wall and plaque presence can be reliably determined using B-mode ultrasound. In this paper we describe a semi-automatic approach to measure artery diameter and IMT based on an active contour technique improved by a multiresolution analysis. The operator selects a region-of-interest (ROI) in a series of carotid images obtained from B-mode ultrasound. This set of images is convolved with the corresponding partial derivatives of the Gaussian filter. The filter response is used to compute a 2D gradient magnitude image in order to refine the vessel's boundaries. Using an active contour technique the vessel's border is determined automatically. The near wall media-adventitia (NWMA), far wall media-adventitia (FWMA) and far wall lumen-intima (FWLI) borders are obtained by a least-square fitting of the active contours result. The distance between NWMA and FWLI (vessel diameter) and between FWLI and FWMA (far wall intima-media thickness) are obtained for all images and the mean value is computed during systole and diastole. The proposed method is a reliable and reproducible way of assessing the vessel diameter and far wall intima-media thickness of the carotid artery.

  10. THE ORIGIN OF SEGMENTATION MOTOR ACTIVITY IN THE INTESTINE

    PubMed Central

    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

    2016-01-01

    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 ICC 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 ICC. PMID:24561718

  11. 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.

  12. Incorporating patch subspace model in Mumford-Shah type active contours.

    PubMed

    Wang, Junyan; Chan, Kap Luk

    2013-11-01

    In this paper, we propose a unified energy minimization model for segmentation of non-smooth image structures, e.g., textures, based on Mumford-Shah functional and linear patch model. We consider that image patches of a non-smooth image structure can be modeled by a patch subspace, and image patches of different non-smooth image structures belong to different patch subspaces, which leads to a computational framework for segmentation of non-smooth image structures. Motivated by the Mumford-Shah model, we show that this segmentation framework is equivalent to minimizing a piecewise linear patch reconstruction energy. We also prove that the error of segmentation is bounded by the error of the linear patch reconstruction, meaning that improving the linear patch reconstruction for each region leads to reduction of the segmentation error. In addition, we derive an algorithm for the linear patch reconstruction with proven global optimality and linear rate of convergence. The segmentation in our method is achieved by minimizing a single energy functional without requiring predefined features. Hence, compared with the previous methods that require predefined texture features, our method can be more suitable for handling general textures in unsupervised segmentation. As a by-product, our method also produces a dictionary of optimized orthonormal descriptors for each segmented region. We mainly evaluate our method on the Brodatz textures. The experiments validate our theoretical claims and show the clear superior performance of our methods over other related methods for segmentation of the textures. PMID:23893721

  13. Real-time segmentation by Active Geometric Functions.

    PubMed

    Duan, Qi; Angelini, Elsa D; Laine, Andrew F

    2010-06-01

    Recent advances in 4D imaging and real-time imaging provide image data with clinically important cardiac dynamic information at high spatial or temporal resolution. However, the enormous amount of information contained in these data has also raised a challenge for traditional image analysis algorithms in terms of efficiency. In this paper, a novel deformable model framework, Active Geometric Functions (AGF), is introduced to tackle the real-time segmentation problem. As an implicit framework paralleling to level-set, AGF has mathematical advantages in efficiency and computational complexity as well as several flexible feature similar to level-set framework. AGF is demonstrated in two cardiac applications: endocardial segmentation in 4D ultrasound and myocardial segmentation in MRI with super high temporal resolution. In both applications, AGF can perform real-time segmentation in several milliseconds per frame, which was less than the acquisition time per frame. Segmentation results are compared to manual tracing with comparable performance with inter-observer variability. The ability of such real-time segmentation will not only facilitate the diagnoses and workflow, but also enables novel applications such as interventional guidance and interactive image acquisition with online segmentation. PMID:19800708

  14. Segments.

    ERIC Educational Resources Information Center

    Zemsky, Robert; Shaman, Susan; Shapiro, Daniel B.

    2001-01-01

    Presents a market taxonomy for higher education, including what it reveals about the structure of the market, the model's technical attributes, and its capacity to explain pricing behavior. Details the identification of the principle seams separating one market segment from another and how student aspirations help to organize the market, making…

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. Active learning based segmentation of Crohns disease from abdominal MRI.

    PubMed

    Mahapatra, Dwarikanath; Vos, Franciscus M; Buhmann, Joachim M

    2016-05-01

    This paper proposes a novel active learning (AL) framework, and combines it with semi supervised learning (SSL) for segmenting Crohns disease (CD) tissues from abdominal magnetic resonance (MR) images. Robust fully supervised learning (FSL) based classifiers require lots of labeled data of different disease severities. Obtaining such data is time consuming and requires considerable expertise. SSL methods use a few labeled samples, and leverage the information from many unlabeled samples to train an accurate classifier. AL queries labels of most informative samples and maximizes gain from the labeling effort. Our primary contribution is in designing a query strategy that combines novel context information with classification uncertainty and feature similarity. Combining SSL and AL gives a robust segmentation method that: (1) optimally uses few labeled samples and many unlabeled samples; and (2) requires lower training time. Experimental results show our method achieves higher segmentation accuracy than FSL methods with fewer samples and reduced training effort. PMID:27040833

  20. 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.

  1. 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.

  2. 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…

  3. 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

  4. Progress in the robust automated segmentation of real cell images

    NASA Astrophysics Data System (ADS)

    Bamford, P.; Jackway, P.; Lovell, Brian

    1999-07-01

    We propose a collection of robust algorithms for the segmentation of cell images from Papanicolaou stained cervical smears (`Pap' smears). This problem is deceptively difficult and often results on laboratory datasets do not carry over to real world data. Our approach is in 3 parts. First, we segment the cytoplasm from the background using a novel method based on the Wilson and Spann multi-resolution framework. Second, we segment the nucleus from the cytoplasm using an active contour method, where the best contour is found by a global minimization method. Third, we implement a method to determine a confidence measure for the segmentation of each object. This uses a stability criterion over the regularization parameter (lambda) in the active contour. We present the results of thorough testing of the algorithms on large numbers of cell images. A database of 20,120 images is used for the segmentation tests and 18,718 images for the robustness tests.

  5. 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.

  6. Ultrasound common carotid artery segmentation based on active shape model.

    PubMed

    Yang, Xin; Jin, Jiaoying; Xu, Mengling; Wu, Huihui; He, Wanji; Yuchi, Ming; Ding, Mingyue

    2013-01-01

    Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM) is developed and evaluated to outline common carotid artery (CCA) for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB) and lumen-intima-boundary (LIB) on transverse views slices from three-dimensional ultrasound (3D US) images. 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 80 mg atorvastatin and nine with placebo), who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC) of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD) of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD) of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression. PMID:23533535

  7. Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model

    PubMed Central

    Yang, Xin; Jin, Jiaoying; Xu, Mengling; Wu, Huihui; He, Wanji; Yuchi, Ming; Ding, Mingyue

    2013-01-01

    Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM) is developed and evaluated to outline common carotid artery (CCA) for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB) and lumen-intima-boundary (LIB) on transverse views slices from three-dimensional ultrasound (3D US) images. 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 80 mg atorvastatin and nine with placebo), who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC) of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD) of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD) of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression. PMID:23533535

  8. 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

  9. Distribution Metrics and Image Segmentation

    PubMed Central

    Georgiou, Tryphon; Michailovich, Oleg; Rathi, Yogesh; Malcolm, James; Tannenbaum, Allen

    2007-01-01

    The purpose of this paper is to describe certain alternative metrics for quantifying distances between distributions, and to explain their use and relevance in visual tracking. Besides the theoretical interest, such metrics may be used to design filters for image segmentation, that is for solving the key visual task of separating an object from the background in an image. The segmenting curve is represented as the zero level set of a signed distance function. Most existing methods in the geometric active contour framework perform segmentation by maximizing the separation of intensity moments between the interior and the exterior of an evolving contour. Here one can use the given distributional metric to determine a flow which minimizes changes in the distribution inside and outside the curve. PMID:18769529

  10. Improved edge detection for object segmentation in ultrasound images using Active Shape Models

    NASA Astrophysics Data System (ADS)

    Arámbula Cosío, F.; Acosta, Hèctor G.; Conde, Edgar

    2015-01-01

    We report a new method for adjusting the points of an active shape model (ASM) to the edge of an object, on a grey level image. The method is based on the original iterative search for an optimum location of each point of the ASM, along the normal direction to the model boundary. In this work we determine the optimum location of the model boundary point through minimization of the error (euclidean distance) between a profile of pixels sampled along the normal direction, and its projection on the principal component axes, obtained from a training set of normal pixel profiles, located at the edge of the object. We validated our method on ultrasound images of the prostate and photographs of the left hand. Significant improvements were observed in the segmentation of the ultrasound images, with reference to the original ASM method of adjustment, while no significant improvement was observed for the photographs. Our method produced a mean error of 4.58 (mm) between corresponding expert and automatically annotated contours of the ultrasound images of the prostate, and 3.12 (mm) of mean error for the photographs of the left hand.

  11. Determination of aortic compliance from magnetic resonance images using an automatic active contour model

    NASA Astrophysics Data System (ADS)

    Krug, Roland; Boese, Jan M.; Schad, Lothar R.

    2003-08-01

    The possibility of monitoring changes in aortic elasticity in humans has important applications for clinical trials because it estimates the efficacy of plaque-reducing therapies. The elasticity is usually quantified by compliance measurements. Therefore, the relative temporal change in the vessel cross-sectional area throughout the cardiac cycle has to be determined. In this work we determined and compared the compliance between three magnetic resonance (MR) methods (FLASH, TrueFISP and pulse-wave). Since manual outlining of the aortic wall area is a very time-consuming process and depends on an operator's variability, an algorithm for the automatic segmentation of the artery wall from MR images through the entire heart cycle is presented. The reliable detection of the artery cross-sectional area over the whole heart cycle was possible with a relative error of about 1%. Optimizing the temporal resolution to 60 ms we obtained a relative error in compliance of about 7% from TrueFISP (1.0 × 1.0 × 10 mm3, signal-to-noise ratio (SNR) > 12) and FLASH (0.7 × 0.7 × 10 mm3, SNR > 12) measurements in volunteers. Pulse-wave measurements yielded an error of more than 9%. In a study of ten volunteers, a compliance between C = 3 × 10-5 Pa-1 and C = 8 × 10-5 Pa-1 was determined, depending on age. The results of the TrueFISP and the pulse-wave measurements agreed very well with one another (confidence interval of 1 × 10-5 Pa-1) while the results of the FLASH method more clearly deviated from the TrueFISP and pulse-wave (confidence interval of more than 2 × 10-5 Pa-1).

  12. 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

  13. Template-driven segmentation of confocal microscopy images.

    PubMed

    Chen, Ying-Cheng; Chen, Yung-Chang; Chiang, Ann-Shyn

    2008-03-01

    High quality 3D visualization of anatomic structures is necessary for many applications. The anatomic structures first need to be segmented. A variety of segmentation algorithms have been developed for this purpose. For confocal microscopy images, the noise introduced during the specimen preparation process, such as the procedure of penetration or staining, may cause images to be of low contrast in some regions. This property will make segmentation difficult. Also, the segmented structures may have rugged surfaces in 3D visualization. In this paper, we present a hybrid method that is suitable for segmentation of confocal microscopy images. A rough segmentation result is obtained from the atlas-based segmentation via affine registration. The boundaries of the segmentation result are close to the object boundaries, and are regarded as the initial contours of the active contour models. After convergence of the snake algorithm, the resulting contours in regions of low contrast are locally refined by parametric bicubic surfaces to alleviate the problem of incorrect convergence. The proposed method increases the accuracy of the snake algorithm because of better initial contours. Besides, it can provide smoother segmented results in 3D visualization. PMID:18178286

  14. Strain gauge ambiguity sensor for segmented mirror active optical system

    NASA Technical Reports Server (NTRS)

    Wyman, C. L.; Howe, T. L. (Inventor)

    1974-01-01

    A system is described to measure alignment between interfacing edges of mirror segments positioned to form a segmented mirror surface. It serves as a gauge having a bending beam with four piezoresistive elements coupled across the interfaces of the edges of adjacent mirror segments. The bending beam has a first position corresponding to alignment of the edges of adjacent mirror segments, and it is bendable from the first position in a direction and to a degree dependent upon the relative misalignment between the edges of adjacent mirror segments to correspondingly vary the resistance of the strain guage. A source of power and an amplifier are connected in circuit with the strain gauge whereby the output of the amplifier varies according to the misalignment of the edges of adjacent mirror segments.

  15. Collective effects on activated segmental relaxation in supercooled polymer melts

    NASA Astrophysics Data System (ADS)

    Mirigian, Stephen; Schweizer, Kenneth

    2013-03-01

    We extend the polymer nonlinear Langevin equation (NLE) theory of activated segmental dynamics in supercooled polymer melts in two new directions. First, a well-defined mapping from real monomers to a freely-jointed chain is formulated that retains information about chain stiffness, monomer volume, and the amplitude of thermal density fluctuations. Second, collective effects beyond the local cage scale are included based on an elastic solid-state perspective in the ``shoving model'' spirit which accounts for longer range contributions to the activation barrier. In contrast to previous phenomenological treatments of this model, we formulate an explicit microscopic picture of the hopping event, and derive, not assume, that the collective barrier is directly related to the elastic shear modulus. Local hopping is thus renormalized by collective motions of the surroundings that are required to physically accommodate it. Using the PRISM theory of structure, and known compressibility and chain statistics information, quantitative applications of the new theory to predict the temperature and chain length dependence of the alpha time, shear modulus, and fragility are carried out for a range of real polymer liquids and compared to experiment.

  16. Evidence for segmental mobility in the active site of pepsin

    SciTech Connect

    Pohl, J.; Strop, P.; Senn, H.; Foundling, S.; Kostka, V.

    1986-05-01

    The low hydrolytic activity (k/sub cat/ < 0.001 s/sup -1/) of chicken pepsin (CP) towards tri- and tetrapeptides is enhanced at least 100 times by modification of its single sulfhydryl group of Cys-115, with little effect on K/sub m/-values. Modification thus simulates the effect of secondary substrate binding on pepsin catalysis. The rate of Cys-115 modification is substantially decreased in the presence of some competitive inhibitors, suggesting its active site location. Experiments with CP alkylated at Cys-115 with Acrylodan as a fluorescent probe or with N-iodoacetyl-(4-fluoro)-aniline as a /sup 19/F-nmr probe suggest conformation change around Cys-115 to occur on substrate or substrate analog binding. The difference /sup 1/H-nmr spectra (500 MHz) of unmodified free and inhibitor-complexed CP reveal chemical shifts almost exclusively in the aromatic region. The effects of Cu/sup + +/ on /sup 19/F- and /sup 1/H-nmr spectra have been studied. Examination of a computer graphics model of CP based on E. parasitica pepsin-inhibitor complex X-ray coordinates suggests that Cys-115 is located near the S/sub 3//S/sub 5/ binding site. The results are interpreted in favor of segmental mobility of this region important for pepsin substrate binding and catalysis.

  17. An adaptive multi-feature segmentation model for infrared image

    NASA Astrophysics Data System (ADS)

    Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

    2016-04-01

    Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

  18. 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.

  19. 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.

  20. 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

  1. A typology of middle school girls: audience segmentation related to physical activity.

    PubMed

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

    2006-02-01

    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

  2. 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.

  3. Shape from equal thickness contours

    SciTech Connect

    Cong, G.; Parvin, B.

    1998-05-10

    A unique imaging modality based on Equal Thickness Contours (ETC) has introduced a new opportunity for 3D shape reconstruction from multiple views. We present a computational framework for representing each view of an object in terms of its object thickness, and then integrating these representations into a 3D surface by algebraic reconstruction. The object thickness is inferred by grouping curve segments that correspond to points of second derivative maxima. At each step of the process, we use some form of regularization to ensure closeness to the original features, as well as neighborhood continuity. We apply our approach to images of a sub-micron crystal structure obtained through a holographic process.

  4. 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

  5. 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…

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. Contouring Trivariate Data

    NASA Technical Reports Server (NTRS)

    Stead, S. E.; Makatura, G. T.

    1985-01-01

    In many applications, the data consist of discrete 3-D points at which one or more parameters are given. To display contours, the data are represented by a continuous function which is evaluated at any point as needed for contouring. Contouring results are presented which are applicable both to artitrarily spaced data and to data which lie on a topologically rectangular three dimensional grid. the contours are assumed to be described by 3-D display lists for viewing on a dynamic color graphics device; that is, they will not simply be projected into 2-D and viewed as a static image on a frame buffer. Dynamic viewing of color contours may be essential to the proper interpretation of results. The gridded data lie on a topologically rectangular grid although two or more nodes may be the same point. Parametric tensor product methods may be used to fit the gridded data and to generate the contours. Rectangular elements are convenient but not necessary. For example, there are other methods which are effective for contouring over tetrahedral elements.

  12. 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. PMID:26355627

  13. Modeling robot contour processes

    NASA Astrophysics Data System (ADS)

    Whitney, D. E.; Edsall, A. C.

    Robot contour processes include those with contact force like car body grinding or deburring of complex castings, as well as those with little or no contact force like inspection. This paper describes ways of characterizing, identifying, and estimating contours and robot trajectories. Contour and robot are modeled as stochastic processes in order to emphasize that both successive robot cycles and successive industrial workpieces are similar but not exactly the same. The stochastic models can be used to identify the state of a workpiece or process, or to design a filter to estimate workpiece, shape and robot position from robot-based measurements.

  14. 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

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

    Singh, Chandan; Saini, Jaswinder Singh

    2016-05-01

    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.

  18. Iterative contextual CV model for liver segmentation

    NASA Astrophysics Data System (ADS)

    Ji, Hongwei; He, Jiangping; Yang, Xin

    2014-01-01

    In this paper, we propose a novel iterative active contour algorithm, i.e. Iterative Contextual CV Model (ICCV), and apply it to automatic liver segmentation from 3D CT images. ICCV is a learning-based method and can be divided into two stages. At the first stage, i.e. the training stage, given a set of abdominal CT training images and the corresponding manual liver labels, our task is to construct a series of self-correcting classifiers by learning a mapping between automatic segmentations (in each round) and manual reference segmentations via context features. At the second stage, i.e. the segmentation stage, first the basic CV model is used to segment the image and subsequently Contextual CV Model (CCV), which combines the image information and the current shape model, is iteratively performed to improve the segmentation result. The current shape model is obtained by inputting the previous automatic segmentation result into the corresponding self-correcting classifier. The proposed method is evaluated on the datasets of MICCAI 2007 liver segmentation challenge. The experimental results show that we obtain more and more accurate segmentation results by the iterative steps and satisfying results are obtained after about six iterations. Also, our method is comparable to the state-of-the-art work on liver segmentation.

  19. Coordination of Fictive Motor Activity in the Larval Zebrafish Is Generated by Non-Segmental Mechanisms

    PubMed Central

    Wiggin, Timothy D.; Peck, Jack H.; Masino, Mark A.

    2014-01-01

    The cellular and network basis for most vertebrate locomotor central pattern generators (CPGs) is incompletely characterized, but organizational models based on known CPG architectures have been proposed. Segmental models propose that each spinal segment contains a circuit that controls local coordination and sends longer projections to coordinate activity between segments. Unsegmented/continuous models propose that patterned motor output is driven by gradients of neurons and synapses that do not have segmental boundaries. We tested these ideas in the larval zebrafish, an animal that swims in discrete episodes, each of which is composed of coordinated motor bursts that progress rostrocaudally and alternate from side to side. We perturbed the spinal cord using spinal transections or strychnine application and measured the effect on fictive motor output. Spinal transections eliminated episode structure, and reduced both rostrocaudal and side-to-side coordination. Preparations with fewer intact segments were more severely affected, and preparations consisting of midbody and caudal segments were more severely affected than those consisting of rostral segments. In reduced preparations with the same number of intact spinal segments, side-to-side coordination was more severely disrupted than rostrocaudal coordination. Reducing glycine receptor signaling with strychnine reversibly disrupted both rostrocaudal and side-to-side coordination in spinalized larvae without disrupting episodic structure. Both spinal transection and strychnine decreased the stability of the motor rhythm, but this effect was not causal in reducing coordination. These results are inconsistent with a segmented model of the spinal cord and are better explained by a continuous model in which motor neuron coordination is controlled by segment-spanning microcircuits. PMID:25275377

  20. Model-based segmentation of the middle phalanx in digital radiographic images of the hand.

    PubMed

    Dendere, Ronald; Kabelitz, Gordian; Douglas, Tania S

    2013-01-01

    We present techniques for segmenting the middle phalanx of the middle finger in digital radiographic images using deformable models and active shape models (ASMs). The result of segmentation may be used in the estimation of bone mineral density which in turn may be used in the diagnosis of osteoporosis. A technique for minimizing user dependence is described. The segmentation accuracy of the two methods is assessed by comparing contours produced by the algorithms to those produced by manual segmentation, using the Hausdorff distance measure. The ASM technique produces more accurate segmentation. PMID:24110534

  1. Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays.

    PubMed

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

    2015-04-01

    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 three 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

  2. 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

  3. A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung.

    PubMed

    Guo, Shengwen; Fei, Baowei

    2009-03-27

    We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs. PMID:24386531

  4. A minimal path searching approach for active shape model (ASM)-based segmentation of the lung

    NASA Astrophysics Data System (ADS)

    Guo, Shengwen; Fei, Baowei

    2009-02-01

    We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 +/- 0.33 pixels, while the error is 1.99 +/- 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

  5. 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.

  6. 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. PMID:15572439

  7. Doubly rotated contoured quartz resonators.

    PubMed

    Sinha, B K

    2001-09-01

    Doubly rotated contoured quartz resonators are used in the design of temperature-compensated stable clocks and dual-mode sensors for simultaneous measurements of pressure and temperature. The design of these devices is facilitated by models that can predict frequency spectra associated with the three thickness modes and temperature and stress-induced frequency changes as a function of crystalline orientation. The Stevens-Tiersten technique for the analysis of the C-mode of a doubly rotated contoured quartz resonator is extended to include the other two thickness modes. Computational results for harmonic and anharmonic overtones of all three thickness modes of such resonators help in optimizing the radius of curvature of the contour and electrode shape for suppression of unwanted modes and prevention of activity dips. The temperature and stress-induced changes in thickness-mode resonator frequencies are calculated from a perturbation technique for small dynamic fields superposed on a static bias. The static bias refers to either a temperature or stress-induced static deformation of the resonator plate. Phenomenological models are also used for calculating the temperature and stress-induced changes in resonant frequencies as a function of crystalline orientation. Results for the SBTC-cut quartz plate with a spherical convex contour of 260 mm indicate that normal trapping occurs for the third (n = 3) and fifth (n = 5) harmonic of the A-mode, the fundamental (n = 1) and third (n = 3) harmonic of the B-mode, and the fundamental (n = 1) and fifth (n = 5) harmonic of the C-mode. PMID:11570746

  8. 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.

  9. Contour detection based on brightness and contour completion

    NASA Astrophysics Data System (ADS)

    Zou, Lamei; Wan, Min; Jin, Liujia; Gao, Yahong; Yang, Weidong

    2015-12-01

    The further research of visual processing mechanism provides a new idea for contour detection. On the primary visual cortex, the non-classical receptive field of the neurons has the orientation selectivity exerts suppression effect on the response of classical receptive field, which influences edge or line perception. Based on the suppression property of non-classical receptive field and contour completion, this paper proposed a contour detection method based on brightness and contour completion. The experiment shows that the proposed method can not only effectively eliminate clutter information, but also connect the broken contour points by taking advantage of contour completion.

  10. 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.

  11. 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.

  12. 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…

  13. 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

  14. 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.

  15. 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

  16. Spatial Segmentation of Image Sequences Based on Their Time Activity

    NASA Astrophysics Data System (ADS)

    Galatsanos, N. P.

    2006-04-01

    There are many applications in medical imaging where one is interested in finding the areas of the image that exhibit the same time activity. Such applications occur in positron and single photon emission imaging as well as in perfusion studies with magnetic resonance imaging (MRI). In this talk we will present Bayesian methodology based on clustering to solve this problem. At first the dimensionality of the pixel observations is reduced using a probabilistic principle component model along the spatial dimension of the data. Then, a multidimensional Gaussian mixture model with spatial constraints is used for clustering. Examples from MRI perfusion studies of the heart and the brain will be shown.

  17. 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

  18. 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…

  19. 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

  20. Data acceptance for automated leukocyte tracking through segmentation of spatiotemporal images.

    PubMed

    Ray, Nilanjan; Acton, Scott T

    2005-10-01

    A crucial task in inflammation research and inflammatory drug validation is leukocyte velocity data collection from microscopic video imagery. Since manual methods are bias-prone and extremely time consuming, automated tracking methods are required to compute cell velocities. However, an automated tracking method is of little practical use unless it is accompanied by a mechanism to validate the tracker output. In this paper, we propose a validation technique that accepts or rejects the output of automated tracking methods. The proposed method first generates a spatiotemporal image from the cell locations given by a tracking method; then, it segments the spatiotemporal image to detect the presence or absence of a leukocyte. For segmenting the spatiotemporal images, we employ an edge-direction sensitive nonlinear filter followed by an active contour based technique. The proposed nonlinear filter, the maximum absolute average directional derivative (MAADD), first computes the magnitude of the mean directional derivative over an oriented line segment and then chooses the maximum of all such values within a range of orientations of the line segment. The proposed active contour segmentation is obtained via growing contours controlled by a two-dimensional force field, which is constructed by imposing a Dirichlet boundary condition on the gradient vector flow (GVF) field equations. The performance of the proposed validation method is reported here for the outputs of three different tracking techniques: the method was successful in 97% of the trials using manual tracking, in 94% using correlation tracking and in 93% using active contour tracking. PMID:16235656

  1. Simultaneous Segmentation of Prostatic Zones Using Active Appearance Models With Multiple Coupled Levelsets

    PubMed Central

    Toth, Robert; Ribault, Justin; Gentile, John; Sperling, Dan; Madabhushi, Anant

    2013-01-01

    In this work we present an improvement to the popular Active Appearance Model (AAM) algorithm, that we call the Multiple-Levelset AAM (MLA). The MLA can simultaneously segment multiple objects, and makes use of multiple levelsets, rather than anatomical landmarks, to define the shapes. AAMs traditionally define the shape of each object using a set of anatomical landmarks. However, landmarks can be difficult to identify, and AAMs traditionally only allow for segmentation of a single object of interest. The MLA, which is a landmark independent AAM, allows for levelsets of multiple objects to be determined and allows for them to be coupled with image intensities. This gives the MLA the flexibility to simulataneously segmentation multiple objects of interest in a new image. In this work we apply the MLA to segment the prostate capsule, the prostate peripheral zone (PZ), and the prostate central gland (CG), from a set of 40 endorectal, T2-weighted MRI images. The MLA system we employ in this work leverages a hierarchical segmentation framework, so constructed as to exploit domain specific attributes, by utilizing a given prostate segmentation to help drive the segmentations of the CG and PZ, which are embedded within the prostate. Our coupled MLA scheme yielded mean Dice accuracy values of .81, .79 and .68 for the prostate, CG, and PZ, respectively using a leave-one-out cross validation scheme over 40 patient studies. When only considering the midgland of the prostate, the mean DSC values were .89, .84, and .76 for the prostate, CG, and PZ respectively. PMID:23997571

  2. Simultaneous Segmentation of Prostatic Zones Using Active Appearance Models With Multiple Coupled Levelsets.

    PubMed

    Toth, Robert; Ribault, Justin; Gentile, John; Sperling, Dan; Madabhushi, Anant

    2013-09-01

    In this work we present an improvement to the popular Active Appearance Model (AAM) algorithm, that we call the Multiple-Levelset AAM (MLA). The MLA can simultaneously segment multiple objects, and makes use of multiple levelsets, rather than anatomical landmarks, to define the shapes. AAMs traditionally define the shape of each object using a set of anatomical landmarks. However, landmarks can be difficult to identify, and AAMs traditionally only allow for segmentation of a single object of interest. The MLA, which is a landmark independent AAM, allows for levelsets of multiple objects to be determined and allows for them to be coupled with image intensities. This gives the MLA the flexibility to simulataneously segmentation multiple objects of interest in a new image. In this work we apply the MLA to segment the prostate capsule, the prostate peripheral zone (PZ), and the prostate central gland (CG), from a set of 40 endorectal, T2-weighted MRI images. The MLA system we employ in this work leverages a hierarchical segmentation framework, so constructed as to exploit domain specific attributes, by utilizing a given prostate segmentation to help drive the segmentations of the CG and PZ, which are embedded within the prostate. Our coupled MLA scheme yielded mean Dice accuracy values of .81, .79 and .68 for the prostate, CG, and PZ, respectively using a leave-one-out cross validation scheme over 40 patient studies. When only considering the midgland of the prostate, the mean DSC values were .89, .84, and .76 for the prostate, CG, and PZ respectively. PMID:23997571

  3. Differential segmental strain during active lengthening in a large biarticular thigh muscle during running

    PubMed Central

    Carr, Jennifer A.; Ellerby, David J.; Marsh, Richard L.

    2011-01-01

    SUMMARY The iliotibialis lateralis pars postacetabularis (ILPO) is the largest muscle in the hindlimb of the guinea fowl and is thought to play an important role during the stance phase of running, both absorbing and producing work. Using sonomicrometry and electromyography, we examined whether the ILPO experiences differential strain between proximal, central and distal portions of the posterior fascicles. When the ILPO is being lengthened while active, the distal portion was found to lengthen significantly more than either the proximal or central portions of the muscle. Our data support the hypothesis that the distal segment lengthened farther and faster because it began activity at shorter sarcomere lengths on the ascending limb of the length–tension curve. Probably because of the self-stabilizing effects of operating on the ascending limb of the length–tension curve, all segments reached the end of lengthening and started shortening at the same sarcomere length. During shortening, this similarity in sarcomere length among the segments was maintained, as predicted from force–velocity effects, and shortening strain was similar in all segments. The differential active strain during active lengthening is thus ultimately determined by differences in strain during the passive portion of the cycle. The sarcomere lengths of all segments of the fascicles were similar at the end of active shortening, but after the passive portion of the cycle the distal segment was shorter. Differential strain in the segments during the passive portion of the cycle may be caused by differential joint excursions at the knee and hip acting on the ends of the muscle and being transmitted differentially by the passive visco-elastic properties of the muscle. Alternatively, the differential passive strain could be due to the action of active or passive muscles in the thigh that transmit force to the IPLO in shear. Based on basic sarcomere dynamics we predict that differential strain is

  4. Modulation of Cell-adhesive Activity of Fibronectin by the Alternatively Spliced EDA Segment

    PubMed Central

    Manabe, Ri-ichiroh; Oh-e, Naoko; Maeda, Toshinaga; Fukuda, Tomohiko; Sekiguchi, Kiyotoshi

    1997-01-01

    Fibronectin (FN) has a complex pattern of alternative splicing at the mRNA level. One of the alternatively spliced segments, EDA, is prominently expressed during biological processes involving substantial cell migration and proliferation, such as embryonic development, malignant transformation, and wound healing. To examine the function of the EDA segment, we overexpressed recombinant FN isoforms with or without EDA in CHO cells and compared their cell-adhesive activities using purified proteins. EDA+ FN was significantly more potent than EDA− FN in promoting cell spreading and cell migration, irrespective of the presence or absence of a second alternatively spliced segment, EDB. The cell spreading activity of EDA+ FN was not affected by antibodies recognizing the EDA segment but was abolished by antibodies against integrin α5 and β1 subunits and by Gly-Arg-Gly-Asp-Ser-Pro peptide, indicating that the EDA segment enhanced the cell-adhesive activity of FN by potentiating the interaction of FN with integrin α5β1. In support of this conclusion, purified integrin α5β1 bound more avidly to EDA+ FN than to EDA− FN. Augmentation of integrin binding by the EDA segment was, however, observed only in the context of the intact FN molecule, since the difference in integrin-binding activity between EDA+ FN and EDA− FN was abolished after limited proteolysis with thermolysin. Consistent with this observation, binding of integrin α5β1 to a recombinant FN fragment, consisting of the central cell-binding domain and the adjacent heparin-binding domain Hep2, was not affected by insertion of the EDA segment. Since the insertion of an extra type III module such as EDA into an array of repeated type III modules is expected to rotate the polypeptide up to 180° at the position of the insertion, the conformation of the FN molecule may be globally altered upon insertion of the EDA segment, resulting in an increased exposure of the RGD motif in III10 module and/or local

  5. Automatic segmentation of heart cavities in multidimensional ultrasound images

    NASA Astrophysics Data System (ADS)

    Wolf, Ivo; Glombitza, Gerald; De Simone, Rosalyn; Meinzer, Hans-Peter

    2000-06-01

    We propose a segmentation method different from active contours, which can cope with incomplete edges. The algorithm has been developed to segment heart cavities, but may be extended to more complex object shapes. Due to the almost convex geometry of heart cavities we are using a polar coordinate system with its origin near the cavity's center. The image is scanned from the origin for potential edge points. In order to assess the likelihood of an edge point to belong to the myocardial wall, region based information, such as visibility and local wall thickness, is included. The local information (edge points) progressively is expanded by first grouping the edge points to line segments and then selecting a subgroup of segments to obtain the final closed contour. This is done by means of minimizing a cost function. The plausibility of the result is checked and, if needed, the contour is corrected and/or refined by searching for additional potential edge points. For multidimensional images the algorithm is applied slice-by-slice without the need of further user interaction. The new segmentation method has been applied to clinical ultrasound images, the result being that the myocardial wall correctly was detected in the vast majority of cases.

  6. 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.

  7. Lung Segmentation in 4D CT Volumes Based on Robust Active Shape Model Matching

    PubMed Central

    Gill, Gurman; Beichel, Reinhard R.

    2015-01-01

    Dynamic and longitudinal lung CT imaging produce 4D lung image data sets, enabling applications like radiation treatment planning or assessment of response to treatment of lung diseases. In this paper, we present a 4D lung segmentation method that mutually utilizes all individual CT volumes to derive segmentations for each CT data set. Our approach is based on a 3D robust active shape model and extends it to fully utilize 4D lung image data sets. This yields an initial segmentation for the 4D volume, which is then refined by using a 4D optimal surface finding algorithm. The approach was evaluated on a diverse set of 152 CT scans of normal and diseased lungs, consisting of total lung capacity and functional residual capacity scan pairs. In addition, a comparison to a 3D segmentation method and a registration based 4D lung segmentation approach was performed. The proposed 4D method obtained an average Dice coefficient of 0.9773 ± 0.0254, which was statistically significantly better (p value ≪0.001) than the 3D method (0.9659 ± 0.0517). Compared to the registration based 4D method, our method obtained better or similar performance, but was 58.6% faster. Also, the method can be easily expanded to process 4D CT data sets consisting of several volumes. PMID:26557844

  8. The W. M. Keck Telescope segmented primary mirror active control system

    SciTech Connect

    Jared, R.C.; Arthur, A.A.; Andreae, S.; Biocca, A.; Cohen, R.W.; Fuertes, J.M.; Franck, J.; Gabor, G.; Llacer, J.; Mast, T.; Meng, J.; Merrick, T.; Minor, R.; Nelson, J.; Orayani, M.; Salz, P.; Schaefer, B.; Witebsky, C.

    1989-07-01

    The ten meter diameter primary mirror of the W. M. Keck Telescope is a mosaic of thirty-six hexagonal mirrors. An active control system stabilizes the primary mirror. The active control system uses 168 measurements of the relative positions of adjacent mirror segments and 3 measurements of the primary mirror position in the telescope structure to control the 108 degrees of freedom needed to stabilize the figure and position of the primary mirror. The components of the active control system are relative position sensors, electronics, computers, actuators that position the mirrors, and software. The software algorithms control the primary mirror, perform star image stacking, emulate the segments, store and fit calibration data, and locate hardware defects. We give an overview of the active control system, its functional requirements and test measurements. 12 refs.

  9. Initiation of segmental locomotor-like activities by stimulation of ventrolateral funiculus in the neonatal rat.

    PubMed

    Cheng, Jianguo; Magnuson, David S K

    2011-09-01

    Descending control is critically important for the generation of locomotor activities. Yet, our understanding of the descending control system of locomotion is limited. We hypothesized that stimulation of the ventrolateral funiculus (VLF) induces rhythmic activity in lumbar neurons that is correlated with locomotor-like activity in the neonatal rat. Intracellular recordings were conducted in the L2-L3 lumbar segments, while locomotor-like output was monitored in the L2 and L5 ventral roots. Stimulation of the VLF at thoracic segments induced locomotor-like activity in the L2 and L5 ventral roots in majority of the preparations (26/33). In a few midline split cord preparations (4/13), VLF stimulation induced rhythmic locomotor-like bursts in either L2 or L5 ventral root without alternating pattern between the ventral roots. The response latencies suggest that VLF stimulation induced antidromic activation (<1 ms, 8 cells), monosynaptic activation (1-3 ms, 18 cells), and oligosynaptic activation (3.5-5 ms, 14 cells) of segmental neurons in the lumbar region. VLF stimulation induced rhythmic membrane potential oscillations with or without bursting of action potentials in 9 of 40 putative interneurons. The membrane potential oscillations were in phase with the locomotor-like output of the L2 ventral root in 7 of the 9 cells while the other 2 cells oscillated in phase with the L5 ventral root activity. We have thus demonstrated that descending axons exist in the VLF which make synaptic connections with segmental neurons in the lumbar region that may be a critical element of the locomotor neural network for the initiation of locomotion. PMID:21858680

  10. Initiation of segmental locomotor-like activities by stimulation of ventrolateral funiculus in the neonatal rat

    PubMed Central

    Magnuson, David S. K.

    2011-01-01

    Descending control is critically important for the generation of locomotor activities. Yet, our understanding of the descending control system of locomotion is limited. We hypothesized that stimulation of the ventrolateral funiculus (VLF) induces rhythmic activity in lumbar neurons that is correlated with locomotor-like activity in the neonatal rat. Intracellular recordings were conducted in the L2–L3 lumbar segments, while locomotor-like output was monitored in the L2 and L5 ventral roots. Stimulation of the VLF at thoracic segments induced locomotor-like activity in the L2 and L5 ventral roots in majority of the preparations (26/33). In a few midline split cord preparations (4/13), VLF stimulation induced rhythmic locomotor-like bursts in either L2 or L5 ventral root without alternating pattern between the ventral roots. The response latencies suggest that VLF stimulation induced antidromic activation (<1 ms, 8 cells), monosynaptic activation (1–3 ms, 18 cells), and oligosynaptic activation (3.5–5 ms, 14 cells) of segmental neurons in the lumbar region. VLF stimulation induced rhythmic membrane potential oscillations with or without bursting of action potentials in 9 of 40 putative interneurons. The membrane potential oscillations were in phase with the locomotor-like output of the L2 ventral root in 7 of the 9 cells while the other 2 cells oscillated in phase with the L5 ventral root activity. We have thus demonstrated that descending axons exist in the VLF which make synaptic connections with segmental neurons in the lumbar region that may be a critical element of the locomotor neural network for the initiation of locomotion. PMID:21858680

  11. 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

  12. 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

  13. Segmentation of 4D cardiac computer tomography images using active shape models

    NASA Astrophysics Data System (ADS)

    Leiner, Barba-J.; Olveres, Jimena; Escalante-Ramírez, Boris; Arámbula, Fernando; Vallejo, Enrique

    2012-06-01

    This paper describes a segmentation method for time series of 3D cardiac images based on deformable models. The goal of this work is to extend active shape models (ASM) of tree-dimensional objects to the problem of 4D (3D + time) cardiac CT image modeling. The segmentation is achieved by constructing a point distribution model (PDM) that encodes the spatio-temporal variability of a training set, i.e., the principal modes of variation of the temporal shapes are computed using some statistical parameters. An active search is used in the segmentation process where an initial approximation of the spatio-temporal shape is given and the gray level information in the neighborhood of the landmarks is analyzed. The starting shape is able to deform so as to better fit the data, but in the range allowed by the point distribution model. Several time series consisting of eleven 3D images of cardiac CT are employed for the method validation. Results are compared with manual segmentation made by an expert. The proposed application can be used for clinical evaluation of the left ventricle mechanical function. Likewise, the results can be taken as the first step of processing for optic flow estimation algorithms.

  14. Segmentation of risk structures for otologic surgery using the Probabilistic Active Shape Model (PASM)

    NASA Astrophysics Data System (ADS)

    Becker, Meike; Kirschner, Matthias; Sakas, Georgios

    2014-03-01

    Our research project investigates a multi-port approach for minimally-invasive otologic surgery. For planning such a surgery, an accurate segmentation of the risk structures is crucial. However, the segmentation of these risk structures is a challenging task: The anatomical structures are very small and some have a complex shape, low contrast and vary both in shape and appearance. Therefore, prior knowledge is needed which is why we apply model-based approaches. In the present work, we use the Probabilistic Active Shape Model (PASM), which is a more flexible and specific variant of the Active Shape Model (ASM), to segment the following risk structures: cochlea, semicircular canals, facial nerve, chorda tympani, ossicles, internal auditory canal, external auditory canal and internal carotid artery. For the evaluation we trained and tested the algorithm on 42 computed tomography data sets using leave-one-out tests. Visual assessment of the results shows in general a good agreement of manual and algorithmic segmentations. Further, we achieve a good Average Symmetric Surface Distance while the maximum error is comparatively large due to low contrast at start and end points. Last, we compare the PASM to the standard ASM and show that the PASM leads to a higher accuracy.

  15. Nonlocal regularization for active appearance model: Application to medial temporal lobe segmentation.

    PubMed

    Hu, Shiyan; Coupé, Pierrick; Pruessner, Jens C; Collins, D Louis

    2014-02-01

    The human medial temporal lobe (MTL) is an important part of the limbic system, and its substructures play key roles in learning, memory, and neurodegeneration. The MTL includes the hippocampus (HC), amygdala (AG), parahippocampal cortex (PHC), entorhinal cortex, and perirhinal cortex--structures that are complex in shape and have low between-structure intensity contrast, making them difficult to segment manually in magnetic resonance images. This article presents a new segmentation method that combines active appearance modeling and patch-based local refinement to automatically segment specific substructures of the MTL including HC, AG, PHC, and entorhinal/perirhinal cortex from MRI data. Appearance modeling, relying on eigen-decomposition to analyze statistical variations in image intensity and shape information in study population, is used to capture global shape characteristics of each structure of interest with a generative model. Patch-based local refinement, using nonlocal means to compare the image local intensity properties, is applied to locally refine the segmentation results along the structure borders to improve structure delimitation. In this manner, nonlocal regularization and global shape constraints could allow more accurate segmentations of structures. Validation experiments against manually defined labels demonstrate that this new segmentation method is computationally efficient, robust, and accurate. In a leave-one-out validation on 54 normal young adults, the method yielded a mean Dice κ of 0.87 for the HC, 0.81 for the AG, 0.73 for the anterior parts of the parahippocampal gyrus (entorhinal and perirhinal cortex), and 0.73 for the posterior parahippocampal gyrus. PMID:22987811

  16. A multi-modal prostate segmentation scheme by combining spectral clustering and active shape models

    NASA Astrophysics Data System (ADS)

    Toth, Robert; Tiwari, Pallavi; Rosen, Mark; Kalyanpur, Arjun; Pungavkar, Sona; Madabhushi, Anant

    2008-03-01

    Segmentation of the prostate boundary on clinical images is useful in a large number of applications including calculating prostate volume during biopsy, tumor estimation, and treatment planning. Manual segmentation of the prostate boundary is, however, time consuming and subject to inter- and intra-reader variability. Magnetic Resonance (MR) imaging (MRI) and MR Spectroscopy (MRS) have recently emerged as promising modalities for detection of prostate cancer in vivo. In this paper we present a novel scheme for accurate and automated prostate segmentation on in vivo 1.5 Tesla multi-modal MRI studies. The segmentation algorithm comprises two steps: (1) A hierarchical unsupervised spectral clustering scheme using MRS data to isolate the region of interest (ROI) corresponding to the prostate, and (2) an Active Shape Model (ASM) segmentation scheme where the ASM is initialized within the ROI obtained in the previous step. The hierarchical MRS clustering scheme in step 1 identifies spectra corresponding to locations within the prostate in an iterative fashion by discriminating between potential prostate and non-prostate spectra in a lower dimensional embedding space. The spatial locations of the prostate spectra so identified are used as the initial ROI for the ASM. The ASM is trained by identifying user-selected landmarks on the prostate boundary on T2 MRI images. Boundary points on the prostate are identified using mutual information (MI) as opposed to the traditional Mahalanobis distance, and the trained ASM is deformed to fit the boundary points so identified. Cross validation on 150 prostate MRI slices yields an average segmentation sensitivity, specificity, overlap, and positive predictive value of 89, 86, 83, and 93% respectively. We demonstrate that the accurate initialization of the ASM via the spectral clustering scheme is necessary for automated boundary extraction. Our method is fully automated, robust to system parameters, and computationally efficient.

  17. Framework of a Contour Based Depth Map Coding Method

    NASA Astrophysics Data System (ADS)

    Wang, Minghui; He, Xun; Jin, Xin; Goto, Satoshi

    Stereo-view and multi-view video formats are heavily investigated topics given their vast application potential. Depth Image Based Rendering (DIBR) system has been developed to improve Multiview Video Coding (MVC). Depth image is introduced to synthesize virtual views on the decoder side in this system. Depth image is a piecewise image, which is filled with sharp contours and smooth interior. Contours in a depth image show more importance than interior in view synthesis process. In order to improve the quality of the synthesized views and reduce the bitrate of depth image, a contour based coding strategy is proposed. First, depth image is divided into layers by different depth value intervals. Then regions, which are defined as the basic coding unit in this work, are segmented from each layer. The region is further divided into the contour and the interior. Two different procedures are employed to code contours and interiors respectively. A vector-based strategy is applied to code the contour lines. Straight lines in contours cost few of bits since they are regarded as vectors. Pixels, which are out of straight lines, are coded one by one. Depth values in the interior of a region are modeled by a linear or nonlinear formula. Coefficients in the formula are retrieved by regression. This process is called interior painting. Unlike conventional block based coding method, the residue between original frame and reconstructed frame (by contour rebuilt and interior painting) is not sent to decoder. In this proposal, contour is coded in a lossless way whereas interior is coded in a lossy way. Experimental results show that the proposed Contour Based Depth map Coding (CBDC) achieves a better performance than JMVC (reference software of MVC) in the high quality scenarios.

  18. 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.

  19. [Post bariatric body contouring.

    PubMed

    Winge, Rikke; Henriksen, Trine Foged; Printzlau, Andreas; Hülmich, Lisbet

    2014-03-17

    Post bariatric body contouring in Denmark is currently a field under development. The scope of this article is to give an overview of existing plastic surgery techniques being used to treat patients with massive weight loss, as well as the current indications for patient referral. Furthermore, we describe how to optimise the preoperative evaluation of the patient and give a brief description of potential surgical adverse effects and their prevalence. Further research can provide this field with invaluable data regarding the post-operative effects on patient rehabilitation and quality of life. PMID:25096208

  20. 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.

  1. 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

  2. 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.

  3. Active edge control in the precessions polishing process for manufacturing large mirror segments

    NASA Astrophysics Data System (ADS)

    Li, Hongyu; Zhang, Wei; Walker, David; Yu, Gouyo

    2014-09-01

    The segmentation of the primary mirror is the only promising solution for building the next generation of ground telescopes. However, manufacturing segmented mirrors presents its own challenges. The edge mis-figure impacts directly on the telescope's scientific output. The `Edge effect' significantly dominates the polishing precision. Therefore, the edge control is regarded as one of the most difficult technical issues in the segment production that needs to be addressed urgently. This paper reports an active edge control technique for the mirror segments fabrication using the Precession's polishing technique. The strategy in this technique requires that the large spot be selected on the bulk area for fast polishing, and the small spot is used for edge figuring. This can be performed by tool lift and optimizing the dell time to compensate for non-uniform material removal at the edge zone. This requires accurate and stable edge tool influence functions. To obtain the full tool influence function at the edge, we have demonstrated in previous work a novel hybrid-measurement method which uses both simultaneous phase interferometry and profilometry. In this paper, the edge effect under `Bonnet tool' polishing is investigated. The pressure distribution is analyzed by means of finite element analysis (FEA). According to the `Preston' equation, the shape of the edge tool influence functions is predicted. With this help, the multiple process parameters at the edge zone are optimized. This is demonstrated on a 200mm crosscorners hexagonal part with a result of PV less than 200nm for entire surface.

  4. Robot Hand Would Adapt To Contours

    NASA Technical Reports Server (NTRS)

    Collins, Earl R., Jr.

    1990-01-01

    Conceptual device uses hydraulic pressure to activate fingers. Projections on opposing fingers of proposed robot hand automatically conform to contours of object on contact. Pistons connected to common reservoir provide gentle, firm grip. Fingers communicate with each other via hydraulic pressure, without elaborate control system. Pistons move in and out, and tips slope to match contour of object. Their action tends to center object on finger. Hand used to grasp objects of various shapes and sizes. Conforming process passive; pressure of object on one or several pad elements forces other pad elements to touch it. Would not use elaborate mechanisms involving motors, cams, and cables.

  5. 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.

  6. 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.

  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. Countering beam divergence effects with focused segmented scintillators for high DQE megavoltage active matrix imagers

    NASA Astrophysics Data System (ADS)

    Liu, Langechuan; Antonuk, Larry E.; Zhao, Qihua; El-Mohri, Youcef; Jiang, Hao

    2012-08-01

    The imaging performance of active matrix flat-panel imagers designed for megavoltage imaging (MV AMFPIs) is severely constrained by relatively low x-ray detection efficiency, which leads to a detective quantum efficiency (DQE) of only ∼1%. Previous theoretical and empirical studies by our group have demonstrated the potential for addressing this constraint through the utilization of thick, two-dimensional, segmented scintillators with optically isolated crystals. However, this strategy is constrained by the degradation of high-frequency DQE resulting from spatial resolution loss at locations away from the central beam axis due to oblique incidence of radiation. To address this challenge, segmented scintillators constructed so that the crystals are individually focused toward the radiation source are proposed and theoretically investigated. The study was performed using Monte Carlo simulations of radiation transport to examine the modulation transfer function and DQE of focused segmented scintillators with thicknesses ranging from 5 to 60 mm. The results demonstrate that, independent of scintillator thickness, the introduction of focusing largely restores spatial resolution and DQE performance otherwise lost in thick, unfocused segmented scintillators. For the case of a 60 mm thick BGO scintillator and at a location 20 cm off the central beam axis, use of focusing improves DQE by up to a factor of ∼130 at non-zero spatial frequencies. The results also indicate relatively robust tolerance of such scintillators to positional displacements, of up to 10 cm in the source-to-detector direction and 2 cm in the lateral direction, from their optimal focusing position, which could potentially enhance practical clinical use of focused segmented scintillators in MV AMFPIs.

  9. Countering Beam Divergence Effects with Focused Segmented Scintillators for High DQE Megavoltage Active Matrix Imagers

    PubMed Central

    Liu, Langechuan; Antonuk, Larry E; Zhao, Qihua; El-Mohri, Youcef; Jiang, Hao

    2012-01-01

    The imaging performance of active matrix flat-panel imagers designed for megavoltage imaging (MV AMFPIs) is severely constrained by relatively low x-ray detection efficiency, which leads to a detective quantum efficiency (DQE) of only ~1%. Previous theoretical and empirical studies by our group have demonstrated the potential for addressing this constraint through utilization of thick, two-dimensional, segmented scintillators with optically isolated crystals. However, this strategy is constrained by degradation of high-frequency DQE resulting from spatial resolution loss at locations away from the central beam axis due to oblique incidence of radiation. To address this challenge, segmented scintillators constructed so that the crystals are individually focused toward the radiation source are proposed and theoretically investigated. The study was performed using Monte Carlo simulations of radiation transport to examine the modulation transfer function and DQE of focused segmented scintillators with thicknesses ranging from 5 to 60 mm. The results demonstrate that, independent of scintillator thickness, the introduction of focusing largely restores spatial resolution and DQE performance otherwise lost in thick, unfocused segmented scintillators. For the case of a 60 mm thick BGO scintillator and at a location 20 cm off the central beam axis, use of focusing improves DQE by up to a factor of ~130 at non-zero spatial frequencies. The results also indicate relatively robust tolerance of such scintillators to positional displacements, of up to 10 cm in the source-to-detector direction and 2 cm in the lateral direction, from their optimal focusing position, which could potentially enhance practical clinical use of focused segmented scintillators in MV AMFPIs. PMID:22854009

  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. A magnetic resonance spectroscopy driven initialization scheme for active shape model based prostate segmentation.

    PubMed

    Toth, Robert; Tiwari, Pallavi; Rosen, Mark; Reed, Galen; Kurhanewicz, John; Kalyanpur, Arjun; Pungavkar, Sona; Madabhushi, Anant

    2011-04-01

    Segmentation of the prostate boundary on clinical images is useful in a large number of applications including calculation of prostate volume pre- and post-treatment, to detect extra-capsular spread, and for creating patient-specific anatomical models. Manual segmentation of the prostate boundary is, however, time consuming and subject to inter- and intra-reader variability. T2-weighted (T2-w) magnetic resonance (MR) structural imaging (MRI) and MR spectroscopy (MRS) have recently emerged as promising modalities for detection of prostate cancer in vivo. MRS data consists of spectral signals measuring relative metabolic concentrations, and the metavoxels near the prostate have distinct spectral signals from metavoxels outside the prostate. Active Shape Models (ASM's) have become very popular segmentation methods for biomedical imagery. However, ASMs require careful initialization and are extremely sensitive to model initialization. The primary contribution of this paper is a scheme to automatically initialize an ASM for prostate segmentation on endorectal in vivo multi-protocol MRI via automated identification of MR spectra that lie within the prostate. A replicated clustering scheme is employed to distinguish prostatic from extra-prostatic MR spectra in the midgland. The spatial locations of the prostate spectra so identified are used as the initial ROI for a 2D ASM. The midgland initializations are used to define a ROI that is then scaled in 3D to cover the base and apex of the prostate. A multi-feature ASM employing statistical texture features is then used to drive the edge detection instead of just image intensity information alone. Quantitative comparison with another recent ASM initialization method by Cosio showed that our scheme resulted in a superior average segmentation performance on a total of 388 2D MRI sections obtained from 32 3D endorectal in vivo patient studies. Initialization of a 2D ASM via our MRS-based clustering scheme resulted in an average

  12. 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.

  13. Roads Centre-Axis Extraction in Airborne SAR Images: AN Approach Based on Active Contour Model with the Use of Semi-Automatic Seeding

    NASA Astrophysics Data System (ADS)

    Lotte, R. G.; Sant'Anna, S. J. S.; Almeida, C. M.

    2013-05-01

    Research works dealing with computational methods for roads extraction have considerably increased in the latest two decades. This procedure is usually performed on optical or microwave sensors (radar) imagery. Radar images offer advantages when compared to optical ones, for they allow the acquisition of scenes regardless of atmospheric and illumination conditions, besides the possibility of surveying regions where the terrain is hidden by the vegetation canopy, among others. The cartographic mapping based on these images is often manually accomplished, requiring considerable time and effort from the human interpreter. Maps for detecting new roads or updating the existing roads network are among the most important cartographic products to date. There are currently many studies involving the extraction of roads by means of automatic or semi-automatic approaches. Each of them presents different solutions for different problems, making this task a scientific issue still open. One of the preliminary steps for roads extraction can be the seeding of points belonging to roads, what can be done using different methods with diverse levels of automation. The identified seed points are interpolated to form the initial road network, and are hence used as an input for an extraction method properly speaking. The present work introduces an innovative hybrid method for the extraction of roads centre-axis in a synthetic aperture radar (SAR) airborne image. Initially, candidate points are fully automatically seeded using Self-Organizing Maps (SOM), followed by a pruning process based on specific metrics. The centre-axis are then detected by an open-curve active contour model (snakes). The obtained results were evaluated as to their quality with respect to completeness, correctness and redundancy.

  14. 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.

  15. 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.

  16. 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.

  17. 3D prostate boundary segmentation from ultrasound images using 2D active shape models.

    PubMed

    Hodge, Adam C; Ladak, Hanif M

    2006-01-01

    Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm for semi-automatic, three-dimensional (3D) segmentation of the prostate boundary from ultrasound images based on two-dimensional (2D) active shape models (ASM) and rotation-based slicing. Evaluation of the algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. The mean absolute distance between the algorithm and gold standard boundaries was 1.09+/-0.49 mm, the average percent absolute volume difference was 3.28+/-3.16%, and a 5x speed increase as compared manual planimetry was achieved. PMID:17946106

  18. Sequential Activation of a Segmented Ground Pad Reduces Skin Heating During Radiofrequency Tumor Ablation: Optimization via Computational Models

    PubMed Central

    Schutt, David J.; Haemmerich, Dieter

    2009-01-01

    Radiofrequency (RF) ablation has become an accepted treatment modality for unresectable tumors. The need for larger ablation zones has resulted in increased RF generator power. Skin burns due to ground pad heating are increasingly limiting further increases in generator power, and thus, ablation zone size. We investigated a method for reducing ground pad heating in which a commercial ground pad is segmented into multiple ground electrodes, with sequential activation of ground electrode subsets. We created finite-element method computer models of a commercial ground pad (14 × 23 cm) and compared normal operation of a standard pad to sequential activation of a segmented pad (two to five separate ground electrode segments). A constant current of 1 A was applied for 12 min in all simulations. Time periods during sequential activation simulations were adjusted to keep the leading edge temperatures at each ground electrode equal. The maximum temperature using standard activation of the commercial pad was 41.7 °C. For sequential activation of a segmented pad, the maximum temperature ranged from 39.3 °C (five segments) to 40.9 °C (two segments). Sequential activation of a segmented ground pad resulted in lower tissue temperatures. This method may reduce the incidence of ground pad burns and enable the use of higher power generators during RF tumor ablation. PMID:18595807

  19. Film coatings for contoured surfaces

    NASA Technical Reports Server (NTRS)

    Flanery, H. E.; Frost, R. K.; Olson, A. J.

    1981-01-01

    Thickness of fluorocarbon elastomer films applied in contoured shapes by vacuum forming is difficult to control at sharply curved areas. Process for spraying contoured fluorocarbon elastomer films of uniform strength and thickness has been used instead of vacuum forming to fabricate curtain covering external tank of Space Shuttle. Conventional spray equipment may be used.

  20. 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)

  1. MAINE CONTOUR LINES 500 FEET

    EPA Science Inventory

    MECON500 contains 500 foot contour intervals for Maine, generated from USGS 1:250,000 DEMs. Arcs are coded by elevation. Due to the nature of the source data, the positional accuracy of these contour lines varies from good to poor. Use of these data at scales of greater then 1:2...

  2. MAINE CONTOUR LINES 60 FEET

    EPA Science Inventory

    MECON60 contains contours at 60 foot intervals for the entire state of Maine as generated from USGS 1:250,000 scale digital elevation models using ARC/INFO software. Arcs are coded by elevation. Due to the nature of the source data, the positional accuracy of these contour line...

  3. 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.

  4. 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.…

  5. A hierarchical method based on active shape models and directed Hough transform for segmentation of noisy biomedical images; application in segmentation of pelvic X-ray images

    PubMed Central

    Smith, Rebecca; Najarian, Kayvan; Ward, Kevin

    2009-01-01

    Background Traumatic pelvic injuries are often associated with severe, life-threatening hemorrhage, and immediate medical treatment is therefore vital. However, patient prognosis depends heavily on the type, location and severity of the bone fracture, and the complexity of the pelvic structure presents diagnostic challenges. Automated fracture detection from initial patient X-ray images can assist physicians in rapid diagnosis and treatment, and a first and crucial step of such a method is to segment key bone structures within the pelvis; these structures can then be analyzed for specific fracture characteristics. Active Shape Model has been applied for this task in other bone structures but requires manual initialization by the user. This paper describes a algorithm for automatic initialization and segmentation of key pelvic structures - the iliac crests, pelvic ring, left and right pubis and femurs - using a hierarchical approach that combines directed Hough transform and Active Shape Models. Results Performance of the automated algorithm is compared with results obtained via manual initialization. An error measures is calculated based on the shapes detected with each method and the gold standard shapes. ANOVA results on these error measures show that the automated algorithm performs at least as well as the manual method. Visual inspection by two radiologists and one trauma surgeon also indicates generally accurate performance. Conclusion The hierarchical algorithm described in this paper automatically detects and segments key structures from pelvic X-rays. Unlike various other x-ray segmentation methods, it does not require manual initialization or input. Moreover, it handles the inconsistencies between x-ray images in a clinical environment and performs successfully in the presence of fracture. This method and the segmentation results provide a valuable base for future work in fracture detection. PMID:19891796

  6. Visual saliency-based active learning for prostate magnetic resonance imaging segmentation.

    PubMed

    Mahapatra, Dwarikanath; Buhmann, Joachim M

    2016-01-01

    We propose an active learning (AL) approach for prostate segmentation from magnetic resonance images. Our label query strategy is inspired from the principles of visual saliency that have similar considerations for choosing the most salient region. These similarities are encoded in a graph using classification maps and low-level features. Random walks are used to identify the most informative node, which is equivalent to the label query sample in AL. To reduce computation time, a volume of interest (VOI) is identified and all subsequent analysis, such as probability map generation using semisupervised random forest classifiers and label query, is restricted to this VOI. The negative log-likelihood of the probability maps serves as the penalty cost in a second-order Markov random field cost function, which is optimized using graph cuts for prostate segmentation. Experimental results on the Medical Image Computing and Computer Assisted Intervention (MICCAI) 2012 prostate segmentation challenge show the superior performance of our approach to conventional methods using fully supervised learning. PMID:26958579

  7. A framework of vertebra segmentation using the active shape model-based approach.

    PubMed

    Benjelloun, Mohammed; Mahmoudi, Saïd; Lecron, Fabian

    2011-01-01

    We propose a medical image segmentation approach based on the Active Shape Model theory. We apply this method for cervical vertebra detection. The main advantage of this approach is the application of a statistical model created after a training stage. Thus, the knowledge and interaction of the domain expert intervene in this approach. Our application allows the use of two different models, that is, a global one (with several vertebrae) and a local one (with a single vertebra). Two modes of segmentation are also proposed: manual and semiautomatic. For the manual mode, only two points are selected by the user on a given image. The first point needs to be close to the lower anterior corner of the last vertebra and the second near the upper anterior corner of the first vertebra. These two points are required to initialize the segmentation process. We propose to use the Harris corner detector combined with three successive filters to carry out the semiautomatic process. The results obtained on a large set of X-ray images are very promising. PMID:21826134

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. Interactive segmentation of abdominal aortic aneurysms in CTA images.

    PubMed

    de Bruijne, Marleen; van Ginneken, Bram; Viergever, Max A; Niessen, Wiro J

    2004-06-01

    A model-based approach to interactive segmentation of abdominal aortic aneurysms from CTA data is presented. After manual delineation of the aneurysm sac in the first slice, the method automatically detects the contour in subsequent slices, using the result from the previous slice as a reference. If an obtained contour is not sufficiently accurate, the user can intervene and provide an additional manual reference contour. The method is inspired by the active shape model (ASM) segmentation scheme (), in which a statistical shape model, derived from corresponding landmark points in manually labeled training images, is fitted to the image in an iterative manner. In our method, a shape model of the contours in two adjacent image slices is progressively fitted to the entire volume. The contour obtained in one slice thus constrains the possible shapes in the next slice. The optimal fit is determined on the basis of multi-resolution gray level models constructed from gray value patches sampled around each landmark. We propose to use the similarity of adjacent image slices for this gray level model, and compare these to single-slice features that are more generally used with ASM. The performance of various image features is evaluated in leave-one-out experiments on 23 data sets. Features that use the similarity of adjacent image slices outperform measures based on single-slice features in all cases. The average number of slices in our datasets is 51, while on average eight manual initializations are required, which decreases operator segmentation time by a factor of 6. PMID:15063862

  13. 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.

  14. Person detection in hyperspectral images via skin segmentation using an active learning approach

    NASA Astrophysics Data System (ADS)

    Marqués, Ion; Graña, Manuel; Sanchez, Stephanie M.; Alkhatib, Mohammed Q.; Velez-Reyes, Miguel

    2015-05-01

    Human skin detection is a computer vision problem that has been widely researched in color images. In this article we deal with this task as an interactive segmentation problem in hyperspectral outdoor images. We have focused on the problem of skin identification in hyperspectral cameras allowing a fine sampling of the light spectrum, so that the information gathered at each pixel is a high dimensional vector. The problem is treated as a classification problem, where we make use of active learning strategies to provide an interactive robust solution reaching high accuracy in a short training/testing cycle.

  15. 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.

  16. 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.

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

    PubMed Central

    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. PMID:24701202

  18. A segmental pattern of alkaline phosphatase activity within the notochord coincides with the initial formation of the vertebral bodies

    PubMed Central

    Sindre, Grotmol; Kari, Nordvik; Harald, Kryvi; Geir, K Totland

    2005-01-01

    This study shows that segmental expression of alkaline phosphatase (ALP) activity by the notochord of the Atlantic salmon (Salmo salar L.) coincides with the initial mineralization of the vertebral body (chordacentrum), and precedes ALP expression by presumed somite-derived cells external to the notochordal sheath. The early expression of ALP indicates that the notochord plays an instructive role in the segmental patterning of the vertebral column. The chordacentra form segmentally as mineralized rings within the notochordal sheath, and ALP activity spreads within the chordoblast layer from ventral to dorsal, displaying the same progression and spatial distribution as the mineralization process. No ALP activity was observed in sclerotomal mesenchyme surrounding the notochordal sheath during initial formation of the chordacentra. Our results support previous findings indicating that the chordoblasts initiate a segmental differentiation of the notochordal sheath into chordacentra and intervertebral regions. PMID:15857363

  19. Brain networks supporting perceptual grouping and contour selection

    PubMed Central

    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. PMID:24772096

  20. 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

  1. 3-D segmentation of human sternum in lung MDCT images.

    PubMed

    Pazokifard, Banafsheh; Sowmya, Arcot

    2013-01-01

    A fully automatic novel algorithm is presented for accurate 3-D segmentation of the human sternum in lung multi detector computed tomography (MDCT) images. The segmentation result is refined by employing active contours to remove calcified costal cartilage that is attached to the sternum. For each dataset, costal notches (sternocostal joints) are localized in 3-D by using a sternum mask and positions of the costal notches on it as reference. The proposed algorithm for sternum segmentation was tested on 16 complete lung MDCT datasets and comparison of the segmentation results to the reference delineation provided by a radiologist, shows high sensitivity (92.49%) and specificity (99.51%) and small mean distance (dmean=1.07 mm). Total average of the Euclidean distance error for costal notches positioning in 3-D is 4.2 mm. PMID:24110446

  2. 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.

  3. A contour-line color layer separation algorithm based on fuzzy clustering and region growing

    NASA Astrophysics Data System (ADS)

    Liu, Tiange; Miao, Qiguang; Xu, Pengfei; Tong, Yubing; Song, Jianfeng; Xia, Ge; Yang, Yun; Zhai, Xiaojie

    2016-03-01

    The color layers of contour-lines separated from scanned topographic map are the basis of contour-line extraction, but it is difficult to separate them well due to the color aliasing and mixed color problems. This paper will focus us on contour-line color layer separation and presents a novel approach for it based on fuzzy clustering and Single-prototype Region Growing for Contour-line Layer (SRGCL). The purpose of this paper is to provide a solution for processing scanned topographic maps on which contour-lines are abundant and densely distributed, for example, in the condition similar to hilly areas and mountainous regions, the contour-lines always occupy the largest proportion in linear features and the contour-line separation is the most difficult task. The proposed approach includes steps as follows. First step, line features are extracted from the map to reduce the interference from area features in fuzzy clustering. Second step, fuzzy clustering algorithm is employed to obtain membership matrix of pixels in the line map. Third step, based on the membership matrix, we obtain the most-similar prototype and the second-similar prototype of each pixel as the indicators of the pixel in SRGCL. The spatial relationship and the fuzzy similarity of color features are used in SRGCL to overcome the inaccurate classification of ambiguous pixels. The procedure focusing on single contour-line layer will improve the accuracy of contour-line segmentation result of SRGCL relative to general segmentation methods. We verified the algorithm on several USGS historical maps, the experimental results show that our algorithm produces contour-line color layers with good continuity and few noises, which verifies the improvement in contour-line color layer separation of our algorithm relative to two general segmentation methods.

  4. 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.

  5. Drosophila Hox and Sex-Determination Genes Control Segment Elimination through EGFR and extramacrochetae Activity

    PubMed Central

    Foronda, David; Martín, Paloma; Sánchez-Herrero, Ernesto

    2012-01-01

    The formation or suppression of particular structures is a major change occurring in development and evolution. One example of such change is the absence of the seventh abdominal segment (A7) in Drosophila males. We show here that there is a down-regulation of EGFR activity and fewer histoblasts in the male A7 in early pupae. If this activity is elevated, cell number increases and a small segment develops in the adult. At later pupal stages, the remaining precursors of the A7 are extruded under the epithelium. This extrusion requires the up-regulation of the HLH protein Extramacrochetae and correlates with high levels of spaghetti-squash, the gene encoding the regulatory light chain of the non-muscle myosin II. The Hox gene Abdominal-B controls both the down-regulation of spitz, a ligand of the EGFR pathway, and the up-regulation of extramacrochetae, and also regulates the transcription of the sex-determining gene doublesex. The male Doublesex protein, in turn, controls extramacrochetae and spaghetti-squash expression. In females, the EGFR pathway is also down-regulated in the A7 but extramacrochetae and spaghetti-squash are not up-regulated and extrusion of precursor cells is almost absent. Our results show the complex orchestration of cellular and genetic events that lead to this important sexually dimorphic character change. PMID:22912593

  6. Drosophila Hox and sex-determination genes control segment elimination through EGFR and extramacrochetae activity.

    PubMed

    Foronda, David; Martín, Paloma; Sánchez-Herrero, Ernesto

    2012-01-01

    The formation or suppression of particular structures is a major change occurring in development and evolution. One example of such change is the absence of the seventh abdominal segment (A7) in Drosophila males. We show here that there is a down-regulation of EGFR activity and fewer histoblasts in the male A7 in early pupae. If this activity is elevated, cell number increases and a small segment develops in the adult. At later pupal stages, the remaining precursors of the A7 are extruded under the epithelium. This extrusion requires the up-regulation of the HLH protein Extramacrochetae and correlates with high levels of spaghetti-squash, the gene encoding the regulatory light chain of the non-muscle myosin II. The Hox gene Abdominal-B controls both the down-regulation of spitz, a ligand of the EGFR pathway, and the up-regulation of extramacrochetae, and also regulates the transcription of the sex-determining gene doublesex. The male Doublesex protein, in turn, controls extramacrochetae and spaghetti-squash expression. In females, the EGFR pathway is also down-regulated in the A7 but extramacrochetae and spaghetti-squash are not up-regulated and extrusion of precursor cells is almost absent. Our results show the complex orchestration of cellular and genetic events that lead to this important sexually dimorphic character change. PMID:22912593

  7. Fully automated liver segmentation from SPIR image series.

    PubMed

    Göçeri, Evgin; Gürcan, Metin N; Dicle, Oğuz

    2014-10-01

    Accurate liver segmentation is an important component of surgery planning for liver transplantation, which enables patients with liver disease a chance to survive. Spectral pre-saturation inversion recovery (SPIR) image sequences are useful for liver vessel segmentation because vascular structures in the liver are clearly visible in these sequences. Although level-set based segmentation techniques are frequently used in liver segmentation due to their flexibility to adapt to different problems by incorporating prior knowledge, the need to initialize the contours on each slice is a common drawback of such techniques. In this paper, we present a fully automated variational level set approach for liver segmentation from SPIR image sequences. Our approach is designed to be efficient while achieving high accuracy. The efficiency is achieved by (1) automatically defining an initial contour for each slice, and (2) automatically computing weight values of each term in the applied energy functional at each iteration during evolution. Automated detection and exclusion of spurious structures (e.g. cysts and other bright white regions on the skin) in the pre-processing stage increases the accuracy and robustness. We also present a novel approach to reduce computational cost by employing binary regularization of level set function. A signed pressure force function controls the evolution of the active contour. The method was applied to ten data sets. In each image, the performance of the algorithm was measured using the receiver operating characteristics method in terms of accuracy, sensitivity and specificity. The accuracy of the proposed method was 96%. Quantitative analyses of results indicate that the proposed method can accurately, efficiently and consistently segment liver images. PMID:25192606

  8. 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

  9. 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.

  10. 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.

  11. Active graph matching for automatic joint segmentation and annotation of C. elegans.

    PubMed

    Kainmueller, Dagmar; Jug, Florian; Rother, Carsten; Myers, Gene

    2014-01-01

    In this work we present a novel technique we term active graph matching, which integrates the popular active shape model into a sparse graph matching problem. This way we are able to combine the benefits of a global, statistical deformation model with the benefits of a local deformation model in form of a second-order random field. We present a new iterative energy minimization technique which achieves empirically good results. This enables us to exceed state-of-the art results for the task of annotating nuclei in 3D microscopic images of C. elegans. Furthermore with the help of the generalized Hough transform we are able to jointly segment and annotate a large set of nuclei in a fully automatic fashion for the first time. PMID:25333104

  12. 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

  13. 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.

  14. Automated medical image segmentation techniques

    PubMed Central

    Sharma, Neeraj; Aggarwal, Lalit M.

    2010-01-01

    Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT) and Magnetic resonance (MR) imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images. PMID:20177565

  15. Diaphragm dome surface segmentation in CT data sets: a 3D active appearance model approach

    NASA Astrophysics Data System (ADS)

    Beichel, Reinhard; Gotschuli, Georg; Sorantin, Erich; Leberl, Franz W.; Sonka, Milan

    2002-05-01

    Knowledge about the location of the diaphragm dome surface, which separates the lungs and the heart from the abdominal cavity, is of vital importance for applications like automated segmentation of adjacent organs (e.g., liver) or functional analysis of the respiratory cycle. We present a new 3D Active Appearance Model (AAM) approach to segmentation of the top layer of the diaphragm dome. The 3D AAM consists of three parts: a 2D closed curve (reference curve), an elevation image and texture layers. The first two parts combined represent 3D shape information and the third part image intensity of the diaphragm dome and the surrounding layers. Differences in height between dome voxels and a reference plane are stored in the elevation image. The reference curve is generated by a parallel projection of the diaphragm dome outline in the axial direction. Landmark point placement is only done on the (2D) reference curve, which can be seen as the bounding curve of the elevation image. Matching is based on a gradient-descent optimization process and uses image intensity appearance around the actual dome shape. Results achieved in 60 computer generated phantom data sets show a high degree of accuracy (positioning error -0.07+/-1.29 mm). Validation using real CT data sets yielded a positioning error of -0.16+/-2.95 mm. Additional training and testing on in-vivo CT image data is ongoing.

  16. 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.

  17. Automated 3-D Segmentation of Lungs With Lung Cancer in CT Data Using a Novel Robust Active Shape Model Approach

    PubMed Central

    Sun, Shanhui; Bauer, Christian; Beichel, Reinhard

    2013-01-01

    Segmentation of lungs with (large) lung cancer regions is a nontrivial problem. We present a new fully automated approach for segmentation of lungs with such high-density pathologies. Our method consists of two main processing steps. First, a novel robust active shape model (RASM) matching method is utilized to roughly segment the outline of the lungs. The initial position of the RASM is found by means of a rib cage detection method. Second, an optimal surface finding approach is utilized to further adapt the initial segmentation result to the lung. Left and right lungs are segmented individually. An evaluation on 30 data sets with 40 abnormal (lung cancer) and 20 normal left/right lungs resulted in an average Dice coefficient of 0.975 ± 0.006 and a mean absolute surface distance error of 0.84 ± 0.23 mm, respectively. Experiments on the same 30 data sets showed that our methods delivered statistically significant better segmentation results, compared to two commercially available lung segmentation approaches. In addition, our RASM approach is generally applicable and suitable for large shape models. PMID:21997248

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. Large segmented UV-optical space telescope using a Hybrid Sensor Active Control (HSAC) architecture

    NASA Astrophysics Data System (ADS)

    Feinberg, Lee D.; Dean, Bruce; Hyde, Tupper; Oegerle, Bill; Bolcar, Matthew R.; Smith, J. Scott

    2009-08-01

    Future large UV-optical space telescopes offer new and exciting windows of scientific parameter space. These telescopes can be placed at L2 and borrow heavily from the James Webb Space Telescope (JWST) heritage. For example, they can have similar deployment schemes, hexagonal mirrors, and use Wavefront Sensing and Control (WFSC) technologies developed for JWST. However, a UV-optical telescope requires a 4x improvement in wavefront quality over JWST to be diffraction-limited at 500 nm. Achieving this tolerance would be difficult using a passive thermal architecture such as the one employed on JWST. To solve this problem, our team has developed a novel Hybrid Sensor Active Control (HSAC) architecture that provides a cost effective approach to building a segmented UV-optical space telescope. In this paper, we show the application of this architecture to the ST-2020 mission concept and summarize the technology development requirements.

  5. 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.

  6. Evaluation of stopping criteria for level set segmentation of breast masses in contrast-enhanced dedicated breast CT

    NASA Astrophysics Data System (ADS)

    Kuo, H.; Giger, M. L.; Reiser, I.; Boone, J. M.; Lindfors, K. K.; Yang, K.; Edwards, A.

    2012-03-01

    Dedicated breast CT (bCT) is an emerging technology that produces 3D images of the breast, thus allowing radiologists to detect and evaluate breast lesions in 3D. However, assessing potential cancers in the bCT volume can prove time consuming and difficult. Thus, we are developing automated 3D lesion segmentation methods to aid in the interpretation of bCT images. Based on previous studies using a 3D radial-gradient index (RGI) method [1], we are investigating whether 3D active contour segmentation can be applied in 3D to capture additional details of the lesion margin. Our data set includes 40 contract-enhanced bCT scans. Based on a radiologist-marked lesion center of each mass, an initial RGI contour is obtained that serves as the input to an active contour segmentation method. In this study, active contour level set segmentation, an iterative segmentation technique, is extended to 3D. Three stopping criteria are compared, based on 1) the change of volume (ΔV/V), 2) the mean value of the increased volume at each iteratin (dμ/dt), and 3) the changing rate of intensity inside and outside the lesion (Δvw). Lesion segmentation was evaluated by determining the overlap ratio between computer-determined segmentations and manually-drawn lesion outlines. For a given lesion, the overlap ratio was averaged across coronal, sagittal, and axial planes. The average overlap ratios for the three stopping criteria were found to be 0.66 (ΔV/V), 0.68 (dμ/dt), 0.69 (Δvw).

  7. 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.

  8. 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.

  9. Lessons learned with the Active Phasing Experiment: comparison of four optical phasing sensors on a segmented Very Large Telescope

    NASA Astrophysics Data System (ADS)

    Gonte, F.; Surdej, I.

    The adaptive optics capabilities are strongly limited by the quality of the phasing of the primary mirror of the extremely large telescope. Up to date, the Keck telescopes are the only segmented telescope phased with a quality enabling the application of adaptive optics. The Active Phasing Experiment has been installed at the Namyth focus of the Very Large Telescope Melipal during the last 6 months. Its purpose is to understand and compare different technological concepts for an optical phasing sensor dedicated to the European Extremely Large Telescope. The pupil of the telescope is segmented in 61 hexagonal segments by projecting it on an Active Segmented Mirror. The ASM is controlled by a dual wavenlength interferometer made by Fogale Nanotech with a nanometric precision. The segmented pupil is distributed in parallel to four optical phasing sensors. They are a pyramid sensor, a curvature sensor, a phase filtering sensor and a ShackHartmann sensor. They have been developed respectively by Istituto Nazionale di Astrofisica in Florenze, Instituto Astrofisica Canarias in Tenerife, Laboratoire d'Astrophysique de Marseille and ESO. The global behaviour of the optical phasing sensors will be described and preliminary results of the Active Phasing Experiments obtained on sky will be explained. The extrapolation of the results to the EELT and the potential consequences for the adaptive optics will be given. The Active Phasing Experiment has been financed by the European Union and the European Southern Observatory via the Sixth European Union Framework Program for Research and Technological Development under the contract number 011863.

  10. 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.

  11. Using Lateral Coupled Snakes for Modeling the Contours of Worms

    NASA Astrophysics Data System (ADS)

    Wang, Qing; Ronneberger, Olaf; Schulze, Ekkehard; Baumeister, Ralf; Burkhardt, Hans

    A model called lateral coupled snakes is proposed to describe the contours of moving C. elegans worms on 2D images with high accuracy. The model comprises two curves with point correspondence between them. The line linking a corresponding pair is approximately perpendicular to the curves at the two points, which is ensured by shear restoring forces. Experimental proofs reveal that the model is a promising tool for locating and segmenting worms or objects with similar shapes.

  12. 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)

  13. Ocular gene transfer of active TGF-beta induces changes in anterior segment morphology and elevated IOP in rats.

    PubMed

    Robertson, Jennifer V; Golesic, Elizabeth; Gauldie, Jack; West-Mays, Judith A

    2010-01-01

    Purpose. Transforming growth factor beta (TGF-beta) is known to play a crucial role in wound healing and fibrotic tissue remodeling. A large body of evidence suggests a role for this cytokine in the pathogenesis of glaucoma; however, the mechanisms by which it affects anterior segment morphology are not well understood. Therefore, the purpose of this study was to examine the effects of TGF-beta overexpression on anterior segment morphology and subsequent effects on intraocular pressure. Methods. Adenoviral gene transfer was used to deliver active TGF-beta1 to the rat eye. Measurements of intraocular pressure were taken with a tonometer on days 0, 14, 21, and 29. Histologic analysis was undertaken to examine anterior segment morphology, and markers of matrix deposition and fibrosis were used. Results. Gene transfer of TGF-beta in the anterior segment resulted in the formation of peripheral anterior synechiae (PAS), which consisted of a fibroproliferative region of corneal endothelial cells, matrix accumulation, and decrease in trabecular meshwork expression of alpha-smooth muscle actin. These features were accompanied by ocular hypertension. Conclusions. Gene transfer of TGF-beta into the anterior segment induces aberrant PAS associated with the transition of corneal endothelial cells and subsequent matrix deposition. These features are highly reminiscent of human iridocorneal endothelial (ICE) syndrome. Gene transfer of TGF-beta can, therefore, be used to induce anatomic changes in the anterior segment in a rodent model that result in ocular hypertension. PMID:19696167

  14. 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

  15. Design and evaluation of a new automated method for the segmentation and characterization of masses on ultrasound images

    NASA Astrophysics Data System (ADS)

    Cui, Jing; Sahiner, Berkman; Chan, Heang-Ping; Nees, Alexis; Paramagul, Chintana; Hadjiiski, Lubomir M.; Zhou, Chuan; Shi, Jiazheng

    2008-03-01

    Segmentation of masses is the first step in most computer-aided diagnosis (CAD) systems for characterization of breast masses as malignant or benign. In this study, we designed an automated method for segmentation of masses on ultrasound (US) images. The method automatically estimated an initial contour based on a manually-identified point approximately at the mass center. A two-stage active contour (AC) method iteratively refined the initial contour and performed self-examination and correction on the segmentation result. To evaluate our method, we compared it with manual segmentation by an experienced radiologists (R1) on a data set of 226 US images containing biopsy-proven masses from 121 patients (44 malignant and 77 benign). Four performance measures were used to evaluate the segmentation accuracy; two measures were related to the overlap between the computer and radiologist segmentation, and two were related to the area difference between the two segmentation results. To compare the difference between the segmentation results by the computer and R1 to inter-observer variation, a second radiologist (R2) also manually segmented all masses. The two overlap measures between the segmentation results by the computer and R1 were 0.87+ 0.16 and 0.73+ 0.17 respectively, indicating a high agreement. However, the segmentation results between two radiologists were more consistent. To evaluate the effect of the segmentation method on classification accuracy, three feature spaces were formed by extracting texture, width-to-height, and posterior shadowing features using the computer segmentation, R1's manual segmentation, and R2's manual segmentation. A linear discriminant analysis classifier using stepwise feature selection was tested and trained by a leave-one-case-out method to characterize the masses as malignant or benign. For case-based classification, the area A z under the test receiver operating characteristic (ROC) curve was 0.90+/-0.03, 0.87+/-0.03 and 0

  16. 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.

  17. Spinal segment-specific transcutaneous stimulation differentially shapes activation pattern among motor pools in humans.

    PubMed

    Sayenko, Dimitry G; Atkinson, Darryn A; Dy, Christine J; Gurley, Katelyn M; Smith, Valerie L; Angeli, Claudia; Harkema, Susan J; Edgerton, V Reggie; Gerasimenko, Yury P

    2015-06-01

    Transcutaneous and epidural electrical spinal cord stimulation techniques are becoming more valuable as electrophysiological and clinical tools. Recently, we observed selective activation of proximal and distal motor pools during epidural spinal stimulation. In the present study, we hypothesized that the characteristics of recruitment curves obtained from leg muscles will reflect a relative preferential activation of proximal and distal motor pools based on their arrangement along the lumbosacral enlargement. The purpose was to describe the electrophysiological responses to transcutaneous stimulation in leg muscles innervated by motoneurons from different segmental levels. Stimulation delivered along the rostrocaudal axis of the lumbosacral enlargement in the supine position resulted in a selective topographical recruitment of proximal and distal leg muscles, as described by threshold intensity, slope of the recruitment curves, and plateau point intensity and magnitude. Relatively selective recruitment of proximal and distal motor pools can be titrated by optimizing the site and intensity level of stimulation to excite a given combination of motor pools. The slope of the recruitment of particular muscles allows characterization of the properties of afferents projecting to specific motoneuron pools, as well as to the type and size of the motoneurons. The location and intensity of transcutaneous spinal electrical stimulation are critical to target particular neural structures across different motor pools in investigation of specific neuromodulatory effects. Finally, the asymmetry in bilateral evoked potentials is inevitable and can be attributed to both anatomical and functional peculiarities of individual muscles or muscle groups. PMID:25814642

  18. 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

  19. 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.

  20. FIST: a fast interactive segmentation technique

    NASA Astrophysics Data System (ADS)

    Padfield, Dirk; Bhotika, Rahul; Natanzon, Alexander

    2015-03-01

    Radiologists are required to read thousands of patient images every day, and any tools that can improve their workflow to help them make efficient and accurate measurements is of great value. Such an interactive tool must be intuitive to use, and we have found that users are accustomed to clicking on the contour of the object for segmentation and would like the final segmentation to pass through these points. The tool must also be fast to enable real-time interactive feedback. To meet these needs, we present a segmentation workflow that enables an intuitive method for fast interactive segmentation of 2D and 3D objects. Given simple user clicks on the contour of an object in one 2D view, the algorithm generates foreground and background seeds and computes foreground and background distributions that are used to segment the object in 2D. It then propagates the information to the two orthogonal planes in a 3D volume and segments all three 2D views. The automated segmentation is automatically updated as the user continues to add points around the contour, and the algorithm is re-run using the total set of points. Based on the segmented objects in these three views, the algorithm then computes a 3D segmentation of the object. This process requires only limited user interaction to segment complex shapes and significantly improves the workflow of the user.

  1. 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.

  2. Gage for 3-d contours

    NASA Technical Reports Server (NTRS)

    Haynie, C. C.

    1980-01-01

    Simple gage, used with template, can help inspectors determine whether three-dimensional curved surface has correct contour. Gage was developed as aid in explosive forming of Space Shuttle emergency-escape hatch. For even greater accuracy, wedge can be made of metal and calibrated by indexing machine.

  3. 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.

  4. 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

  5. Measuring and Plotting Surface-Contour Deviations

    NASA Technical Reports Server (NTRS)

    Aragon, Lino A.; Shuck, Thomas; Crockett, Leroy K.

    1987-01-01

    Hand-held device measures deviation of contour of surface from desired contour and provides output to x-y plotter. Carriage on device rolled along track representing desired contour, while spring-loaded stylus on device deflects perpendicularly to track to follow surface. Operator moves carriage of contour-measuring device on beamlike track. Stylus on carriage traces contour of surface above it. Carriage of measuring device holds transducer measuring cross-track displacement of surface from desired contour, and multiple-turn potentiometer measuring position along track.

  6. Deformable membrane for the segmentation of cytological samples

    NASA Astrophysics Data System (ADS)

    Metzler, Volker H.; Bredno, Joerg; Lehmann, Thomas M.; Spitzer, Klaus

    1998-06-01

    In clinical cytology quantitative parameters have to be extracted from a large number of biological samples to obtain diagnostically relevant and reproducible information. Computer-assisted microscopy can provide methods that increase the quality and comparability of clinical studies by reducing the subjective influence of human operators on their results. In order to guarantee the correctness of extracted parameters automatic and reliable segmentation of the samples is required. For the detection of cytological objects a novel deformable membrane model is presented which is strictly based on macroscopical mechanics and statics. This is appropriate for modeling physiological membranes, because their shape is determined exclusively by mechanical forces. The self-driven membrane converges iteratively towards a stable state, where the contrary forces are in balance. However, active contours may not yield sufficient detection quality for acquisition of quantitative parameters. Therefore, after convergence a stochastic optimization process corrects the contour according to local graylevel information. This yields a contour that is well- adapted to the local graylevel structure. Additionally, for subsequent cytometric quantifications a local measure of confidence is provided for the contour. this can be used to enhance the robustness of the extracted parameters by incorporating the confidence factors in the quantification process. The method is applied to cytological and histological samples of different magnification.

  7. 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.

  8. 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.

  9. Automated segmentation and dose-volume analysis with DICOMautomaton

    NASA Astrophysics Data System (ADS)

    Clark, H.; Thomas, S.; Moiseenko, V.; Lee, R.; Gill, B.; Duzenli, C.; Wu, J.

    2014-03-01

    Purpose: Exploration of historical data for regional organ dose sensitivity is limited by the effort needed to (sub-)segment large numbers of contours. A system has been developed which can rapidly perform autonomous contour sub-segmentation and generic dose-volume computations, substantially reducing the effort required for exploratory analyses. Methods: A contour-centric approach is taken which enables lossless, reversible segmentation and dramatically reduces computation time compared with voxel-centric approaches. Segmentation can be specified on a per-contour, per-organ, or per-patient basis, and can be performed along either an embedded plane or in terms of the contour's bounds (e.g., split organ into fractional-volume/dose pieces along any 3D unit vector). More complex segmentation techniques are available. Anonymized data from 60 head-and-neck cancer patients were used to compare dose-volume computations with Varian's EclipseTM (Varian Medical Systems, Inc.). Results: Mean doses and Dose-volume-histograms computed agree strongly with Varian's EclipseTM. Contours which have been segmented can be injected back into patient data permanently and in a Digital Imaging and Communication in Medicine (DICOM)-conforming manner. Lossless segmentation persists across such injection, and remains fully reversible. Conclusions: DICOMautomaton allows researchers to rapidly, accurately, and autonomously segment large amounts of data into intricate structures suitable for analyses of regional organ dose sensitivity.

  10. Semi-automatic Segmentation for Prostate Interventions

    PubMed Central

    Mahdavi, S. Sara; Chng, Nick; Spadinger, Ingrid; Morris, William J.; Salcudean, Septimiu E.

    2011-01-01

    In this paper we report and characterize a semi-automatic prostate segmentation method for prostate brachytherapy. Based on anatomical evidence and requirements of the treatment procedure, a warped and tapered ellipsoid was found suitable as the a priori 3D shape of the prostate. By transforming the acquired endorectal transverse images of the prostate into ellipses, the shape fitting problem was cast into a convex problem which can be solved efficiently. The average whole gland error between volumes created from manual and semi-automatic contours from 21 patients was 6.63±0.9%. For use in brachytherapy treatment planning, the resulting contours were modified, if deemed necessary, by radiation oncologists prior to treatment. The average whole gland volume error between the volumes computed from semi-automatic contours and those computed from modified contours, from 40 patients, was 5.82±4.15%. The amount of bias in the physicians’ delineations when given an initial semi-automatic contour was measured by comparing the volume error between 10 prostate volumes computed from manual contours with those of modified contours. This error was found to be 7.25±0.39% for the whole gland. Automatic contouring reduced subjectivity, as evidenced by a decrease in segmentation inter- and intra-observer variability from 4.65% and 5.95% for manual segmentation to 3.04% and 3.48% for semi-automatic segmentation, respectively. We characterized the performance of the method relative to the reference obtained from manual segmentation by using a novel approach that divides the prostate region into nine sectors. We analyzed each sector independently as the requirements for segmentation accuracy depend on which region of the prostate is considered. The measured segmentation time is 14±1 seconds with an additional 32±14 seconds for initialization. By assuming 1–3 minutes for modification of the contours, if necessary, a total segmentation time of less than 4 minutes is required

  11. Micro-segmented flow and multisensor-technology for microbial activity profiling.

    PubMed

    Kürsten, Dana; Kothe, Erika; Wetzel, Katharina; Bergmann, Katja; Köhler, J Michael

    2014-01-01

    The combination of micro-segmented flow with miniaturized flow-through multisensor-technology has been utilized for metabolite profiling of soil bacteria. Series of sub-μl segments were generated containing soil sample slurry from historic copper mining sites and exposed to heavy metal salts of copper and nickel. Segments were examined for bacterial growth and spectral properties as well as for the effect of heavy metal-treatment after different incubation times. In order to evaluate microbial growth, extinction was recorded with 4 different spectral channels. Fluorescence was measured using a microflow-through fluorometer to detect both growth and production of fluorescent dyes or metabolites. The incidence of single segments with enhanced absorption in one of the spectral channels or enhanced fluorescence was scored to detect soil microorganisms with interesting properties for further screening. The study could show that the number of vegetated segments, the density of microorganisms in the segments after cultivation and the spectral response are different for separate soil samples and different metals. Thus, the highly parallelized and miniaturized segmented flow method is a promising tool for profiling of soil samples with regard to identifying micro-organisms with interesting profiles for secondary metabolite-production. PMID:25119668

  12. 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.

  13. Human mesenchymal stem cell behavior on segmented polyurethanes prepared with biologically active chain extenders.

    PubMed

    Kavanaugh, Taylor E; Clark, Amy Y; Chan-Chan, Lerma H; Ramírez-Saldaña, Maricela; Vargas-Coronado, Rossana F; Cervantes-Uc, José M; Hernández-Sánchez, Fernando; García, Andrés J; Cauich-Rodríguez, Juan V

    2016-02-01

    The development of elastomeric, bioresorbable and biocompatible segmented polyurethanes (SPUs) for use in tissue-engineering applications has attracted considerable interest because of the existing need of mechanically tunable scaffolds for regeneration of different tissues, but the incorporation of osteoinductive molecules into SPUs has been limited. In this study, SPUs were synthesized from poly (ε-caprolactone)diol, 4,4'-methylene bis(cyclohexyl isocyanate) using biologically active compounds such as ascorbic acid, L-glutamine, β-glycerol phosphate, and dexamethasone as chain extenders. Fourier transform infrared spectroscopy (FTIR) revealed the formation of both urethanes and urea linkages while differential scanning calorimetry, dynamic mechanical analysis, X-ray diffraction and mechanical testing showed that these polyurethanes were semi-crystalline polymers exhibiting high deformations. Cytocompatibility studies showed that only SPUs containing β-glycerol phosphate supported human mesenchymal stem cell adhesion, growth, and osteogenic differentiation, rendering them potentially suitable for bone tissue regeneration, whereas other SPUs failed to support either cell growth or osteogenic differentiation, or both. This study demonstrates that modification of SPUs with osteogenic compounds can lead to new cytocompatible polymers for regenerative medicine applications. PMID:26704555

  14. Fault barriers favor activation of backthrusts near segment ends of megathrust ruptures

    NASA Astrophysics Data System (ADS)

    Xu, S.; Fukuyama, E.; Ben-Zion, Y.; Ampuero, J. P.

    2013-12-01

    Increasing evidence indicates that backthrusts may become active during or after megathrust ruptures in subduction zones, such as in Chile and Sumatra areas (Melnick et al., 2012; Singh et al., 2011). Previous studies on relevant mechanisms mainly focused on the interaction between forethrusts and the megathrust. Here we aim to investigate through dynamic rupture simulations how backthrusts may be activated by megathrust ruptures in subduction zone environment. Assuming a single backthrust branch, our preliminary results show that the activation of backthrust is difficult if the megathrust rupture can easily pass through the fault junction, owing to a quickly established stress shadow zone in the wake of the megathrust rupture front. In contrast, if the megathrust rupture is arrested or delayed around the junction, a resultant backward stress lobe of the type discussed by Xu and Ben-Zion (2013) can load the backthrust over a considerable amount of time and facilitates rupture activation along the backthrust. A number of candidates can serve to arrest or delay megathrust ruptures, such as the velocity-strengthening frictional behavior and off-fault weak materials in the shallow portion of subduction zones, fault bend or ramp, and subducted seamount. Moreover, these features are also found capable of generating backthrusts during the long-term quasi-static process, which provide pre-existing weakness to be reactivated by later dynamic ruptures. Our results agree, from a different point of view, with the study based on the critical taper theory (Cubas et al., 2013) that an increase of friction towards the trench favors the activation of backthrusts near the up-dip limit of megathrust ruptures. The results highlight the role of fault geometric or strength heterogeneities in controlling the strain partitioning on and off the main fault plane. Accordingly, activated backthrusts may be treated as markers that reflect the limits of seismogenic zones, and thus may be used

  15. 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.

  16. 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

  17. Active shape models for a fully automated 3D segmentation of the liver--an evaluation on clinical data.

    PubMed

    Heimann, Tobias; Wolf, Ivo; Meinzer, Hans-Peter

    2006-01-01

    This paper presents an evaluation of the performance of a three-dimensional Active Shape Model (ASM) to segment the liver in 48 clinical CT scans. The employed shape model is built from 32 samples using an optimization approach based on the minimum description length (MDL). Three different gray-value appearance models (plain intensity, gradient and normalized gradient profiles) are created to guide the search. The employed segmentation techniques are ASM search with 10 and 30 modes of variation and a deformable model coupled to a shape model with 10 modes of variation. To assess the segmentation performance, the obtained results are compared to manual segmentations with four different measures (overlap, average distance, RMS distance and ratio of deviations larger 5mm). The only appearance model delivering usable results is the normalized gradient profile. The deformable model search achieves the best results, followed by the ASM search with 30 modes. Overall, statistical shape modeling delivers very promising results for a fully automated segmentation of the liver. PMID:17354754

  18. Prostate boundary segmentation from ultrasound images using 2D active shape models: optimisation and extension to 3D.

    PubMed

    Hodge, Adam C; Fenster, Aaron; Downey, Dónal B; Ladak, Hanif M

    2006-12-01

    Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm based on two-dimensional (2D) active shape models (ASM) for semi-automatic segmentation of the prostate boundary from ultrasound images. Optimisation of the 2D ASM for prostatic ultrasound was done first by examining ASM construction and image search parameters. Extension of the algorithm to three-dimensional (3D) segmentation was then done using rotational-based slicing. Evaluation of the 3D segmentation algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. Minimum description length landmark placement for ASM construction, and specific values for constraints and image search were found to be optimal. Evaluation of the algorithm versus gold standard boundaries found an average mean absolute distance of 1.09+/-0.49 mm, an average percent absolute volume difference of 3.28+/-3.16%, and a 5x speed increase versus manual segmentation. PMID:16930764

  19. 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.

  20. Application Of Moire Contour Fringes To Study Nycticebus Coucany

    NASA Astrophysics Data System (ADS)

    Ren-xiang, Zhang; Ming, Lu; Zu-yun, Lan; Wen-ji, Qu

    1984-12-01

    In this paper we have studied the moire contour fringes of the skull and femur knee joint of Nycticebus coucany and obtained the following results: 1. The skull's value K is very useful for comparative study with the different kinds of Primate. 2. The moire contour fringes of the tibia facies of knee joint is convex on one side while the other side is concave. 3. At the same condition the grade of the first moire contour fringe of connection on the femur knee joint between the two condyles and its angle β are smaller than Hylobates concolor leucongeuys. This study is significant, because: 1. The evolution of skull may be related with the increased value K. 2. The moire contour fringes of the Nycticebus coucany's tibia and femur knee joint have lower range of activity. 3. From the moire contour fringes of knee, the Nycticebus coucany and. Hylobates concolor leucongeuys are of one kind. But the moire contour Nycticebus of tibia is different form.

  1. New automatic liver segmentation and extraction method

    NASA Astrophysics Data System (ADS)

    Zhang, Pinzheng; Xu, Qinzheng; Wang, Zheng

    2007-12-01

    Liver segmentation is critical in designing and developing computer-assisted systems that have been used for liver disease diagnosis before surgery or transplantation. The purpose of this study is to develop a computerized system for extracting liver contours and reconstructing liver volume using contrast-enhanced hepatic CT images. The automatic liver segmentation method adopted the graph optimal algorithm with ratio contour as its salient measure. This new cost function encoded the Gestalt laws and synthesized the gap length, the liver region area, the length of the closed contour and the average curvature of the closed boundary. With the extracted liver contours, a promising system to exclude tissues outside the liver was developed. It promised to save time and simplify liver volume reconstruction by minimizing intervention operations. Some 3D-rendered reconstruction results were also created to demonstrate the final results of our system.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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. PMID:26956926

  8. Optical flow 3D segmentation and interpretation: a variational method with active curve evolution and level sets.

    PubMed

    Mitiche, Amar; Sekkati, Hicham

    2006-11-01

    This study investigates a variational, active curve evolution method for dense three-dimentional (3D) segmentation and interpretation of optical flow in an image sequence of a scene containing moving rigid objects viewed by a possibly moving camera. This method jointly performs 3D motion segmentation, 3D interpretation (recovery of 3D structure and motion), and optical flow estimation. The objective functional contains two data terms for each segmentation region, one based on the motion-only equation which relates the essential parameters of 3D rigid body motion to optical flow, and the other on the Horn and Schunck optical flow constraint. It also contains two regularization terms for each region, one for optical flow, the other for the region boundary. The necessary conditions for a minimum of the functional result in concurrent 3D-motion segmentation, by active curve evolution via level sets, and linear estimation of each region essential parameters and optical flow. Subsequently, the screw of 3D motion and regularized relative depth are recovered analytically for each region from the estimated essential parameters and optical flow. Examples are provided which verify the method and its implementation. PMID:17063686

  9. Multi-segment detector

    NASA Technical Reports Server (NTRS)

    George, Peter K. (Inventor)

    1978-01-01

    A plurality of stretcher detector segments are connected in series whereby detector signals generated when a bubble passes thereby are added together. Each of the stretcher detector segments is disposed an identical propagation distance away from passive replicators wherein bubbles are replicated from a propagation path and applied, simultaneously, to the stretcher detector segments. The stretcher detector segments are arranged to include both dummy and active portions thereof which are arranged to permit the geometry of both the dummy and active portions of the segment to be substantially matched.

  10. 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.

  11. Three-dimensional active shape model matching for left ventricle segmentation in cardiac CT

    NASA Astrophysics Data System (ADS)

    van Assen, Hans C.; van der Geest, Rob J.; Danilouchkine, Mikhail G.; Lamb, Hildo J.; Reiber, Johan H. C.; Lelieveldt, Boudewijn P. F.

    2003-05-01

    Manual quantitative analysis of cardiac left ventricular function using multi-slice CT is labor intensive because of the large datasets. We present an automatic, robust and intrinsically three-dimensional segmentation method for cardiac CT images, based on 3D Active Shape Models (ASMs). ASMs describe shape and shape variations over a population as a mean shape and a number of eigenvariations, which can be extracted by e.g. Principal Component Analysis (PCA). During the iterative ASM matching process, the shape deformation is restricted within statistically plausible constraints (+/-3σ). Our approach has two novel aspects: the 3D-ASM application to volume data of arbitrary planar orientation, and the application to image data from another modality than which was used to train the model, without the necessity of retraining it. The 3D-ASM was trained on MR data and quantitatively evaluated on 17 multi-slice cardiac CT data sets, with respect to calculated LV volume (blood pool plus myocardium) and endocardial volume. In all cases, model matching was convergent and final results showed a good model performance. Bland-Altman analysis however, showed that bloodpool volume was slightly underestimated and LV volume was slightly overestimated by the model. Nevertheless, these errors remain within clinically acceptable margins. Based on this evaluation, we conclude that our 3D-ASM combines robustness with clinically acceptable accuracy. Without retraining for cardiac CT, we could adapt a model trained on cardiac MR data sets for application in cardiac CT volumes, demonstrating the flexibility and feasibility of our matching approach. Causes for the systematic errors are edge detection, model constraints, or image data reconstruction. For all these categories, solutions are discussed.

  12. 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.

  13. 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.

  14. A geometric snake model for segmentation of medical imagery.

    PubMed

    Yezzi, A; Kichenassamy, S; Kumar, A; Olver, P; Tannenbaum, A

    1997-04-01

    In this note, we employ the new geometric active contour models formulated in [25] and [26] for edge detection and segmentation of magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound medical imagery. Our method is based on defining feature-based metrics on a given image which in turn leads to a novel snake paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. Thus, the snake is attracted very quickly and efficiently to the desired feature. PMID:9101329

  15. 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.

  16. AUTOMATED SKIN SEGMENTATION IN ULTRASONIC EVALUATION OF SKIN TOXICITY IN BREAST CANCER RADIOTHERAPY

    PubMed Central

    Gao, Yi; Tannenbaum, Allen; Chen, Hao; Torres, Mylin; Yoshida, Emi; Yang, Xiaofeng; Wang, Yuefeng; Curran, Walter; Liu, Tian

    2013-01-01

    Skin toxicity is the most common side effect of breast cancer radiotherapy and impairs the quality of life of many breast cancer survivors. We, along with other researchers, have recently found quantitative ultrasound to be effective as a skin toxicity assessment tool. Although more reliable than standard clinical evaluations (visual observation and palpation), the current procedure for ultrasound-based skin toxicity measurements requires manual delineation of the skin layers (i.e., epidermis-dermis and dermis-hypodermis interfaces) on each ultrasound B-mode image. Manual skin segmentation is time consuming and subjective. Moreover, radiation-induced skin injury may decrease image contrast between the dermis and hypodermis, which increases the difficulty of delineation. Therefore, we have developed an automatic skin segmentation tool (ASST) based on the active contour model with two significant modifications: (i) The proposed algorithm introduces a novel dual-curve scheme for the double skin layer extraction, as opposed to the original single active contour method. (ii) The proposed algorithm is based on a geometric contour framework as opposed to the previous parametric algorithm. This ASST algorithm was tested on a breast cancer image database of 730 ultrasound breast images (73 ultrasound studies of 23 patients). We compared skin segmentation results obtained with the ASST with manual contours performed by two physicians. The average percentage differences in skin thickness between the ASST measurement and that of each physician were less than 5% (4.8 ± 17.8% and −3.8 ± 21.1%, respectively). In summary, we have developed an automatic skin segmentation method that ensures objective assessment of radiation-induced changes in skin thickness. Our ultrasound technology offers a unique opportunity to quantify tissue injury in a more meaningful and reproducible manner than the subjective assessments currently employed in the clinic. PMID:23993172

  17. Pre-Processing Effect on the Accuracy of Event-Based Activity Segmentation and Classification through Inertial Sensors.

    PubMed

    Fida, Benish; Bernabucci, Ivan; Bibbo, Daniele; Conforto, Silvia; Schmid, Maurizio

    2015-01-01

    Inertial sensors are increasingly being used to recognize and classify physical activities in a variety of applications. For monitoring and fitness applications, it is crucial to develop methods able to segment each activity cycle, e.g., a gait cycle, so that the successive classification step may be more accurate. To increase detection accuracy, pre-processing is often used, with a concurrent increase in computational cost. In this paper, the effect of pre-processing operations on the detection and classification of locomotion activities was investigated, to check whether the presence of pre-processing significantly contributes to an increase in accuracy. The pre-processing stages evaluated in this study were inclination correction and de-noising. Level walking, step ascending, descending and running were monitored by using a shank-mounted inertial sensor. Raw and filtered segments, obtained from a modified version of a rule-based gait detection algorithm optimized for sequential processing, were processed to extract time and frequency-based features for physical activity classification through a support vector machine classifier. The proposed method accurately detected >99% gait cycles from raw data and produced >98% accuracy on these segmented gait cycles. Pre-processing did not substantially increase classification accuracy, thus highlighting the possibility of reducing the amount of pre-processing for real-time applications. PMID:26378544

  18. Pre-Processing Effect on the Accuracy of Event-Based Activity Segmentation and Classification through Inertial Sensors

    PubMed Central

    Fida, Benish; Bernabucci, Ivan; Bibbo, Daniele; Conforto, Silvia; Schmid, Maurizio

    2015-01-01

    Inertial sensors are increasingly being used to recognize and classify physical activities in a variety of applications. For monitoring and fitness applications, it is crucial to develop methods able to segment each activity cycle, e.g., a gait cycle, so that the successive classification step may be more accurate. To increase detection accuracy, pre-processing is often used, with a concurrent increase in computational cost. In this paper, the effect of pre-processing operations on the detection and classification of locomotion activities was investigated, to check whether the presence of pre-processing significantly contributes to an increase in accuracy. The pre-processing stages evaluated in this study were inclination correction and de-noising. Level walking, step ascending, descending and running were monitored by using a shank-mounted inertial sensor. Raw and filtered segments, obtained from a modified version of a rule-based gait detection algorithm optimized for sequential processing, were processed to extract time and frequency-based features for physical activity classification through a support vector machine classifier. The proposed method accurately detected >99% gait cycles from raw data and produced >98% accuracy on these segmented gait cycles. Pre-processing did not substantially increase classification accuracy, thus highlighting the possibility of reducing the amount of pre-processing for real-time applications. PMID:26378544

  19. 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

  20. Plasma Characterization of Hall Thruster with Active and Passive Segmented Electrodes

    SciTech Connect

    Raitses, Y.; Staack, D.; Fisch, N.J.

    2002-09-04

    Non-emissive electrodes and ceramic spacers placed along the Hall thruster channel are shown to affect the plasma potential distribution and the thruster operation. These effects are associated with physical properties of the electrode material and depend on the electrode configuration, geometry and the magnetic field distribution. An emissive segmented electrode was able to maintain thruster operation by supplying an additional electron flux to sustain the plasma discharge between the anode and cathode neutralizer. These results indicate the possibility of new configurations for segmented electrode Hall thruster.

  1. Graph-based active learning of agglomeration (GALA): a Python library to segment 2D and 3D neuroimages

    PubMed Central

    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

  2. Multi-segment and multi-ply overlapping process of multi coupled activities based on valid information evolution

    NASA Astrophysics Data System (ADS)

    Wang, Zhiliang; Wang, Yunxia; Qiu, Shenghai

    2013-01-01

    Complex product development will inevitably face the design planning of the multi-coupled activities, and overlapping these activities could potentially reduce product development time, but there is a risk of the additional cost. Although the downstream task information dependence to the upstream task is already considered in the current researches, but the design process overall iteration caused by the information interdependence between activities is hardly discussed; especially the impact on the design process' overall iteration from the valid information accumulation process. Secondly, most studies only focus on the single overlapping process of two activities, rarely take multi-segment and multi-ply overlapping process of multi coupled activities into account; especially the inherent link between product development time and cost which originates from the overlapping process of multi coupled activities. For the purpose of solving the above problems, as to the insufficiency of the accumulated valid information in overlapping process, the function of the valid information evolution (VIE) degree is constructed. Stochastic process theory is used to describe the design information exchange and the valid information accumulation in the overlapping segment, and then the planning models of the single overlapping segment are built. On these bases, by analyzing overlapping processes and overlapping features of multi-coupling activities, multi-segment and multi-ply overlapping planning models are built; by sorting overlapping processes and analyzing the construction of these planning models, two conclusions are obtained: (1) As to multi-segment and multi-ply overlapping of multi coupled activities, the total decrement of the task set development time is the sum of the time decrement caused by basic overlapping segments, and minus the sum of the time increment caused by multiple overlapping segments; (2) the total increment of development cost is the sum of the cost

  3. 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.

  4. 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

  5. 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

  6. Analysis of multitemporal laserscanned DTMs of an active landslide (Doren, Western Austria) using a robust planefitting segmentation

    NASA Astrophysics Data System (ADS)

    Koma, Zs.; Pocsai, A.; Székely, B.; Dorninger, P.; Zámolyi, A.; Roncat, A.

    2012-04-01

    Structural geomorphometric analysis of high-resolution laser scanned DTMs is a straightforward method to study microtopographic components of dynamically forming landscapes, and thus areas affected by mass movements. However, results for multitemporal DTMs may turn out to be difficult to evaluate. In our approach, a robust plane fitting algorithm is used to create various segmentations to filtered lidar point cloud (ground surface points) by applying different sets of parameters. The resulting sets of planes are analyzed in terms of their geologic meaning and compared in order to detect changes. Our study area, the Doren landslide (Bregenzerwald, Vorarlberg, Western Austria), an actively forming landslide developed in molasse sediments has been measured several times by laser scanning (lidar). These DTMs form the input to our procedure. The DTMs are analyzed by the segmentation algorithm, using varying parameter sets (i.e. number of minimum points, standard deviation, point-to-plain distance). The segmented results are checked for indications of geological structures as well as for features belonging to the moving material of the landslide. Finally the segments of the different years are compared. Results show that patterns composed of segments of steep and less steep valley sides can be correlated with the tectonic and lithological setting of the study area. Furthermore some narrow linear or curvilinear zones appear that can be related to the outlines of some small internal mass movements. Interestingly, the various years show sometimes similar patterns despite the continuous displacement of the sliding material. The project has been supported by the Austrian Academy of Sciences (ÖAW) in the framework of the project "Geophysik der Erdkruste".

  7. Changes in time-segment specific physical activity between ages 10 and 14 years: A longitudinal observational study

    PubMed Central

    Brooke, Hannah L.; Atkin, Andrew J.; Corder, Kirsten; Ekelund, Ulf; van Sluijs, Esther M.F.

    2016-01-01

    Objectives Describe (1) time-segment specific changes in physical activity (PA) into adolescence, (2) differences in change in PA between specific time-segments (weekdays–weekends, in-school–out-of-school, out-of-school–weekends, lesson-time–lunch-time), and (3) associations of change in time-segment specific with overall PA. Design Longitudinal observational study (4-year follow-up). Methods Children from the SPEEDY study (n = 769, 42% boys) had PA measured by accelerometer for at least three days at ages 10.2 ± 0.3, 11.2 ± 0.3 and 14.3 ± 0.3 years. Changes in moderate-to-vigorous PA (ΔMVPA, minutes ≥2000 counts/minute [cpm]) and total PA (ΔTPA, average cpm) during weekdays, weekends, in-school, out-of-school, lesson-times and lunch-times, were tested using three level (age, individual, school) mixed-effects linear regression. Differences in ΔMVPA/ΔTPA between time-segments were tested using time-segment × age interaction terms. Associations of four-year time-segment specific ΔMVPA/ΔTPA with four-year overall ΔMVPA/ΔTPA were tested using two level (time-segment specific ΔMVPA/ΔTPA, school) mixed-effects linear regression. Results MVPA and TPA declined in all time-segments, except lesson-time MVPA. Annual ΔMVPA and, for boys only, ΔTPA was greater on weekends than weekdays (beta ± SE for interaction term: boys, −3.53 ± 0.83 min, −29.64 ± 7.64 cpm; girls, −2.20 ± 0.64 min) and out-of-school (boys, −4.36 ± 0.79 min, −19.36 ± 8.46 cpm; girls, −2.44 ± 0.63 min). ΔMVPA and ΔTPA during lunch-time was greater than during lesson-time (boys, −0.96 ± 0.20 min, −36.43 ± 6.55 cpm; girls, −0.90 ± 0.13 min, −38.72 ± 4.40 cpm). ΔTPA was greater out-of-school than in-school (boys, −19.89 ± 6.71 cpm; girls, −18.46 ± 6.51 cpm). For all time-segments, four-year ΔMVPA/ΔTPA was positively associated with four-year overall ΔMVPA/ΔTPA (all p < 0.042), except for girl

  8. Brightness alteration with interweaving contours

    PubMed Central

    Roncato, Sergio

    2012-01-01

    Chromatic induction is observed whenever the perceived colour of a target surface shifts towards the hue of a neighbouring surface. Some vivid manifestations may be seen in a white background where thin coloured lines have been drawn (assimilation) or when lines of different colours are collinear (neon effect) or adjacent (watercolour) to each other. This study examines a particular colour induction that manifests in concomitance with an opposite effect of colour saturation (or anti-spread). The two phenomena can be observed when a repetitive pattern is drawn in which outline thin contours intercept wider contours or surfaces, colour spreading appear to fill the surface occupied by surfaces or thick lines whereas the background traversed by thin lines is seen as brighter or filled of a saturated white. These phenomena were first observed by Bozzi (1975) and Kanizsa (1979) in figural conditions that did not allow them to document their conjunction. Here we illustrate various manifestations of this twofold phenomenon and compare its effects with the known effects of brightness and colour induction. Some conjectures on the nature of these effects are discussed. PMID:23483806

  9. 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.

  10. 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.

  11. Segmented Ge detector rejection of internal beta activity produced by neutron irradiation

    NASA Technical Reports Server (NTRS)

    Varnell, L. S.; Callas, J. L.; Mahoney, W. A.; Pehl, R. H.; Landis, D. A.

    1991-01-01

    Future Ge spectrometers flown in space to observe cosmic gamma-ray sources will incorporate segmented detectors to reduce the background from radioactivity produced by energetic particle reactions. To demonstrate the effectiveness of a segmented Ge detector in rejecting background events due to the beta decay of internal radioactivity, a laboratory experiment has been carried out in which radioactivity was produced in the detector by neutron irradiation. A Cf-252 source of neutrons was used to produce, by neutron capture on Ge-74 (36.5 percent of natural Ge) in the detector itself, Ge-75 (t sub 1/2 = 82.78 min), which decays by beta emission with a maximum electron kinetic energy of 1188 keV. By requiring that an ionizing event deposit energy in two or more of the five segments of the detector, each about 1-cm thick, the beta particles, which have a range of about 1-mm, are rejected, while most external gamma rays incident on the detector are counted. Analysis of this experiment indicates that over 85 percent of the beta events from the decay of Ge-75 are rejected, which is in good agreement with Monte Carlo calculations.

  12. 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.

  13. 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.

  14. The application of the multi-scale GVF model based on the B-spline lifting wavelet in medical images segmentation

    NASA Astrophysics Data System (ADS)

    Xue, Juntao; Liu, Zhengguang; Zhang, Hongwei; Wang, Shucheng

    2007-01-01

    Snakes, or active contours, are used extensively in computer vision and image processing application, particularly to locate object boundaries. GVF (Gradient Vector Flow) model has resolved two key problems of the traditional deformable model. However, it still requires both the initial contour being close to the target and a large amount of computation. And it is difficult to process the cupped target edge. This paper analysis the characteristics of deformable model firstly, then proposed a new method based on B-spline lifting wavelet. Experimentations based on GVF model and MRI segmentation show that the proposed method is a good resolution to the initialization sensitivity and the large computation.

  15. Hydrothermal Activity Along Multiple Ridge Segments of the Northern Central Indian Ridge, 8°-17°S

    NASA Astrophysics Data System (ADS)

    Son, J.; Kim, J.; Pak, S.; Son, S.; Moon, J.; Baker, E. T.

    2012-12-01

    We report the first systematic hydrothermal plume surveys conducted on the northern Central Indian Ridge (CIR, 8°-17°S), a slow spreading ridge with rates between ~35 and 40 mm/yr, during the CIR research program of KORDI between 2009 and 2011. Using a combined CTD/Miniature Autonomous Plume Recorder (MAPR) package we occupied 208 vertical casts and 82 tows along seven segments of the CIR totaling ~700 km of ridge length to estimate the frequency of hydrothermal activity on this slow-spreading ridge. Evidence for hydrothermal activity was found on each of the seven segments, with most plumes found between 3000 and 3500 m. Using only stations within the rift valley, the estimated value of plume incidence (ph=0.19) coincides with the global trend between the spatial density of hydrothermal plumes and full-spreading rate (an indicator of magmatic budget). However, there are also indications of possible discharge from hydrothermal activity or serpentinization from the ridge flanks (possible ocean core complexes), as has been observed along the Mid-Atlantic Ridge. For example, some sites show methane anomalies unaccompanied by any optical anomaly. Our preliminary results support the increasing role of tectonic control on hydrothermal activity as spreading rates decrease. Further examination of the plume signals, combined with chemical composition of sampled water and geological data, will provide valuable insights into hydrothermal activity on slow spreading ridges.

  16. 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

  17. 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.

  18. Contoured insulation window for evacuated solar collector

    SciTech Connect

    Coppola, F. T.; Lentz, W. P.; Vandewoestine, R. V.

    1980-02-05

    An insulating contoured window is provided for use with an enclosed chamber such as an evacuated flat plate solar heat collector with the contoured solar window being of minimum thickness and supported solely about its peripheral edge portions. The window is contoured in both its longitudinal and transverse directions, such that in its longitudinal direction the window is composed of a plurality of sinusoidal corrugations whereas in its transverse direction the peaks of such corrugations are contoured in the form of paraboloids so that the structure may withstand the forces generated thereon by the atmosphere.

  19. Late quaternary active characteristics and slip-rate of Pingding-Huama Fault, the eastern segment of Guanggaishan-Dieshan Fault zone ( West Qinlin Mountain )

    NASA Astrophysics Data System (ADS)

    Jingxing, Y.; Wenjun, Z.; Daoyang, Y.; Jianzhang, P.; Xingwang, L.; Baiyun, L.

    2012-12-01

    Stretching along the west QinlinShan in the north Tibet, the Guanggaishan-Dieshanfaultis composed of three sub-parallel faults among which the major one is a fault named Pingding-Huama fault. The Pingding-Huama fault can be further defined as a combination of a western segment and an eastern segment separated by Minjiang river at Dangchang. Along the western segment of the Pingding-Huama fault, significant linear characteristics, scars, and fault scarps cutting several alluvial fans can be easily distinguished, indicating that the western segment is active since the late Quatenary and the elapsed time of the last event should be less than 1ka B.P.. We estimated the slip rates of the western segment through geomorphology analysis and dating the age of the top surface of terraces and the deformed strata (OSL, 14C). The results show that its reverse slip rate ranges from 0.69±0.16 to 1.15±0.28mm/a and the sinistral slip rate is 0.51±0.13mm/a. In contrast to the simple structure of the western segment, the eastern segment consists of several sub-parallel faults as well as oblique intersected faults. On all faults of the eastern segment, no sign of recent movement was discovered. Along these faults, the tectonic topography features a sequence of linear valleys in the west and dominant folds in the east. Only striations in bedrock and geomorphology show that the eastern segment was reversely slipping on the whole with sinistral component. In summary, at present the Pingding-Huama fault is active along its western segment while shows very weak deformation along the eastern segment.

  20. 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).

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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.

  6. 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…

  7. 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…

  8. Auditory and Visual Similarity of Pitch Contours.

    ERIC Educational Resources Information Center

    Hermes, Dik J.

    1998-01-01

    In two experiments, five phoneticians rated the dissimilarity of two pitch contours to investigate whether important audible differences would correspond with visually conspicuous differences between displayed pitch contours. Results indicate that visual feedback may be very effective in intonation training if auditorily relevant features of pitch…

  9. Measuring the Perceptual Similarity of Pitch Contours.

    ERIC Educational Resources Information Center

    Hermes, Dik J.

    1998-01-01

    This study investigated the effectiveness of four different methods for measuring the similarity of pitch contours. The correlation coefficient between two normalized contours was the best method; however, if pitch range is important, the mean distance and the root-mean-square distance should be considered first in automatic training in…

  10. Predominant expression and activity of vacuolar H(+)-ATPases in the mixed segment of the wood-feeding termite Nasutitermes takasagoensis.

    PubMed

    Kumara, Rohitha P; Saitoh, Seikoh; Aoyama, Hiroaki; Shinzato, Naoya; Tokuda, Gaku

    2015-07-01

    The mixed segment is a unique part of the gut present only in the most apical lineage of termites and consists of a complex of overlapping mesenteric and proctodeal epithelia. In spite of its unique structure, the physiological functions of the mixed segment have been poorly studied. We performed transcriptome analysis to identify functional enzymes acting in the mixed segment of the wood-feeding higher termite Nasutitermes takasagoensis. We sequenced the transcripts (4563 isotigs) of the mixed segment and compared them with those of the midgut (4813 isotigs) and the first proctodeal segment (3629 isotigs). We found that vacuolar H(+)-ATPase (V-ATPase) subunits were predominant in the mixed segment, which was confirmed by RT-qPCR analysis. The V-ATPase activity in these three tissues was in a good agreement with the expression patterns, suggesting that V-ATPase is a prevalent enzyme in the mixed segment of the termites. The results confirmed the proposed role of the mixed segment as a transporting epithelium. PMID:25937057

  11. 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. PMID:27452469

  12. 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. PMID:26683043

  13. Contour Tracking in Echocardiographic Sequences via Sparse Representation and Dictionary Learning

    PubMed Central

    Huang, Xiaojie; Dione, Donald P.; Compas, Colin B.; Papademetris, Xenophon; Lin, Ben A.; Bregasi, Alda; Sinusas, Albert J.; Staib, Lawrence H.; Duncan, James S.

    2013-01-01

    This paper presents a dynamical appearance model based on sparse representation and dictionary learning for tracking both endocardial and epicardial contours of the left ventricle in echocardiographic sequences. Instead of learning offline spatiotemporal priors from databases, we exploit the inherent spatiotemporal coherence of individual data to constraint cardiac contour estimation. The contour tracker is initialized with a manual tracing of the first frame. It employs multiscale sparse representation of local image appearance and learns online multiscale appearance dictionaries in a boosting framework as the image sequence is segmented frame-by-frame sequentially. The weights of multiscale appearance dictionaries are optimized automatically. Our region-based level set segmentation integrates a spectrum of complementary multilevel information including intensity, multiscale local appearance, and dynamical shape prediction. The approach is validated on twenty-six 4D canine echocardiographic images acquired from both healthy and post-infarct canines. The segmentation results agree well with expert manual tracings. The ejection fraction estimates also show good agreement with manual results. Advantages of our approach are demonstrated by comparisons with a conventional pure intensity model, a registration-based contour tracker, and a state-of-the-art database-dependent offline dynamical shape model. We also demonstrate the feasibility of clinical application by applying the method to four 4D human data sets. PMID:24292554

  14. Contour tracking in echocardiographic sequences via sparse representation and dictionary learning.

    PubMed

    Huang, Xiaojie; Dione, Donald P; Compas, Colin B; Papademetris, Xenophon; Lin, Ben A; Bregasi, Alda; Sinusas, Albert J; Staib, Lawrence H; Duncan, James S

    2014-02-01

    This paper presents a dynamical appearance model based on sparse representation and dictionary learning for tracking both endocardial and epicardial contours of the left ventricle in echocardiographic sequences. Instead of learning offline spatiotemporal priors from databases, we exploit the inherent spatiotemporal coherence of individual data to constraint cardiac contour estimation. The contour tracker is initialized with a manual tracing of the first frame. It employs multiscale sparse representation of local image appearance and learns online multiscale appearance dictionaries in a boosting framework as the image sequence is segmented frame-by-frame sequentially. The weights of multiscale appearance dictionaries are optimized automatically. Our region-based level set segmentation integrates a spectrum of complementary multilevel information including intensity, multiscale local appearance, and dynamical shape prediction. The approach is validated on twenty-six 4D canine echocardiographic images acquired from both healthy and post-infarct canines. The segmentation results agree well with expert manual tracings. The ejection fraction estimates also show good agreement with manual results. Advantages of our approach are demonstrated by comparisons with a conventional pure intensity model, a registration-based contour tracker, and a state-of-the-art database-dependent offline dynamical shape model. We also demonstrate the feasibility of clinical application by applying the method to four 4D human data sets. PMID:24292554

  15. 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

  16. Automatic morphological characterization of nanobubbles with a novel image segmentation method and its application in the study of nanobubble coalescence

    PubMed Central

    Wang, Huimin; Bi, Shusheng; Guo, Bin

    2015-01-01

    Summary 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

  17. 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.

  18. 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

  19. Determination of the absolute contours of optical flats

    NASA Technical Reports Server (NTRS)

    Primak, W.

    1969-01-01

    Emersons procedure is used to determine true absolute contours of optical flats. Absolute contours of standard flats are determined and a comparison is then made between standard and unknown flats. Contour differences are determined by deviation of Fizeau fringe.

  20. Differential contribution of early visual areas to the perceptual process of contour processing.

    PubMed

    Schira, Mark M; Fahle, Manfred; Donner, Tobias H; Kraft, Antje; Brandt, Stephan A

    2004-04-01

    We investigated contour processing and figure-ground detection within human retinotopic areas using event-related functional magnetic resonance imaging (fMRI) in 6 healthy and naïve subjects. A figure (6 degrees side length) was created by a 2nd-order texture contour. An independent and demanding foveal letter-discrimination task prevented subjects from noticing this more peripheral contour stimulus. The contour subdivided our stimulus into a figure and a ground. Using localizers and retinotopic mapping stimuli we were able to subdivide each early visual area into 3 eccentricity regions corresponding to 1) the central figure, 2) the area along the contour, and 3) the background. In these subregions we investigated the hemodynamic responses to our stimuli and compared responses with or without the contour defining the figure. No contour-related blood oxygenation level-dependent modulation in early visual areas V1, V3, VP, and MT+ was found. Significant signal modulation in the contour subregions of V2v, V2d, V3a, and LO occurred. This activation pattern was different from comparable studies, which might be attributable to the letter-discrimination task reducing confounding attentional modulation. In V3a, but not in any other retinotopic area, signal modulation corresponding to the central figure could be detected. Such contextual modulation will be discussed in light of the recurrent processing hypothesis and the role of visual awareness. PMID:14668291

  1. 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.

  2. 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.

  3. 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.

  4. Active fault segmentation and seismic hazard in Hoa-Binh reservoir, Vietnam

    NASA Astrophysics Data System (ADS)

    Trinh, Phan; Vinh, Hoang; Huong, Nguyen; Liem, Ngo

    2013-06-01

    Based on remote sensing, geological data, geomorphologic analysis, and field observations, we determine the fault system which is a potential source of earthquakes in Hoa-Binh reservoir. It is the sub-meridian fault system composed of fault segments located in the central part of the eastern and western flanks of the Quaternary Hoa-Binh Graben: the Hoa-Binh 1 fault is east-dipping (75-80°), N-S trending, 4 km long, situated in the west of the Hoa-Binh Graben, and the Hoa-Binh 2 is a west-dipping (75-80°), N-S trending; 8.4 km long fault, situated in the east of the Hoa-Binh Graben. The slip rate of normal fault in Hoa-Binh hydropower dam was estimated at 0.3-1.1 mm/yr. The Maximum Credible Earthquake (MCE) and Peak Ground Acceleration (PGA) in the Hoa-Binh hydropower dam have been assessed. The estimated MCE of HB.1 and HB.2 is 5.6 and 6.1 respectively, and the maximum PGA at Hoa-Binh dam is 0.30 g and 0.40 g, respectively. The assessment of seismic hazard in Hoa-Binh reservoir is a typical example of seismic hazards of a large dam constructed in an area of low seismicity and lack of law of seismic attenuation.

  5. 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.

  6. Structural Geology of the Active Forearc above the Maule Megathrust: Traces of a Long-lived Subduction Segment

    NASA Astrophysics Data System (ADS)

    Aron, F. A.; Cembrano, J. M.; Allmendinger, R. W.; Astudillo, F.; Arancibia, G.

    2012-12-01

    The 2010 Mw8.8 Maule earthquake rupture in central Chile produced significant upper and lower plate normal fault aftershocks including some of the largest recorded, the Mw7.0 Pichilemu events 11 days after the main event. Our understanding of the context and significance of these events for permanent deformation of the upper plate has been hampered by poorly known regional geology overlying the northern and central parts of the Maule rupture. We present new structural data of the Coastal Cordillera from the northern end of the rupture which illuminates the relationship between coseimic and long term deformation. We show that the Neogene normal faults along the outer forearc, including the Pichilemu normal fault, can be reactivated by the coseismic stress imposed within the upper plate by great subduction ruptures. The structural style of the region overlying the northern end of the Maule rupture is dominated by kilometer-scale normal faults which have been active at least throughout the Neogene. The strikes of these main structures define three structural systems: (1) a NE and (2) a NW sets of margin-oblique faults, and (3) a ~NS, margin-parallel set. The SW-dipping Pichilemu fault, which has at least three flights of uplifted marine terraces in the footwall but only a single low terrace displaying a rollover anticline in the footwall, belongs to the second group. The first two sets characterize the northernmost part of the rupture and spatially overlap, displaying a bimodal orientation; the third set occurs farther south and appears to characterize the central part of the rupture segment. Reverse faults exist but are scarce. Using the slip model of the Maule earthquake by Vigny et al. 2011 we calculate the strikes of optimally oriented normal faults along the Coastal Cordillera from the Coulomb stress increment. Comparing these strikes to the strikes of known faults and our new data, we find that nearly half agree in orientation within 22.5°. The extensional

  7. Segmental neurofibromatosis.

    PubMed

    Galhotra, Virat; Sheikh, Soheyl; Jindal, Sanjeev; Singla, Anshu

    2014-07-01

    Segmental neurofibromatosis is a rare disorder, characterized by neurofibromas or cafι-au-lait macules limited to one region of the body. Its occurrence on the face is extremely rare and only few cases of segmental neurofibromatosis over the face have been described so far. We present a case of segmental neurofibromatosis involving the buccal mucosa, tongue, cheek, ear, and neck on the right side of the face. PMID:25565748

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. Holding fixture for variable-contour parts

    NASA Technical Reports Server (NTRS)

    Haynie, C. C.; Packer, P. N.; Zebus, P. P.

    1979-01-01

    Array of vacuum cups on spindles holds parts for safe machining and other processings. Variable-contour part resting on fixture is held firmly enough for machining, coating, or other mechanical treatment.

  13. Pin guidance of reconstruction plate contour: an expanded role of external fixation.

    PubMed

    Jaquet, Yves; Higgins, Kevin M; Enepekides, Danny J

    2011-09-01

    This article presents a modification of intraoperative external fixation for mandibular reconstruction with free tissue flaps. This technique is indicated when preregistration of the reconstruction plate is not possible due to transmandibular tumor extension. Once standard external fixation has been carried out and prior to segmental mandibulectomy, additional pins are fixed to the connecting rod that delineate the mandibular contour in three-dimensional (3D) space. Following mandibulectomy, these pins allow accurate contouring of the reconstruction plate and improved restoration of mandibular contour, projection, and dental occlusion. A step-by-step description of the technique using models and intraoperative photos is presented. This method of mandibular reconstruction is a simple and time-effective alternative to intraoperative computer navigation and 3D modeling in select cases of oral carcinoma where tumor infiltration of the outer mandibular cortex precludes prebending of the reconstruction plates. PMID:22024840

  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. Segmental neurofibromatosis.

    PubMed

    Toy, Brian

    2003-10-01

    Segmental neurofibromatosis is a rare variant of neurofibromatosis in which skin lesions are confined to a circumscribed body segment. A case of a 72-year-old woman with this condition is presented. Clinical features and genetic evidence are reviewed. PMID:14594599

  16. 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.

  17. 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.

  18. Surgical correction of postliposuction contour irregularities.

    PubMed

    Chang, K N

    1994-07-01

    The surgical correction of postliposuction contour irregularities and the results are presented. Postliposuction contour irregularities are classified as major or minor according to the size of the area, severity of the irregularity, difficulty of the correction, visual impact, and the need for dermolipectomy. Methods of correction include (1) liposuction of the area of protuberance, (2) liposuction around the area of depression, (3) simultaneous fat grafting, and (4) dermolipectomy. Results of 22 patients with 43 areas of postliposuction contour irregularities were analyzed. Follow-up ranged from 1 to 4.8 years (mean 2.1 +/- 1.0 years). All patients had corrective liposuction except one, who required medial thigh dermolipectomy. Fat grafting was performed in 19 areas in 9 patients. Average number of operations performed was 1.4 per patient (range 1 to 3). Of 17 areas of minor postliposuction contour irregularities, 8 (47 percent) were improved and 8 (47 percent) were corrected. Of 26 areas of major postliposuction contour irregularities, 17 (65 percent) were improved and 8 (31 percent) were corrected. Of all 43 areas, 25 (58 percent) were improved and 16 (37 percent) were corrected. Overcorrection in two areas (4.7 percent) resulted in minor depressions in 2 patients. Results from 5 patients are presented. In summary, postliposuction contour irregularities were treated with various surgical techniques with a high rate of improvement or correction. PMID:8016225

  19. Max-flow segmentation of the left ventricle by recovering subject-specific distributions via a bound of the Bhattacharyya measure.

    PubMed

    Ben Ayed, Ismail; Chen, Hua-Mei; Punithakumar, Kumaradevan; Ross, Ian; Li, Shuo

    2012-01-01

    This study investigates fast detection of the left ventricle (LV) endo- and epicardium boundaries in a cardiac magnetic resonance (MR) sequence following the optimization of two original discrete cost functions, each containing global intensity and geometry constraints based on the Bhattacharyya similarity. The cost functions and the corresponding max-flow optimization built upon an original bound of the Bhattacharyya measure yield competitive results in nearly real-time. Within each frame, the algorithm seeks the LV cavity and myocardium regions consistent with subject-specific model distributions learned from the first frame in the sequence. Based on global rather than pixel-wise information, the proposed formulation relaxes the need of a large training set and optimization with respect to geometric transformations. Different from related active contour methods, it does not require a large number of iterative updates of the segmentation and the corresponding computationally onerous kernel density estimates (KDEs). The algorithm requires very few iterations and KDEs to converge. Furthermore, the proposed bound can be used for several other applications and, therefore, can lead to segmentation algorithms which share the flexibility of active contours and computational advantages of max-flow optimization. Quantitative evaluations over 2280 images acquired from 20 subjects demonstrated that the results correlate well with independent manual segmentations by an expert. Moreover, comparisons with a related recent active contour method showed that the proposed framework brings significant improvements in regard to accuracy and computational efficiency. PMID:21705264

  20. Evaluation of the effect of myocardial segmentation errors on myocardial blood flow estimates from DCE-MRI

    NASA Astrophysics Data System (ADS)

    Biglands, J.; Magee, D.; Boyle, R.; Larghat, A.; Plein, S.; Radjenović, A.

    2011-04-01

    Quantitative analysis of cardiac dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) perfusion datasets is dependent on the drawing (manually or automatically) of myocardial contours. The required accuracy of these contours for myocardial blood flow (MBF) estimation is not well understood. This study investigates the relationship between myocardial contour errors and MBF errors. Myocardial contours were manually drawn on DCE-MRI perfusion datasets of healthy volunteers imaged in systole. Systematic and random contour errors were simulated using spline curves and the resulting errors in MBF were calculated. The degree of contour error was also evaluated by two recognized segmentation metrics. We derived contour error tolerances in terms of the maximum deviation (MD) a contour could deviate radially from the 'true' contour expressed as a fraction of each volunteer's mean myocardial width (MW). Significant MBF errors were avoided by setting tolerances of MD <= 0.4 MW, when considering the whole myocardium, MD <= 0.3 MW, when considering six radial segments, and MD <= 0.2 MW for further subdivision into endo- and epicardial regions, with the exception of the anteroseptal region, which required greater accuracy. None of the considered segmentation metrics correlated with MBF error; thus, both segmentation metrics and MBF errors should be used to evaluate contouring algorithms.

  1. Segmentation-based video coding

    SciTech Connect

    Lades, M.; Wong, Yiu-fai; Li, Qi

    1995-10-01

    Low bit rate video coding is gaining attention through a current wave of consumer oriented multimedia applications which aim, e.g., for video conferencing over telephone lines or for wireless communication. In this work we describe a new segmentation-based approach to video coding which belongs to a class of paradigms appearing very promising among the various proposed methods. Our method uses a nonlinear measure of local variance to identify the smooth areas in an image in a more indicative and robust fashion: First, the local minima in the variance image are identified. These minima then serve as seeds for the segmentation of the image with a watershed algorithm. Regions and their contours are extracted. Motion compensation is used to predict the change of regions between previous frames and the current frame. The error signal is then quantized. To reduce the number of regions and contours, we use the motion information to assist the segmentation process, to merge regions, resulting in a further reduction in bit rate. Our scheme has been tested and good results have been obtained.

  2. Active figure maintenance control using an optical truss laser metrology system for a space-based far-IR segmented telescope

    NASA Technical Reports Server (NTRS)

    Lau, Kenneth; Breckenridge, Bill; Nerheim, Noble; Redding, David

    1992-01-01

    A two-stage active control approach was developed addressing the figure control problem for a spaceborne FIR telescope, the Precision Segmented Reflectors Focus Moderate Mission Telescope (FMMT). The first active control stage aligns the optical segments based on images; attention is here given to the second stage, active figure maintenance control system, which maintains the alignment of the optical elements between initializations to hold the mirror figure steady while obtaining data and fixes translational and rotational changes of the optical segments induced by long-term thermal drifts of the support structure. Errors are expected to be 10-100 microns at the nodes of the primary backup structure over the course of an orbit. An rms performance of 0.8 microns of wavefront error can be expected during the maintenance function based on specified nominal sensor noises, actuator accuracies, and system environments. A performance of less than 0.3 microns rms can be expected, based on advanced components.

  3. Retinal Vessel Segmentation: An Efficient Graph Cut Approach with Retinex and Local Phase

    PubMed Central

    Zhao, Yitian; Liu, Yonghuai; Wu, Xiangqian; Harding, Simon P.; Zheng, Yalin

    2015-01-01

    Our application concerns the automated detection of vessels in retinal images to improve understanding of the disease mechanism, diagnosis and treatment of retinal and a number of systemic diseases. We propose a new framework for segmenting retinal vasculatures with much improved accuracy and efficiency. The proposed framework consists of three technical components: Retinex-based image inhomogeneity correction, local phase-based vessel enhancement and graph cut-based active contour segmentation. These procedures are applied in the following order. Underpinned by the Retinex theory, the inhomogeneity correction step aims to address challenges presented by the image intensity inhomogeneities, and the relatively low contrast of thin vessels compared to the background. The local phase enhancement technique is employed to enhance vessels for its superiority in preserving the vessel edges. The graph cut-based active contour method is used for its efficiency and effectiveness in segmenting the vessels from the enhanced images using the local phase filter. We have demonstrated its performance by applying it to four public retinal image datasets (3 datasets of color fundus photography and 1 of fluorescein angiography). Statistical analysis demonstrates that each component of the framework can provide the level of performance expected. The proposed framework is compared with widely used unsupervised and supervised methods, showing that the overall framework outperforms its competitors. For example, the achieved sensitivity (0:744), specificity (0:978) and accuracy (0:953) for the DRIVE dataset are very close to those of the manual annotations obtained by the second observer. PMID:25830353

  4. A review of ultrasound common carotid artery image and video segmentation techniques.

    PubMed

    Loizou, Christos P

    2014-12-01

    The determination of the wall thickness [intima-media thickness (IMT)], the delineation of the atherosclerotic carotid plaque, the measurement of the diameter in the common carotid artery (CCA), as well as the grading of its stenosis are important for the evaluation of the atherosclerosis disease. All these measurements are also considered to be significant markers for the clinical evaluation of the risk of stroke. A number of CCA segmentation techniques have been proposed in the last few years either for the segmentation of the intima-media complex (IMC), the lumen of the CCA, or for the atherosclerotic carotid plaque from ultrasound images or videos of the CCA. The present review study proposes and discusses the methods and systems introduced so far in the literature for performing automated or semi-automated segmentation in ultrasound images or videos of the CCA. These are based on edge detection, active contours, level sets, dynamic programming, local statistics, Hough transform, statistical modeling, neural networks, and an integration of the above methods. Furthermore, the performance of these systems is evaluated and discussed based on various evaluation metrics. We finally propose the best performing method that can be used for the segmentation of the IMC and the atherosclerotic carotid plaque in ultrasound images and videos. We end the present review study with a discussion of the different image and video CCA segmentation techniques, future perspectives, and further extension of these techniques to ultrasound video segmentation and wall tracking of the CCA. Future work on the segmentation of the CCA will be focused on the development of integrated segmentation systems for the complete segmentation of the CCA as well as the segmentation and motion analysis of the plaque and or the IMC from ultrasound video sequences of the CCA. These systems will improve the evaluation, follow up, and treatment of patients affected by advanced atherosclerosis disease

  5. 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

  6. 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

  7. 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. PMID:21353575

  8. Sodium-pump gene-expression, protein abundance and enzyme activity in isolated nephron segments of the aging rat kidney

    PubMed Central

    Scherzer, Pnina; Gal-Moscovici, Anca; Sheikh-Hamad, David; Popovtzer, Mordecai M

    2015-01-01

    Aging is associated with alteration in renal tubular functions, including sodium handling and concentrating ability. Na-K-ATPase plays a key role in driving tubular transport, and we hypothesized that decreased concentrating ability of the aging kidney is due in part to downregulation of Na-K-ATPase. In this study, we evaluated Na and K balance, aldosterone levels, and Na-K-ATPase gene expression, protein abundance, and activity in aging rat kidney. Na-K-ATPase activity (assayed microfluorometrically), mRNA (RT-PCR), and protein abundance (immunoblotting) were quantitated in the following isolated nephron segments: PCT, PST, MTAL, DCT, and CCD from 2, 8, 15, and 24 month-old-rats. In the course of aging, creatinine clearance decreased from 0.48 ± 0.02 mL/min/100 g BW to 0.28 ± 0.06 (P < 0.001) and aldosterone decreased from 23.6 ± 0.8 ng/dL to 13.2 ± 0.6 (P < 0.001). Serum Na+ and K+ increased by 4.0% and 22.5%, respectively. Na-K-ATPase activity, mRNA, and protein abundance of the α1 subunit displayed similar trends in all assayed segments; increasing in PCT and PST; decreasing in MTAL and DCT; increasing in CCD: in PCT they increased by 40%, 75%, and 250%, respectively; while in PST they increased by 80%, 50%, and 100%, respectively (P < 0.001). In MTAL they declined by 36%, 24%, and 34%, respectively, and in DCT by 38%, 59%, and 60%, respectively (P < 0.001). They were higher in CCD by 110%, 115%, and 246%, respectively (P < 0.001). Rats maintained Na/K balance; however with a steady state elevated serum K+. These results reveal quantitative changes in axial distribution of Na-K-ATPase at the level of gene expression, protein abundance, and activity in the nephrons of aging animals and may explain, in part, the pathophysiology of the senescent kidney. PMID:26056060

  9. 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.

  10. Fusion of ultrasound B-mode and vibro-elastography images for automatic 3D segmentation of the prostate.

    PubMed

    Mahdavi, S Sara; Moradi, Mehdi; Morris, William J; Goldenberg, S Larry; Salcudean, Septimiu E

    2012-11-01

    Prostate segmentation in B-mode images is a challenging task even when done manually by experts. In this paper we propose a 3D automatic prostate segmentation algorithm which makes use of information from both ultrasound B-mode and vibro-elastography data.We exploit the high contrast to noise ratio of vibro-elastography images of the prostate, in addition to the commonly used B-mode images, to implement a 2D Active Shape Model (ASM)-based segmentation algorithm on the midgland image. The prostate model is deformed by a combination of two measures: the gray level similarity and the continuity of the prostate edge in both image types. The automatically obtained mid-gland contour is then used to initialize a 3D segmentation algorithm which models the prostate as a tapered and warped ellipsoid. Vibro-elastography images are used in addition to ultrasound images to improve boundary detection.We report a Dice similarity coefficient of 0.87±0.07 and 0.87±0.08 comparing the 2D automatic contours with manual contours of two observers on 61 images. For 11 cases, a whole gland volume error of 10.2±2.2% and 13.5±4.1% and whole gland volume difference of -7.2±9.1% and -13.3±12.6% between 3D automatic and manual surfaces of two observers is obtained. This is the first validated work showing the fusion of B-mode and vibro-elastography data for automatic 3D segmentation of the prostate. PMID:22829391

  11. 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

  12. Review of recent advances in segmentation of the breast boundary and the pectoral muscle in mammograms.

    PubMed

    Mustra, Mario; Grgic, Mislav; Rangayyan, Rangaraj M

    2016-07-01

    This paper presents a review of recent advances in the development of methods for segmentation of the breast boundary and the pectoral muscle in mammograms. Regardless of improvement of imaging technology, accurate segmentation of the breast boundary and detection of the pectoral muscle are still challenging tasks for image processing algorithms. In this paper, we discuss problems related to mammographic image preprocessing and accurate segmentation. We review specific methods that were commonly used in most of the techniques proposed for segmentation of mammograms and discuss their advantages and disadvantages. Comparative analysis of the methods reported on is made difficult by variations in the datasets and procedures of evaluation used by the authors. We attempt to overcome some of these limitations by trying to compare methods which used the same dataset and have some similarities in approaches to the breast boundary segmentation and detection of the pectoral muscle. In this paper, we will address the most often used methods for segmentation such as thresholding, morphology, region growing, active contours, and wavelet filtering. These methods, or their combinations, are the ones most used in the last decade by the majority of work published in this image processing domain. PMID:26546074

  13. 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. PMID:26459767

  14. Perception of emotional valences and activity levels from vowel segments of continuous speech.

    PubMed

    Waaramaa, Teija; Laukkanen, Anne-Maria; Airas, Matti; Alku, Paavo

    2010-01-01

    This study aimed to investigate the role of voice source and formant frequencies in the perception of emotional valence and psychophysiological activity level from short vowel samples (approximately 150 milliseconds). Nine professional actors (five males and four females) read a prose passage simulating joy, tenderness, sadness, anger, and a neutral emotional state. The stress carrying vowel [a:] was extracted from continuous speech during the Finnish word [ta:k:ahan] and analyzed for duration, fundamental frequency (F0), equivalent sound level (L(eq)), alpha ratio, and formant frequencies F1-F4. Alpha ratio was calculated by subtracting the L(eq) (dB) in the range 50 Hz-1 kHz from the L(eq) in the range 1-5 kHz. The samples were inverse filtered by Iterative Adaptive Inverse Filtering and the estimates of the glottal flow obtained were parameterized with the normalized amplitude quotient (NAQ = f(AC)/(d(peak)T)). Fifty listeners (mean age 28.5 years) identified the emotional valences from the randomized samples. Multinomial Logistic Regression Analysis was used to study the interrelations of the parameters for perception. It appeared to be possible to identify valences from vowel samples of short duration ( approximately 150 milliseconds). NAQ tended to differentiate between the valences and activity levels perceived in both genders. Voice source may not only reflect variations of F0 and L(eq), but may also have an independent role in expression, reflecting phonation types. To some extent, formant frequencies appeared to be related to valence perception but no clear patterns could be identified. Coding of valence tends to be a complicated multiparameter phenomenon with wide individual variation. PMID:19111438

  15. 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.

  16. Prostate Contouring Variation: Can It Be Fixed?

    SciTech Connect

    Khoo, Eric L.H.; Schick, Karlissa; Plank, Ashley W.; Poulsen, Michael; Wong, Winnie W.G.; Middleton, Mark; Martin, Jarad M.

    2012-04-01

    Purpose: To assess whether an education program on CT and MRI prostate anatomy would reduce inter- and intraobserver prostate contouring variation among experienced radiation oncologists. Methods and Materials: Three patient CT and MRI datasets were selected. Five radiation oncologists contoured the prostate for each patient on CT first, then MRI, and again between 2 and 4 weeks later. Three education sessions were then conducted. The same contouring process was then repeated with the same datasets and oncologists. The observer variation was assessed according to changes in the ratio of the encompassing volume to intersecting volume (volume ratio [VR]), across sets of target volumes. Results: For interobserver variation, there was a 15% reduction in mean VR with CT, from 2.74 to 2.33, and a 40% reduction in mean VR with MRI, from 2.38 to 1.41 after education. A similar trend was found for intraobserver variation, with a mean VR reduction for CT and MRI of 9% (from 1.51 to 1.38) and 16% (from 1.37 to 1.15), respectively. Conclusion: A well-structured education program has reduced both inter- and intraobserver prostate contouring variations. The impact was greater on MRI than on CT. With the ongoing incorporation of new technologies into routine practice, education programs for target contouring should be incorporated as part of the continuing medical education of radiation oncologists.

  17. New insights on the seismogenic potential of the Eastern Betic Shear Zone (SE Iberia): Quaternary activity and paleoseismicity of the SW segment of the Carrascoy Fault Zone

    NASA Astrophysics Data System (ADS)

    Martín-Banda, Raquel; García-Mayordomo, Julián.; Insua-Arévalo, Juan M.; Salazar, Ángel E.; Rodríguez-Escudero, Emilio; Álvarez-Gómez, Jose A.; Medialdea, Alicia; Herrero, María. J.

    2016-01-01

    The Carrascoy Fault (CAF) is one of the main active faults that form part of the Eastern Betic Shear Zone, a 450 km fault system that accommodates most of the convergence between the Eurasian (Iberia) and Nubian plates in the Betic Cordillera, south Spain. Although the CAF represents a major earthquake threat to the nearby City of Murcia, studies on its Quaternary tectonics and seismogenic potential are scarce to date. We present evidence that supports the division of the CAF into two overlapping segments with contrasting tectonic structure, Quaternary activity, and landform control: a SW segment, characterized by a broad fold-and-thrust zone similar to the forebergs defined in the Gobi-Altai region, and a NE segment, characterized by a sharp mountain front controlled by strike-slip tectonics. We attribute the differentiation into these two segments to the stresses associated with topography, which in turn is a consequence of the shortening component, at the middle Pleistocene, after circa 217.4 ka. For the SW segment we infer the occurrence of 9 to 11, Mw 6.7 paleoearthquakes in the last 30.2 kyr, and a slip rate of 0.37 ± 0.08 m/kyr. We date the occurrence of the last surface rupture event after 2750 B.P., and we estimate an average recurrence period of major events of 3.3 ± 0.7 kyr.

  18. 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

  19. 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

  20. Coding Long Contour Shapes of Binary Objects

    NASA Astrophysics Data System (ADS)

    Sánchez-Cruz, Hermilo; Rodríguez-Díaz, Mario A.

    This is an extension of the paper appeared in [15]. This time, we compare four methods: Arithmetic coding applied to 3OT chain code (Arith-3OT), Arithmetic coding applied to DFCCE (Arith-DFCCE), Huffman coding applied to DFCCE chain code (Huff-DFCCE), and, to measure the efficiency of the chain codes, we propose to compare the methods with JBIG, which constitutes an international standard. In the aim to look for a suitable and better representation of contour shapes, our probes suggest that a sound method to represent contour shapes is 3OT, because Arithmetic coding applied to it gives the best results regarding JBIG, independently of the perimeter of the contour shapes.

  1. 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.

  2. Leaf Shape Recognition using Centroid Contour Distance

    NASA Astrophysics Data System (ADS)

    Hasim, Abdurrasyid; Herdiyeni, Yeni; Douady, Stephane

    2016-01-01

    This research recognizes the leaf shape using Centroid Contour Distance (CCD) as shape descriptor. CCD is an algorithm of shape representation contour-based approach which only exploits boundary information. CCD calculates the distance between the midpoint and the points on the edge corresponding to interval angle. Leaf shapes that included in this study are ellips, cordate, ovate, and lanceolate. We analyzed 200 leaf images of tropical plant. Each class consists of 50 images. The best accuracy is obtained by 96.67%. We used Probabilistic Neural Network to classify the leaf shape. Experimental results demonstrated the effectiveness of the proposed approach for shape recognition with high accuracy.

  3. 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.

  4. Effects of deuterium oxide on growth, proton extrusion, potassium influx, and in vitro plasma membrane activities in maize root segments.

    PubMed

    Sacchi, G A; Cocucci, M

    1992-12-01

    Elongation of subapical segments of maize (Zea mays) roots was greatly inhibited by (2)H(2)O in the incubation medium. Short-term exposure (30 min) to (2)H(2)O slightly reduced O(2) uptake and significantly increased ATP levels. (2)H(2)O inhibited H(+) extrusion in the presence of both low (0.05 mm) and high (5 mm) external concentrations of K(+) (about 30 and 53%, respectively at 50% [v/v] (2)H(2)O). Experiments on plasma membrane vesicles showed that H(+)-pumping and ATPase activities were greatly inhibited by (2)H(2)O (about 35% at 50% [v/v] (2)H(2)O); NADH-ferricyanide reductase and 1,3-beta-glucan synthase activities were inhibited to a lesser extent (less than 15%). ATPase activities present in both the tonoplast-enriched and submitochondrial particle preparations were not affected by (2)H(2)O. Therefore, the effect of short incubation time and low concentration of (2)H(2)O is not due to a general action on overall cell metabolism but involves a specific inhibition of the plasma membrane H(+) -ATPase. K(+) uptake was inhibited by (2)H(2)O only when K(+) was present at a low (0.05 mm) external concentration where absorption is against its electrochemical potential. The transmembrane electric potential difference (E(m)) was slightly hyperpolarized by (2)H(2)O at low K(+), but was not affected at the higher K(+) concentrations. These results suggest a relationship between H(+) extrusion and K(+) uptake at low K(+) external concentration. PMID:16653224

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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. PMID:27118087

  10. Using Modified Contour Deformable Model to Quantitatively Estimate Ultrasound Parameters for Osteoporosis Assessment

    NASA Astrophysics Data System (ADS)

    Chen, Yung-Fu; Du, Yi-Chun; Tsai, Yi-Ting; Chen, Tainsong

    Osteoporosis is a systemic skeletal disease, which is characterized by low bone mass and micro-architectural deterioration of bone tissue, leading to bone fragility. Finding an effective method for prevention and early diagnosis of the disease is very important. Several parameters, including broadband ultrasound attenuation (BUA), speed of sound (SOS), and stiffness index (STI), have been used to measure the characteristics of bone tissues. In this paper, we proposed a method, namely modified contour deformable model (MCDM), bases on the active contour model (ACM) and active shape model (ASM) for automatically detecting the calcaneus contour from quantitative ultrasound (QUS) parametric images. The results show that the difference between the contours detected by the MCDM and the true boundary for the phantom is less than one pixel. By comparing the phantom ROIs, significant relationship was found between contour mean and bone mineral density (BMD) with R=0.99. The influence of selecting different ROI diameters (12, 14, 16 and 18 mm) and different region-selecting methods, including fixed region (ROI fix ), automatic circular region (ROI cir ) and calcaneal contour region (ROI anat ), were evaluated for testing human subjects. Measurements with large ROI diameters, especially using fixed region, result in high position errors (10-45%). The precision errors of the measured ultrasonic parameters for ROI anat are smaller than ROI fix and ROI cir . In conclusion, ROI anat provides more accurate measurement of ultrasonic parameters for the evaluation of osteoporosis and is useful for clinical application.

  11. Segmented combustor

    NASA Technical Reports Server (NTRS)

    Halila, Ely E. (Inventor)

    1994-01-01

    A combustor liner segment includes a panel having four sidewalls forming a rectangular outer perimeter. A plurality of integral supporting lugs are disposed substantially perpendicularly to the panel and extend from respective ones of the four sidewalls. A plurality of integral bosses are disposed substantially perpendicularly to the panel and extend from respective ones of the four sidewalls, with the bosses being shorter than the lugs. In one embodiment, the lugs extend through supporting holes in an annular frame for mounting the liner segments thereto, with the bosses abutting the frame for maintaining a predetermined spacing therefrom.

  12. Magnetic resonance segmentation with the bubble wave algorithm

    NASA Astrophysics Data System (ADS)

    Cline, Harvey E.; Ludke, Siegwalt

    2003-05-01

    A new bubble wave algorithm provides automatic segmentation of three-dimensional magnetic resonance images of both the peripheral vasculature and the brain. Simple connectivity algorithms are not reliable in these medical applications because there are unwanted connections through background noise. The bubble wave algorithm restricts connectivity using curvature by testing spherical regions on a propagating active contour to eliminate noise bridges. After the user places seeds in both the selected regions and in the regions that are not desired, the method provides the critical threshold for segmentation using binary search. Today, peripheral vascular disease is diagnosed using magnetic resonance imaging with a timed contrast bolus. A new blood pool contrast agent MS-325 (Epix Medical) binds to albumen in the blood and provides high-resolution three-dimensional images of both arteries and veins. The bubble wave algorithm provides a means to automatically suppress the veins that obscure the arteries in magnetic resonance angiography. Monitoring brain atrophy is needed for trials of drugs that retard the progression of dementia. The brain volume is measured by placing seeds in both the brain and scalp to find the critical threshold that prevents connections between the brain volume and the scalp. Examples from both three-dimensional magnetic resonance brain and contrast enhanced vascular images were segmented with minimal user intervention.

  13. Image Segmentation With Eigenfunctions of an Anisotropic Diffusion Operator.

    PubMed

    Wang, Jingyue; Huang, Weizhang

    2016-05-01

    We propose the eigenvalue problem of an anisotropic diffusion operator for image segmentation. The diffusion matrix is defined based on the input image. The eigenfunctions and the projection of the input image in some eigenspace capture key features of the input image. An important property of the model is that for many input images, the first few eigenfunctions are close to being piecewise constant, which makes them useful as the basis for a variety of applications, such as image segmentation and edge detection. The eigenvalue problem is shown to be related to the algebraic eigenvalue problems resulting from several commonly used discrete spectral clustering models. The relation provides a better understanding and helps developing more efficient numerical implementation and rigorous numerical analysis for discrete spectral segmentation methods. The new continuous model is also different from energy-minimization methods such as active contour models in that no initial guess is required for in the current model. A numerical implementation based on a finite-element method with an anisotropic mesh adaptation strategy is presented. It is shown that the numerical scheme gives much more accurate results on eigenfunctions than uniform meshes. Several interesting features of the model are examined in numerical examples, and possible applications are discussed. PMID:26992021

  14. Activity-dependent mismatch between axo-axonic synapses and the axon initial segment controls neuronal output

    PubMed Central

    Wefelmeyer, Winnie; Cattaert, Daniel; Burrone, Juan

    2015-01-01

    The axon initial segment (AIS) is a structure at the start of the axon with a high density of sodium and potassium channels that defines the site of action potential generation. It has recently been shown that this structure is plastic and can change its position along the axon, as well as its length, in a homeostatic manner. Chronic activity-deprivation paradigms in a chick auditory nucleus lead to a lengthening of the AIS and an increase in neuronal excitability. On the other hand, a long-term increase in activity in dissociated rat hippocampal neurons results in an outward movement of the AIS and a decrease in the cell’s excitability. Here, we investigated whether the AIS is capable of undergoing structural plasticity in rat hippocampal organotypic slices, which retain the diversity of neuronal cell types present at postnatal ages, including chandelier cells. These interneurons exclusively target the AIS of pyramidal neurons and form rows of presynaptic boutons along them. Stimulating individual CA1 pyramidal neurons that express channelrhodopsin-2 for 48 h leads to an outward shift of the AIS. Intriguingly, both the pre- and postsynaptic components of the axo-axonic synapses did not change position after AIS relocation. We used computational modeling to explore the functional consequences of this partial mismatch and found that it allows the GABAergic synapses to strongly oppose action potential generation, and thus downregulate pyramidal cell excitability. We propose that this spatial arrangement is the optimal configuration for a homeostatic response to long-term stimulation. PMID:26195803

  15. Apparatus for electrolytically tapered or contoured cavities

    NASA Technical Reports Server (NTRS)

    Williams, L. A. (Inventor)

    1967-01-01

    An electrolytic machining apparatus for forming tapered or contoured cavities in an electrically conductive and electrochemically erodible piece is presented. It supports the workpiece and an electrode for movement relatively toward each other and has means for pumping an electrolyte between the workpiece and the electrode.

  16. 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.

  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. 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

  19. Expectations for melodic contours transcend pitch.

    PubMed

    Graves, Jackson E; Micheyl, Christophe; Oxenham, Andrew J

    2014-12-01

    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 that the generalization of contour perception to nontraditional dimensions also extends to melodic expectations. In the first experiment, subjective ratings for 3-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 3 auditory dimensions. Taken together, these results suggest that (a) certain well-known principles of melodic expectation (such as the expectation for a reversal following a skip) are dependent on long-term context, and (b) these expectations are not unique to the dimension of pitch and may instead reflect more general principles of perceptual organization. PMID:25365571

  20. 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.

  1. A Computer Language for ECG Contour Analysis

    PubMed Central

    McConnochie, John W.

    1982-01-01

    The purpose of this paper is to demonstrate contructively that criteria for ECG contour analysis can be interpreted directly by a computer. Thereby, the programming task is greatly reduced. Direct interpretation is achieved by the creation of a computer language that is well-suited for the expression of such criteria. Further development of the language is planned.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Camera Would Monitor Weld-Pool Contours

    NASA Technical Reports Server (NTRS)

    Gordon, Stephen S.; Gutow, David A.

    1990-01-01

    Weld pool illuminated and viewed coaxially along welding torch. Proposed monitoring subsystem for arc welder provides image in which horizontal portions of surface of weld pool highlighted. Monitoring and analyzing subsystems integrated into overall control system of robotic welder. Control system sets welding parameters to adapt to changing conditions, maintaining surface contour giving desired pattern of reflections.

  7. Melodic Contour Identification by Cochlear Implant Listeners

    PubMed Central

    Galvin, John J.; Fu, Qian-Jie; Nogaki, Geraldine

    2013-01-01

    Objective While the cochlear implant provides many deaf patients with good speech understanding in quiet, music perception and appreciation with the cochlear implant remains a major challenge for most cochlear implant users. The present study investigated whether a closed-set melodic contour identification (MCI) task could be used to quantify cochlear implant users’ ability to recognize musical melodies and whether MCI performance could be improved with moderate auditory training. The present study also compared MCI performance with familiar melody identification (FMI) performance, with and without MCI training. Methods For the MCI task, test stimuli were melodic contours composed of 5 notes of equal duration whose frequencies corresponded to musical intervals. The interval between successive notes in each contour was varied between 1 and 5 semitones; the “root note” of the contours was also varied (A3, A4, and A5). Nine distinct musical patterns were generated for each interval and root note condition, resulting in a total of 135 musical contours. The identification of these melodic contours was measured in 11 cochlear implant users. FMI was also evaluated in the same subjects; recognition of 12 familiar melodies was tested with and without rhythm cues. MCI was also trained in 6 subjects, using custom software and melodic contours presented in a different frequency range from that used for testing. Results Results showed that MCI recognition performance was highly variable among cochlear implant users, ranging from 14% to 91% correct. For most subjects, MCI performance improved as the number of semitones between successive notes was increased; performance was slightly lower for the A3 root note condition. Mean FMI performance was 58% correct when rhythm cues were preserved and 29% correct when rhythm cues were removed. Statistical analyses revealed no significant correlation between MCI performance and FMI performance (with or without rhythmic cues). However

  8. 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

  9. MOZ and BMI1 play opposing roles during Hox gene activation in ES cells and in body segment identity specification in vivo.

    PubMed

    Sheikh, Bilal N; Downer, Natalie L; Phipson, Belinda; Vanyai, Hannah K; Kueh, Andrew J; McCarthy, Davis J; Smyth, Gordon K; Thomas, Tim; Voss, Anne K

    2015-04-28

    Hox genes underlie the specification of body segment identity in the anterior-posterior axis. They are activated during gastrulation and undergo a dynamic shift from a transcriptionally repressed to an active chromatin state in a sequence that reflects their chromosomal location. Nevertheless, the precise role of chromatin modifying complexes during the initial activation phase remains unclear. In the current study, we examined the role of chromatin regulators during Hox gene activation. Using embryonic stem cell lines lacking the transcriptional activator MOZ and the polycomb-family repressor BMI1, we showed that MOZ and BMI1, respectively, promoted and repressed Hox genes during the shift from the transcriptionally repressed to the active state. Strikingly however, MOZ but not BMI1 was required to regulate Hox mRNA levels after the initial activation phase. To determine the interaction of MOZ and BMI1 in vivo, we interrogated their role in regulating Hox genes and body segment identity using Moz;Bmi1 double deficient mice. We found that the homeotic transformations and shifts in Hox gene expression boundaries observed in single Moz and Bmi1 mutant mice were rescued to a wild type identity in Moz;Bmi1 double knockout animals. Together, our findings establish that MOZ and BMI1 play opposing roles during the onset of Hox gene expression in the ES cell model and during body segment identity specification in vivo. We propose that chromatin-modifying complexes have a previously unappreciated role during the initiation phase of Hox gene expression, which is critical for the correct specification of body segment identity. PMID:25922517

  10. 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.

  11. A Multi-Atlas Based Method for Automated Anatomical Rat Brain MRI Segmentation and Extraction of PET Activity

    PubMed Central

    Lancelot, Sophie; Roche, Roxane; Slimen, Afifa; Bouillot, Caroline; Levigoureux, Elise; Langlois, Jean-Baptiste; Zimmer, Luc; Costes, Nicolas

    2014-01-01

    Introduction Preclinical in vivo imaging requires precise and reproducible delineation of brain structures. Manual segmentation is time consuming and operator dependent. Automated segmentation as usually performed via single atlas registration fails to account for anatomo-physiological variability. We present, evaluate, and make available a multi-atlas approach for automatically segmenting rat brain MRI and extracting PET activies. Methods High-resolution 7T 2DT2 MR images of 12 Sprague-Dawley rat brains were manually segmented into 27-VOI label volumes using detailed protocols. Automated methods were developed with 7/12 atlas datasets, i.e. the MRIs and their associated label volumes. MRIs were registered to a common space, where an MRI template and a maximum probability atlas were created. Three automated methods were tested: 1/registering individual MRIs to the template, and using a single atlas (SA), 2/using the maximum probability atlas (MP), and 3/registering the MRIs from the multi-atlas dataset to an individual MRI, propagating the label volumes and fusing them in individual MRI space (propagation & fusion, PF). Evaluation was performed on the five remaining rats which additionally underwent [18F]FDG PET. Automated and manual segmentations were compared for morphometric performance (assessed by comparing volume bias and Dice overlap index) and functional performance (evaluated by comparing extracted PET measures). Results Only the SA method showed volume bias. Dice indices were significantly different between methods (PF>MP>SA). PET regional measures were more accurate with multi-atlas methods than with SA method. Conclusions Multi-atlas methods outperform SA for automated anatomical brain segmentation and PET measure’s extraction. They perform comparably to manual segmentation for FDG-PET quantification. Multi-atlas methods are suitable for rapid reproducible VOI analyses. PMID:25330005

  12. Comparative analysis of geodynamic activity of the Caucasian and Eastern Mediterranean segments of the Alpine-Himalayan convergence zone

    NASA Astrophysics Data System (ADS)

    Chelidze, Tamaz; Eppelbaum, Lev

    2013-04-01

    activity in this region highlights the need for combined analysis of seismo-neotectonic signatures. For this purpose, this article presents the key features of the tectonic zonation of the Eastern Mediterranean. Map of derivatives of the gravity field retracked from the Geosat satellite and novel map of the Moho discontinuity illustrate the most important tectonic features of the region. The Post-Jurassic map of the deformation of surface leveling reflects the modern tectonic stage of Eastern Mediterranean evolution. The developed tectono-geophysical zonation map integrates the potential geophysical field analysis and seismic section utilization, as well as tectonic-structural, paleogeographical and facial analyses. Tectonically the map agrees with the earlier model of continental accretion (Ben-Avraham and Ginzburg, 1990). Overlaying the seismicity map of the Eastern Mediterranean tectonic region (for the period between 1900 and 2012) on the tectonic zonation chart reveals the key features of the seismo-neotectonic pattern of the Eastern Mediterranean. The results have important implications for tectonic-seismological analysis in this region (Eppelbaum and Katz, 2012). A difference in the geotectonic patterns makes interesting comparison of geodynamic activity and seismic hazard of the Caucasian and Eastern Mediterranean segments of the AHCZ.

  13. Automatic Contour Detection Using a "Fixed-Point Hachimura-Kuwahara Filter" for SPECT Attenuation Correction.

    PubMed

    Minato, K; Tang, Y N; Bennett, G W; Brill, A

    1987-01-01

    Attenuation correction for single-photon emission computed tomography (SPECT) usually assumes a uniform attenuation distribution within the body surface contour. Previous methods to estimate this contour have used thresholding of a reconstructed section image. This method is often very sensitive to the selection of a threshold value, especially for nonuniform activity distributions within the body. We have proposed the "fixed-point Hachimura-Kuwahara filter" to extract contour primitives from SPECT images. The Hachimura-Kuwahara filter, which preserves edges but smoothes nonedge regions, is applied repeatedly to identify the invariant set-the fixed-point image-which is unchanged by this nonlinear, two-dimensional filtering operation. This image usually becomes a piecewise constant array. In order to detect the contour, the tracing algorithm based on the minimum distance connection criterion is applied to the extracted contour primitives. This procedure does not require choice of a threshold value in determining the contour. SPECT data from a water-filled elliptical phantom containing three sources was obtained and scattered projections were reconstructed. The automatic edge detection procedure was applied to the scattered window reconstruction, resulting in a reasonable outline of the phantom. PMID:18230438

  14. Automatic Endocardium Contour Tracing Method Using Standard Left Ventricles Shape Model

    NASA Astrophysics Data System (ADS)

    Horie, Masahiro; Kashima, Masayuki; Sato, Kiminori; Watanabe, Mutsumi

    The necessity of ultrasonic diagnosis tools increases every year. We propose an automatic endocardium tracing method by applying prepared “Standard Left Ventricles Shape Model (SLVSM)”. The cross section of heart wall in ultrasonic image is decided depending on the position and the angle of this probe. The initial contour is adaptively determined as crossing curve line between the SLVSM and the cross section. And the endocardium contour is extracted by active contour model(ACM) in two stages. In the first stage, an endocardium contour is detected using the result of an edge extraction based on the separability of image features. In the second stage, the endocardium contour is extracted using shape correction processing. “Mitral valve processing” not only detects the position of the mitral valve at the end diastolic period, but also corrects the detected contour after the first stage of ACM. Experimental results using one healthy case and three diseased cases have shown the effectiveness of the proposed method.

  15. Foreland segmentation along an active convergent margin: New constraints in southeastern Sicily (Italy) from seismic and geodetic observations

    NASA Astrophysics Data System (ADS)

    Musumeci, Carla; Scarfì, Luciano; Palano, Mimmo; Patanè, Domenico

    2014-09-01

    We performed an in-depth analysis of the ongoing tectonics of a large sector of southern Sicily, including the Hyblean Foreland and the front of the Maghrebian Chain, as well as the Ionian Sea offshore, through the integration of seismic and GPS observations collected in the nearly two decades. In particular, a dataset consisting of more than 1100 small-to moderate-magnitude earthquakes (1.0 ≤ ML ≤ 4.6) has been used for local earthquake tomography in order to trace the characteristics of the faulting systems, and for focal mechanisms computation to resolve the current local stress field and to characterise the faulting regime of the investigated area. In addition, GPS measurements, carried out on both episodic and continuous stations, allowed us to infer the main features of the current crustal deformation pattern. Main results evidence that the Hyblean Plateau is subject to a general strike-slip faulting regime, with a maximum horizontal stress axis NW-SE to NNW-SSE oriented, in agreement with the Eurasia-Nubia direction of convergence. The Plateau is separated into two different tectonic crustal blocks by the left-lateral strike-slip Scicli-Ragusa Fault System. The western block moves in agreement with central Sicily while the eastern one accommodates part of the contraction arising from the main Eurasia-Nubia convergence. Furthermore, we provided evidences leading to consider the Hyblean-Maltese Escarpment Fault System as an active boundary characterised by a left-lateral strike-slip motion, separating the eastern block of the Plateau from the Ionian basin. All these evidences lend credit to a crustal segmentation of the southeastern Sicily.

  16. 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.

  17. 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

  18. 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

  19. 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

  20. Semi-automatic geographic atrophy segmentation for SD-OCT images

    PubMed Central

    Chen, Qiang; de Sisternes, Luis; Leng, Theodore; Zheng, Luoluo; Kutzscher, Lauren; Rubin, Daniel L.

    2013-01-01

    Geographic atrophy (GA) is a condition that is associated with retinal thinning and loss of the retinal pigment epithelium (RPE) layer. It appears in advanced stages of non-exudative age-related macular degeneration (AMD) and can lead to vision loss. We present a semi-automated GA segmentation algorithm for spectral-domain optical coherence tomography (SD-OCT) images. The method first identifies and segments a surface between the RPE and the choroid to generate retinal projection images in which the projection region is restricted to a sub-volume of the retina where the presence of GA can be identified. Subsequently, a geometric active contour model is employed to automatically detect and segment the extent of GA in the projection images. Two image data sets, consisting on 55 SD-OCT scans from twelve eyes in eight patients with GA and 56 SD-OCT scans from 56 eyes in 56 patients with GA, respectively, were utilized to qualitatively and quantitatively evaluate the proposed GA segmentation method. Experimental results suggest that the proposed algorithm can achieve high segmentation accuracy. The mean GA overlap ratios between our proposed method and outlines drawn in the SD-OCT scans, our method and outlines drawn in the fundus auto-fluorescence (FAF) images, and the commercial software (Carl Zeiss Meditec proprietary software, Cirrus version 6.0) and outlines drawn in FAF images were 72.60%, 65.88% and 59.83%, respectively. PMID:24409376

  1. 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.

  2. A novel approach to motion correction for ASL images based on brain contours

    NASA Astrophysics Data System (ADS)

    Tarroni, Giacomo; Castellaro, Marco; Boffano, Carlo; Bruzzone, Maria Grazia; Bertoldo, Alessandra; Grisan, Enrico

    2015-03-01

    Motion correction in Arterial Spin Labeling (ASL) is essential to accurately assess brain perfusion. Motion correction techniques are usually based on intensity-related information, which might be unreliable in ASL due to local intensity differences between control and labeled acquisitions and to non-uniform volume magnetization caused by background-suppressed acquisition protocols. Accordingly, a novel motion correction technique based only on brain contour points is presented and tested against a widely used intensity-based technique (MCFLIRT). The proposed Contour-Based Motion Correction (CBCM) technique relies on image segmentation (to extract brain contour point clouds) and on Iterative Closest Point algorithm (to estimate the roto-translation required to align them). At variance with other approaches based on point clouds alignment, the local 3D curvature is also computed for each contour point and used as an additional coordinate to increase the accuracy of the alignment. The technique has been tested along with MCFLIRT on a database of randomly roto-translated brain volumes. Several error metrics have been computed and compared between the two techniques. The results show that the proposed technique is able to achieve a higher accuracy than MCFLIRT without any intensity-dependent information.

  3. 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 obj