WorldWideScience

Sample records for adaptive 3-d segmentation

  1. 3D segmentation of masses in DCE-MRI images using FCM and adaptive MRF

    Science.gov (United States)

    Zhang, Chengjie; Li, Lihua

    2014-03-01

    Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a sensitive imaging modality for the detection of breast cancer. Automated segmentation of breast lesions in DCE-MRI images is challenging due to inherent signal-to-noise ratios and high inter-patient variability. A novel 3D segmentation method based on FCM and MRF is proposed in this study. In this method, a MRI image is segmented by spatial FCM, firstly. And then MRF segmentation is conducted to refine the result. We combined with the 3D information of lesion in the MRF segmentation process by using segmentation result of contiguous slices to constraint the slice segmentation. At the same time, a membership matrix of FCM segmentation result is used for adaptive adjustment of Markov parameters in MRF segmentation process. The proposed method was applied for lesion segmentation on 145 breast DCE-MRI examinations (86 malignant and 59 benign cases). An evaluation of segmentation was taken using the traditional overlap rate method between the segmented region and hand-drawing ground truth. The average overlap rates for benign and malignant lesions are 0.764 and 0.755 respectively. Then we extracted five features based on the segmentation region, and used an artificial neural network (ANN) to classify between malignant and benign cases. The ANN had a classification performance measured by the area under the ROC curve of AUC=0.73. The positive and negative predictive values were 0.86 and 0.58, respectively. The results demonstrate the proposed method not only achieves a better segmentation performance in accuracy also has a reasonable classification performance.

  2. AN ADAPTIVE APPROACH FOR SEGMENTATION OF 3D LASER POINT CLOUD

    Directory of Open Access Journals (Sweden)

    Z. Lari

    2012-09-01

    Full Text Available Automatic processing and object extraction from 3D laser point cloud is one of the major research topics in the field of photogrammetry. Segmentation is an essential step in the processing of laser point cloud, and the quality of extracted objects from laser data is highly dependent on the validity of the segmentation results. This paper presents a new approach for reliable and efficient segmentation of planar patches from a 3D laser point cloud. In this method, the neighbourhood of each point is firstly established using an adaptive cylinder while considering the local point density and surface trend. This neighbourhood definition has a major effect on the computational accuracy of the segmentation attributes. In order to efficiently cluster planar surfaces and prevent introducing ambiguities, the coordinates of the origin's projection on each point's best fitted plane are used as the clustering attributes. Then, an octree space partitioning method is utilized to detect and extract peaks from the attribute space. Each detected peak represents a specific cluster of points which are located on a distinct planar surface in the object space. Experimental results show the potential and feasibility of applying this method for segmentation of both airborne and terrestrial laser data.

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

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    Abhau, Jochen; Scherzer, Otmar

    2008-03-01

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

  4. Spatio-Temporal Video Object Segmentation via Scale-Adaptive 3D Structure Tensor

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    Hai-Yun Wang

    2004-06-01

    Full Text Available To address multiple motions and deformable objects' motions encountered in existing region-based approaches, an automatic video object (VO segmentation methodology is proposed in this paper by exploiting the duality of image segmentation and motion estimation such that spatial and temporal information could assist each other to jointly yield much improved segmentation results. The key novelties of our method are (1 scale-adaptive tensor computation, (2 spatial-constrained motion mask generation without invoking dense motion-field computation, (3 rigidity analysis, (4 motion mask generation and selection, and (5 motion-constrained spatial region merging. Experimental results demonstrate that these novelties jointly contribute much more accurate VO segmentation both in spatial and temporal domains.

  5. Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm.

    Science.gov (United States)

    Onoma, D P; Ruan, S; Thureau, S; Nkhali, L; Modzelewski, R; Monnehan, G A; Vera, P; Gardin, I

    2014-12-01

    A segmentation algorithm based on the random walk (RW) method, called 3D-LARW, has been developed to delineate small tumors or tumors with a heterogeneous distribution of FDG on PET images. Based on the original algorithm of RW [1], we propose an improved approach using new parameters depending on the Euclidean distance between two adjacent voxels instead of a fixed one and integrating probability densities of labels into the system of linear equations used in the RW. These improvements were evaluated and compared with the original RW method, a thresholding with a fixed value (40% of the maximum in the lesion), an adaptive thresholding algorithm on uniform spheres filled with FDG and FLAB method, on simulated heterogeneous spheres and on clinical data (14 patients). On these three different data, 3D-LARW has shown better segmentation results than the original RW algorithm and the three other methods. As expected, these improvements are more pronounced for the segmentation of small or tumors having heterogeneous FDG uptake.

  6. 3D Structured Grid Adaptation

    Science.gov (United States)

    Banks, D. W.; Hafez, M. M.

    1996-01-01

    Grid adaptation for structured meshes is the art of using information from an existing, but poorly resolved, solution to automatically redistribute the grid points in such a way as to improve the resolution in regions of high error, and thus the quality of the solution. This involves: (1) generate a grid vis some standard algorithm, (2) calculate a solution on this grid, (3) adapt the grid to this solution, (4) recalculate the solution on this adapted grid, and (5) repeat steps 3 and 4 to satisfaction. Steps 3 and 4 can be repeated until some 'optimal' grid is converged to but typically this is not worth the effort and just two or three repeat calculations are necessary. They also may be repeated every 5-10 time steps for unsteady calculations.

  7. Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform

    Directory of Open Access Journals (Sweden)

    Shuo-Tsung Chen

    2015-01-01

    Full Text Available Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries. Results. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed. Conclusion. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.

  8. Hybrid segmentation framework for 3D medical image analysis

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    Chen, Ting; Metaxas, Dimitri N.

    2003-05-01

    Medical image segmentation is the process that defines the region of interest in the image volume. Classical segmentation methods such as region-based methods and boundary-based methods cannot make full use of the information provided by the image. In this paper we proposed a general hybrid framework for 3D medical image segmentation purposes. In our approach we combine the Gibbs Prior model, and the deformable model. First, Gibbs Prior models are applied onto each slice in a 3D medical image volume and the segmentation results are combined to a 3D binary masks of the object. Then we create a deformable mesh based on this 3D binary mask. The deformable model will be lead to the edge features in the volume with the help of image derived external forces. The deformable model segmentation result can be used to update the parameters for Gibbs Prior models. These methods will then work recursively to reach a global segmentation solution. The hybrid segmentation framework has been applied to images with the objective of lung, heart, colon, jaw, tumor, and brain. The experimental data includes MRI (T1, T2, PD), CT, X-ray, Ultra-Sound images. High quality results are achieved with relatively efficient time cost. We also did validation work using expert manual segmentation as the ground truth. The result shows that the hybrid segmentation may have further clinical use.

  9. Needle segmentation using 3D Hough transform in 3D TRUS guided prostate transperineal therapy

    International Nuclear Information System (INIS)

    Purpose: Prostate adenocarcinoma is the most common noncutaneous malignancy in American men with over 200 000 new cases diagnosed each year. Prostate interventional therapy, such as cryotherapy and brachytherapy, is an effective treatment for prostate cancer. Its success relies on the correct needle implant position. This paper proposes a robust and efficient needle segmentation method, which acts as an aid to localize the needle in three-dimensional (3D) transrectal ultrasound (TRUS) guided prostate therapy. Methods: The procedure of locating the needle in a 3D TRUS image is a three-step process. First, the original 3D ultrasound image containing a needle is cropped; the cropped image is then converted to a binary format based on its histogram. Second, a 3D Hough transform based needle segmentation method is applied to the 3D binary image in order to locate the needle axis. The position of the needle endpoint is finally determined by an optimal threshold based analysis of the intensity probability distribution. The overall efficiency is improved through implementing a coarse-fine searching strategy. The proposed method was validated in tissue-mimicking agar phantoms, chicken breast phantoms, and 3D TRUS patient images from prostate brachytherapy and cryotherapy procedures by comparison to the manual segmentation. The robustness of the proposed approach was tested by means of varying parameters such as needle insertion angle, needle insertion length, binarization threshold level, and cropping size. Results: The validation results indicate that the proposed Hough transform based method is accurate and robust, with an achieved endpoint localization accuracy of 0.5 mm for agar phantom images, 0.7 mm for chicken breast phantom images, and 1 mm for in vivo patient cryotherapy and brachytherapy images. The mean execution time of needle segmentation algorithm was 2 s for a 3D TRUS image with size of 264 × 376 × 630 voxels. Conclusions: The proposed needle segmentation

  10. 3D surface analysis and classification in neuroimaging segmentation.

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    Zagar, Martin; Mlinarić, Hrvoje; Knezović, Josip

    2011-06-01

    This work emphasizes new algorithms for 3D edge and corner detection used in surface extraction and new concept of image segmentation in neuroimaging based on multidimensional shape analysis and classification. We propose using of NifTI standard for describing input data which enables interoperability and enhancement of existing computing tools used widely in neuroimaging research. In methods section we present our newly developed algorithm for 3D edge and corner detection, together with the algorithm for estimating local 3D shape. Surface of estimated shape is analyzed and segmented according to kernel shapes. PMID:21755723

  11. Adaptive interrogation for 3D-PIV

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    Novara, Matteo; Ianiro, Andrea; Scarano, Fulvio

    2013-02-01

    A method to adapt the shape and orientation of interrogation volumes for 3D-PIV motion analysis is introduced, aimed to increase the local spatial resolution. The main application of this approach is the detailed analysis of complex 3D and vortex-dominated flows that exhibit high vorticity in confined regions like shear layers and vortex filaments. The adaptive criterion is based on the analysis of the components of the local velocity gradient tensor, which returns the level of anisotropy of velocity spatial fluctuations. The principle to increase the local spatial resolution is based on the deformation of spherical isotropic interrogation regions, obtained by means of Gaussian weighting, into ellipsoids, with free choice of the principal axes and their directions. The interrogation region is contracted in the direction of the maximum velocity variation and elongated in the minimum one in order to maintain a constant interrogation volume. The adaptivity technique for three-dimensional PIV data takes advantage of the 3D topology of the flow, allowing increasing the spatial resolution not only in the case of shear layers, but also for vortex filaments, which is not possible for two-dimensional measurement in the plane normal to the vortex axis. The definition of the ellipsoidal interrogation region semi-axes is based on the singular values and singular directions of the local velocity gradient tensor as obtained by the singular values decomposition technique (SVD). The working principle is verified making use of numerical simulations of a shear layer and of a vortex filament. The application of the technique to data from a Tomo-PIV experiment conducted on a round jet, shows that the resolution of the shear layer at the jet exit can be considerably improved and an increase of about 25% in the vorticity peak is attained when the adaptive approach is applied. On the other hand, the peak vorticity description in the core of vortex rings is only slightly improved with

  12. 3D Surface Analysis and Classification in Neuroimaging Segmentation

    OpenAIRE

    Žagar, Martin; Mlinarić, Hrvoje; Knezović, Josip

    2011-01-01

    This work emphasizes new algorithms for 3D edge and corner detection used in surface extraction and new concept of image segmentation in neuroimaging based on multidimensional shape analysis and classification. We propose using of NifTI standard for describing input data which enables interoperability and enhancement of existing computing tools used widely in neuroimaging research. In methods section we present our newly developed algorithm for 3D edge and corner detection, togeth...

  13. 3D Medical Image Segmentation Based on Rough Set Theory

    Institute of Scientific and Technical Information of China (English)

    CHEN Shi-hao; TIAN Yun; WANG Yi; HAO Chong-yang

    2007-01-01

    This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI (region of interest) when there are multiple types of expert knowledge. Based on rough set theory, the image can be split into three regions:positive regions; negative regions; boundary regions. With multiple knowledge we refine ROI as an intersection of all of the expected shapes with single knowledge. At last we show the results of implementing a rough 3D image segmentation and visualization system.

  14. Needle segmentation using 3D Hough transform in 3D TRUS guided prostate transperineal therapy

    Energy Technology Data Exchange (ETDEWEB)

    Qiu Wu [Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Imaging Research Laboratories, Robarts Research Institute, Western University, London, Ontario N6A 5K8 (Canada); Yuchi Ming; Ding Mingyue [Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074 (China); Tessier, David; Fenster, Aaron [Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario N6A 5K8 (Canada)

    2013-04-15

    Purpose: Prostate adenocarcinoma is the most common noncutaneous malignancy in American men with over 200 000 new cases diagnosed each year. Prostate interventional therapy, such as cryotherapy and brachytherapy, is an effective treatment for prostate cancer. Its success relies on the correct needle implant position. This paper proposes a robust and efficient needle segmentation method, which acts as an aid to localize the needle in three-dimensional (3D) transrectal ultrasound (TRUS) guided prostate therapy. Methods: The procedure of locating the needle in a 3D TRUS image is a three-step process. First, the original 3D ultrasound image containing a needle is cropped; the cropped image is then converted to a binary format based on its histogram. Second, a 3D Hough transform based needle segmentation method is applied to the 3D binary image in order to locate the needle axis. The position of the needle endpoint is finally determined by an optimal threshold based analysis of the intensity probability distribution. The overall efficiency is improved through implementing a coarse-fine searching strategy. The proposed method was validated in tissue-mimicking agar phantoms, chicken breast phantoms, and 3D TRUS patient images from prostate brachytherapy and cryotherapy procedures by comparison to the manual segmentation. The robustness of the proposed approach was tested by means of varying parameters such as needle insertion angle, needle insertion length, binarization threshold level, and cropping size. Results: The validation results indicate that the proposed Hough transform based method is accurate and robust, with an achieved endpoint localization accuracy of 0.5 mm for agar phantom images, 0.7 mm for chicken breast phantom images, and 1 mm for in vivo patient cryotherapy and brachytherapy images. The mean execution time of needle segmentation algorithm was 2 s for a 3D TRUS image with size of 264 Multiplication-Sign 376 Multiplication-Sign 630 voxels. Conclusions

  15. Calculation of prestressed anchor segment by 3D infiniteelement

    Institute of Scientific and Technical Information of China (English)

    Yanfen WANG; Hongyang XIE; Yuanhan WANG

    2009-01-01

    Based on 1D infinite element theory, the coordinate transformation and shape function of 3D point-radiation 4-node infinite elements were derived.They were coupled with 8-node finite elements to compute the compressive deformation of the prestressed anchor segment. The results indicate that when the prestressed force acts on the anchor segment, the stresses and displacements in the rock around the anchor segment are concentrated in the zone center with the anchor axis and are subjected to exponential decay. Therefore, the stresses and the displacement spindles are formed. The calculation results of the infinite element are close to the theoretical results.

  16. Quality assessment of adaptive 3D video streaming

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    Tavakoli, Samira; Gutiérrez, Jesús; García, Narciso

    2013-03-01

    The streaming of 3D video contents is currently a reality to expand the user experience. However, because of the variable bandwidth of the networks used to deliver multimedia content, a smooth and high-quality playback experience could not always be guaranteed. Using segments in multiple video qualities, HTTP adaptive streaming (HAS) of video content is a relevant advancement with respect to classic progressive download streaming. Mainly, it allows resolving these issues by offering significant advantages in terms of both user-perceived Quality of Experience (QoE) and resource utilization for content and network service providers. In this paper we discuss the impact of possible HAS client's behavior while adapting to the network capacity on enduser. This has been done through an experiment of testing the end-user response to the quality variation during the adaptation procedure. The evaluation has been carried out through a subjective test of the end-user response to various possible clients' behaviors for increasing, decreasing, and oscillation of quality in 3D video. In addition, some of the HAS typical impairments during the adaptation has been simulated and their effects on the end-user perception are assessed. The experimental conclusions have made good insight into the user's response to different adaptation scenarios and visual impairments causing the visual discomfort that can be used to develop the adaptive streaming algorithm to improve the end-user experience.

  17. Chest wall segmentation in automated 3D breast ultrasound scans.

    Science.gov (United States)

    Tan, Tao; Platel, Bram; Mann, Ritse M; Huisman, Henkjan; Karssemeijer, Nico

    2013-12-01

    In this paper, we present an automatic method to segment the chest wall in automated 3D breast ultrasound images. Determining the location of the chest wall in automated 3D breast ultrasound images is necessary in computer-aided detection systems to remove automatically detected cancer candidates beyond the chest wall and it can be of great help for inter- and intra-modal image registration. We show that the visible part of the chest wall in an automated 3D breast ultrasound image can be accurately modeled by a cylinder. We fit the surface of our cylinder model to a set of automatically detected rib-surface points. The detection of the rib-surface points is done by a classifier using features representing local image intensity patterns and presence of rib shadows. Due to attenuation of the ultrasound signal, a clear shadow is visible behind the ribs. Evaluation of our segmentation method is done by computing the distance of manually annotated rib points to the surface of the automatically detected chest wall. We examined the performance on images obtained with the two most common 3D breast ultrasound devices in the market. In a dataset of 142 images, the average mean distance of the annotated points to the segmented chest wall was 5.59 ± 3.08 mm. PMID:23273891

  18. Chest wall segmentation in automated 3D breast ultrasound scans.

    Science.gov (United States)

    Tan, Tao; Platel, Bram; Mann, Ritse M; Huisman, Henkjan; Karssemeijer, Nico

    2013-12-01

    In this paper, we present an automatic method to segment the chest wall in automated 3D breast ultrasound images. Determining the location of the chest wall in automated 3D breast ultrasound images is necessary in computer-aided detection systems to remove automatically detected cancer candidates beyond the chest wall and it can be of great help for inter- and intra-modal image registration. We show that the visible part of the chest wall in an automated 3D breast ultrasound image can be accurately modeled by a cylinder. We fit the surface of our cylinder model to a set of automatically detected rib-surface points. The detection of the rib-surface points is done by a classifier using features representing local image intensity patterns and presence of rib shadows. Due to attenuation of the ultrasound signal, a clear shadow is visible behind the ribs. Evaluation of our segmentation method is done by computing the distance of manually annotated rib points to the surface of the automatically detected chest wall. We examined the performance on images obtained with the two most common 3D breast ultrasound devices in the market. In a dataset of 142 images, the average mean distance of the annotated points to the segmented chest wall was 5.59 ± 3.08 mm.

  19. NIHmagic: 3D visualization, registration, and segmentation tool

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    Freidlin, Raisa Z.; Ohazama, Chikai J.; Arai, Andrew E.; McGarry, Delia P.; Panza, Julio A.; Trus, Benes L.

    2000-05-01

    Interactive visualization of multi-dimensional biological images has revolutionized diagnostic and therapy planning. Extracting complementary anatomical and functional information from different imaging modalities provides a synergistic analysis capability for quantitative and qualitative evaluation of the objects under examination. We have been developing NIHmagic, a visualization tool for research and clinical use, on the SGI OnyxII Infinite Reality platform. Images are reconstructed into a 3D volume by volume rendering, a display technique that employs 3D texture mapping to provide a translucent appearance to the object. A stack of slices is rendered into a volume by an opacity mapping function, where the opacity is determined by the intensity of the voxel and its distance from the viewer. NIHmagic incorporates 3D visualization of time-sequenced images, manual registration of 2D slices, segmentation of anatomical structures, and color-coded re-mapping of intensities. Visualization of MIR, PET, CT, Ultrasound, and 3D reconstructed electron microscopy images has been accomplished using NIHmagic.

  20. Ultrafast superpixel segmentation of large 3D medical datasets

    Science.gov (United States)

    Leblond, Antoine; Kauffmann, Claude

    2016-03-01

    Even with recent hardware improvements, superpixel segmentation of large 3D medical images at interactive speed (cohesive, the fast Thread Group Shared Memory can be used and reused through a Gauss-Seidel like acceleration. The work unit partitioning scheme will however vary on odd- and even-numbered iterations to reduce convergence barriers. Synchronization will be ensured by an 8-step 3D variant of the traditional Red Black Ordering scheme. An attack model and early termination will also be described and implemented as additional acceleration techniques. Using our hybrid framework and typical operating parameters, we were able to compute the superpixels of a high-resolution 512x512x512 aortic angioCT scan in 283 ms using a AMD R9 290X GPU. We achieved a 22.3X speed-up factor compared to the published reference GPU implementation.

  1. Automated 3D renal segmentation based on image partitioning

    Science.gov (United States)

    Yeghiazaryan, Varduhi; Voiculescu, Irina D.

    2016-03-01

    Despite several decades of research into segmentation techniques, automated medical image segmentation is barely usable in a clinical context, and still at vast user time expense. This paper illustrates unsupervised organ segmentation through the use of a novel automated labelling approximation algorithm followed by a hypersurface front propagation method. The approximation stage relies on a pre-computed image partition forest obtained directly from CT scan data. We have implemented all procedures to operate directly on 3D volumes, rather than slice-by-slice, because our algorithms are dimensionality-independent. The results picture segmentations which identify kidneys, but can easily be extrapolated to other body parts. Quantitative analysis of our automated segmentation compared against hand-segmented gold standards indicates an average Dice similarity coefficient of 90%. Results were obtained over volumes of CT data with 9 kidneys, computing both volume-based similarity measures (such as the Dice and Jaccard coefficients, true positive volume fraction) and size-based measures (such as the relative volume difference). The analysis considered both healthy and diseased kidneys, although extreme pathological cases were excluded from the overall count. Such cases are difficult to segment both manually and automatically due to the large amplitude of Hounsfield unit distribution in the scan, and the wide spread of the tumorous tissue inside the abdomen. In the case of kidneys that have maintained their shape, the similarity range lies around the values obtained for inter-operator variability. Whilst the procedure is fully automated, our tools also provide a light level of manual editing.

  2. 3D GEOMARKETING SEGMENTATION: A HIGHER SPATIAL DIMENSION PLANNING PERSPECTIVE

    Directory of Open Access Journals (Sweden)

    A. Suhaibah

    2016-09-01

    Full Text Available Geomarketing is a discipline which uses geographic information in the process of planning and implementation of marketing activities. It can be used in any aspect of the marketing such as price, promotion or geo targeting. The analysis of geomarketing data use a huge data pool such as location residential areas, topography, it also analyzes demographic information such as age, genre, annual income and lifestyle. This information can help users to develop successful promotional campaigns in order to achieve marketing goals. One of the common activities in geomarketing is market segmentation. The segmentation clusters the data into several groups based on its geographic criteria. To refine the search operation during analysis, we proposed an approach to cluster the data using a clustering algorithm. However, with the huge data pool, overlap among clusters may happen and leads to inefficient analysis. Moreover, geomarketing is usually active in urban areas and requires clusters to be organized in a three-dimensional (3D way (i.e. multi-level shop lots, residential apartments. This is a constraint with the current Geographic Information System (GIS framework. To avoid this issue, we proposed a combination of market segmentation based on geographic criteria and clustering algorithm for 3D geomarketing data management. The proposed approach is capable in minimizing the overlap region during market segmentation. In this paper, geomarketing in urban area is used as a case study. Based on the case study, several locations of customers and stores in 3D are used in the test. The experiments demonstrated in this paper substantiated that the proposed approach is capable of minimizing overlapping segmentation and reducing repetitive data entries. The structure is also tested for retrieving the spatial records from the database. For marketing purposes, certain radius of point is used to analyzing marketing targets. Based on the presented tests in this paper

  3. Efficient segmentation of 3D fluoroscopic datasets from mobile C-arm

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    Styner, Martin A.; Talib, Haydar; Singh, Digvijay; Nolte, Lutz-Peter

    2004-05-01

    The emerging mobile fluoroscopic 3D technology linked with a navigation system combines the advantages of CT-based and C-arm-based navigation. The intra-operative, automatic segmentation of 3D fluoroscopy datasets enables the combined visualization of surgical instruments and anatomical structures for enhanced planning, surgical eye-navigation and landmark digitization. We performed a thorough evaluation of several segmentation algorithms using a large set of data from different anatomical regions and man-made phantom objects. The analyzed segmentation methods include automatic thresholding, morphological operations, an adapted region growing method and an implicit 3D geodesic snake method. In regard to computational efficiency, all methods performed within acceptable limits on a standard Desktop PC (30sec-5min). In general, the best results were obtained with datasets from long bones, followed by extremities. The segmentations of spine, pelvis and shoulder datasets were generally of poorer quality. As expected, the threshold-based methods produced the worst results. The combined thresholding and morphological operations methods were considered appropriate for a smaller set of clean images. The region growing method performed generally much better in regard to computational efficiency and segmentation correctness, especially for datasets of joints, and lumbar and cervical spine regions. The less efficient implicit snake method was able to additionally remove wrongly segmented skin tissue regions. This study presents a step towards efficient intra-operative segmentation of 3D fluoroscopy datasets, but there is room for improvement. Next, we plan to study model-based approaches for datasets from the knee and hip joint region, which would be thenceforth applied to all anatomical regions in our continuing development of an ideal segmentation procedure for 3D fluoroscopic images.

  4. Ultrafast superpixel segmentation of large 3D medical datasets

    Science.gov (United States)

    Leblond, Antoine; Kauffmann, Claude

    2016-03-01

    Even with recent hardware improvements, superpixel segmentation of large 3D medical images at interactive speed (<500 ms) remains a challenge. We will describe methods to achieve such performances using a GPU based hybrid framework implementing wavefront propagation and cellular automata resolution. Tasks will be scheduled in blocks (work units) using a wavefront propagation strategy, therefore allowing sparse scheduling. Because work units has been designed as spatially cohesive, the fast Thread Group Shared Memory can be used and reused through a Gauss-Seidel like acceleration. The work unit partitioning scheme will however vary on odd- and even-numbered iterations to reduce convergence barriers. Synchronization will be ensured by an 8-step 3D variant of the traditional Red Black Ordering scheme. An attack model and early termination will also be described and implemented as additional acceleration techniques. Using our hybrid framework and typical operating parameters, we were able to compute the superpixels of a high-resolution 512x512x512 aortic angioCT scan in 283 ms using a AMD R9 290X GPU. We achieved a 22.3X speed-up factor compared to the published reference GPU implementation.

  5. A spherical harmonics intensity model for 3D segmentation and 3D shape analysis of heterochromatin foci.

    Science.gov (United States)

    Eck, Simon; Wörz, Stefan; Müller-Ott, Katharina; Hahn, Matthias; Biesdorf, Andreas; Schotta, Gunnar; Rippe, Karsten; Rohr, Karl

    2016-08-01

    The genome is partitioned into regions of euchromatin and heterochromatin. The organization of heterochromatin is important for the regulation of cellular processes such as chromosome segregation and gene silencing, and their misregulation is linked to cancer and other diseases. We present a model-based approach for automatic 3D segmentation and 3D shape analysis of heterochromatin foci from 3D confocal light microscopy images. Our approach employs a novel 3D intensity model based on spherical harmonics, which analytically describes the shape and intensities of the foci. The model parameters are determined by fitting the model to the image intensities using least-squares minimization. To characterize the 3D shape of the foci, we exploit the computed spherical harmonics coefficients and determine a shape descriptor. We applied our approach to 3D synthetic image data as well as real 3D static and real 3D time-lapse microscopy images, and compared the performance with that of previous approaches. It turned out that our approach yields accurate 3D segmentation results and performs better than previous approaches. We also show that our approach can be used for quantifying 3D shape differences of heterochromatin foci. PMID:27037463

  6. Segmentation of 3D EBSD data for subgrain boundary identification and feature characterization.

    Science.gov (United States)

    Loeb, Andrew; Ferry, Michael; Bassman, Lori

    2016-02-01

    Subgrain structures formed during plastic deformation of metals can be observed by electron backscatter diffraction (EBSD) but are challenging to identify automatically. We have adapted a 2D image segmentation technique, fast multiscale clustering (FMC), to 3D EBSD data using a novel variance function to accommodate quaternion data. This adaptation, which has been incorporated into the free open source texture analysis software package MTEX, is capable of segmenting based on subtle and gradual variation as well as on sharp boundaries within the data. FMC has been further modified to group the resulting closed 3D segment boundaries into distinct coherent surfaces based on local normals of a triangulated surface. We demonstrate the excellent capabilities of this technique with application to 3D EBSD data sets generated from cold rolled aluminum containing well-defined microbands, cold rolled and partly recrystallized extra low carbon steel microstructure containing three magnitudes of boundary misorientations, and channel-die plane strain compressed Goss-oriented nickel crystal containing microbands with very subtle changes in orientation. PMID:26630071

  7. 3D+t brain MRI segmentation using robust 4D Hidden Markov Chain.

    Science.gov (United States)

    Lavigne, François; Collet, Christophe; Armspach, Jean-Paul

    2014-01-01

    In recent years many automatic methods have been developed to help physicians diagnose brain disorders, but the problem remains complex. In this paper we propose a method to segment brain structures on two 3D multi-modal MR images taken at different times (longitudinal acquisition). A bias field correction is performed with an adaptation of the Hidden Markov Chain (HMC) allowing us to take into account the temporal correlation in addition to spatial neighbourhood information. To improve the robustness of the segmentation of the principal brain structures and to detect Multiple Sclerosis Lesions as outliers the Trimmed Likelihood Estimator (TLE) is used during the process. The method is validated on 3D+t brain MR images. PMID:25571045

  8. Improving Semantic Updating Method on 3d City Models Using Hybrid Semantic-Geometric 3d Segmentation Technique

    Science.gov (United States)

    Sharkawi, K.-H.; Abdul-Rahman, A.

    2013-09-01

    to LoD4. The accuracy and structural complexity of the 3D objects increases with the LoD level where LoD0 is the simplest LoD (2.5D; Digital Terrain Model (DTM) + building or roof print) while LoD4 is the most complex LoD (architectural details with interior structures). Semantic information is one of the main components in CityGML and 3D City Models, and provides important information for any analyses. However, more often than not, the semantic information is not available for the 3D city model due to the unstandardized modelling process. One of the examples is where a building is normally generated as one object (without specific feature layers such as Roof, Ground floor, Level 1, Level 2, Block A, Block B, etc). This research attempts to develop a method to improve the semantic data updating process by segmenting the 3D building into simpler parts which will make it easier for the users to select and update the semantic information. The methodology is implemented for 3D buildings in LoD2 where the buildings are generated without architectural details but with distinct roof structures. This paper also introduces hybrid semantic-geometric 3D segmentation method that deals with hierarchical segmentation of a 3D building based on its semantic value and surface characteristics, fitted by one of the predefined primitives. For future work, the segmentation method will be implemented as part of the change detection module that can detect any changes on the 3D buildings, store and retrieve semantic information of the changed structure, automatically updates the 3D models and visualize the results in a userfriendly graphical user interface (GUI).

  9. 3D Printing device adaptable to Computer Numerical Control (CNC)

    OpenAIRE

    Gardan, Julien; DANESI, Frédéric; Roucoules, Lionel; Schneider, A

    2014-01-01

    This article presents the development of a 3D printing device for the additive manufacturing adapted to a CNC machining. The application involves the integration of a specific printing head. Additive manufacturing technology is most commonly used for modeling, prototyping, tooling through an exclusive machine or 3D printer. A global review and analysis of technologies show the additive manufacturing presents little independent solutions [6][9]. The problem studied especially the additive manu...

  10. Parameterization adaption for 3D shape optimization in aerodynamics

    Directory of Open Access Journals (Sweden)

    Badr Abou El Majd

    2013-10-01

    Full Text Available When solving a PDE problem numerically, a certain mesh-refinement process is always implicit, and very classically, mesh adaptivity is a very effective means to accelerate grid convergence. Similarly, when optimizing a shape by means of an explicit geometrical representation, it is natural to seek for an analogous concept of parameterization adaptivity. We propose here an adaptive parameterization for three-dimensional optimum design in aerodynamics by using the so-called “Free-Form Deformation” approach based on 3D tensorial Bézier parameterization. The proposed procedure leads to efficient numerical simulations with highly reduced computational costs.[How to cite this article:  Majd, B.A.. 2014. Parameterization adaption for 3D shape optimization in aerodynamics. International Journal of Science and Engineering, 6(1:61-69. Doi: 10.12777/ijse.6.1.61-69

  11. Blood Pool Segmentation Results in Superior Virtual Cardiac Models than Myocardial Segmentation for 3D Printing.

    Science.gov (United States)

    Farooqi, Kanwal M; Lengua, Carlos Gonzalez; Weinberg, Alan D; Nielsen, James C; Sanz, Javier

    2016-08-01

    The method of cardiac magnetic resonance (CMR) three-dimensional (3D) image acquisition and post-processing which should be used to create optimal virtual models for 3D printing has not been studied systematically. Patients (n = 19) who had undergone CMR including both 3D balanced steady-state free precession (bSSFP) imaging and contrast-enhanced magnetic resonance angiography (MRA) were retrospectively identified. Post-processing for the creation of virtual 3D models involved using both myocardial (MS) and blood pool (BP) segmentation, resulting in four groups: Group 1-bSSFP/MS, Group 2-bSSFP/BP, Group 3-MRA/MS and Group 4-MRA/BP. The models created were assessed by two raters for overall quality (1-poor; 2-good; 3-excellent) and ability to identify predefined vessels (1-5: superior vena cava, inferior vena cava, main pulmonary artery, ascending aorta and at least one pulmonary vein). A total of 76 virtual models were created from 19 patient CMR datasets. The mean overall quality scores for Raters 1/2 were 1.63 ± 0.50/1.26 ± 0.45 for Group 1, 2.12 ± 0.50/2.26 ± 0.73 for Group 2, 1.74 ± 0.56/1.53 ± 0.61 for Group 3 and 2.26 ± 0.65/2.68 ± 0.48 for Group 4. The numbers of identified vessels for Raters 1/2 were 4.11 ± 1.32/4.05 ± 1.31 for Group 1, 4.90 ± 0.46/4.95 ± 0.23 for Group 2, 4.32 ± 1.00/4.47 ± 0.84 for Group 3 and 4.74 ± 0.56/4.63 ± 0.49 for Group 4. Models created using BP segmentation (Groups 2 and 4) received significantly higher ratings than those created using MS for both overall quality and number of vessels visualized (p < 0.05), regardless of the acquisition technique. There were no significant differences between Groups 1 and 3. The ratings for Raters 1 and 2 had good correlation for overall quality (ICC = 0.63) and excellent correlation for the total number of vessels visualized (ICC = 0.77). The intra-rater reliability was good for Rater A (ICC = 0.65). Three models were successfully printed

  12. Blood Pool Segmentation Results in Superior Virtual Cardiac Models than Myocardial Segmentation for 3D Printing.

    Science.gov (United States)

    Farooqi, Kanwal M; Lengua, Carlos Gonzalez; Weinberg, Alan D; Nielsen, James C; Sanz, Javier

    2016-08-01

    The method of cardiac magnetic resonance (CMR) three-dimensional (3D) image acquisition and post-processing which should be used to create optimal virtual models for 3D printing has not been studied systematically. Patients (n = 19) who had undergone CMR including both 3D balanced steady-state free precession (bSSFP) imaging and contrast-enhanced magnetic resonance angiography (MRA) were retrospectively identified. Post-processing for the creation of virtual 3D models involved using both myocardial (MS) and blood pool (BP) segmentation, resulting in four groups: Group 1-bSSFP/MS, Group 2-bSSFP/BP, Group 3-MRA/MS and Group 4-MRA/BP. The models created were assessed by two raters for overall quality (1-poor; 2-good; 3-excellent) and ability to identify predefined vessels (1-5: superior vena cava, inferior vena cava, main pulmonary artery, ascending aorta and at least one pulmonary vein). A total of 76 virtual models were created from 19 patient CMR datasets. The mean overall quality scores for Raters 1/2 were 1.63 ± 0.50/1.26 ± 0.45 for Group 1, 2.12 ± 0.50/2.26 ± 0.73 for Group 2, 1.74 ± 0.56/1.53 ± 0.61 for Group 3 and 2.26 ± 0.65/2.68 ± 0.48 for Group 4. The numbers of identified vessels for Raters 1/2 were 4.11 ± 1.32/4.05 ± 1.31 for Group 1, 4.90 ± 0.46/4.95 ± 0.23 for Group 2, 4.32 ± 1.00/4.47 ± 0.84 for Group 3 and 4.74 ± 0.56/4.63 ± 0.49 for Group 4. Models created using BP segmentation (Groups 2 and 4) received significantly higher ratings than those created using MS for both overall quality and number of vessels visualized (p 3D printing. Desktop 3D printers can offer good quality printed models with accurate representation of anatomic detail.

  13. Hybrid Method for 3D Segmentation of Magnetic Resonance Images

    Institute of Scientific and Technical Information of China (English)

    ZHANGXiang; ZHANGDazhi; TIANJinwen; LIUJian

    2003-01-01

    Segmentation of some complex images, especially in magnetic resonance brain images, is often difficult to perform satisfactory results using only single approach of image segmentation. An approach towards the integration of several techniques seems to be the best solution. In this paper a new hybrid method for 3-dimension segmentation of the whole brain is introduced, based on fuzzy region growing, edge detection and mathematical morphology, The gray-level threshold, controlling the process of region growing, is determined by fuzzy technique. The image gradient feature is obtained by the 3-dimension sobel operator considering a 3×3×3 data block with the voxel to be evaluated at the center, while the gradient magnitude threshold is defined by the gradient magnitude histogram of brain magnetic resonance volume. By the combined methods of edge detection and region growing, the white matter volume of human brain is segmented perfectly. By the post-processing using mathematical morphological techniques, the whole brain region is obtained. In order to investigate the validity of the hybrid method, two comparative experiments, the region growing method using only gray-level feature and the thresholding method by combining gray-level and gradient features, are carried out. Experimental results indicate that the proposed method provides much better results than the traditional method using a single technique in the 3-dimension segmentation of human brain magnetic resonance data sets.

  14. Shape-driven 3D segmentation using spherical wavelets.

    Science.gov (United States)

    Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

    2006-01-01

    This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details. PMID:17354875

  15. Holoscopic 3D image depth estimation and segmentation techniques

    OpenAIRE

    Alazawi, Eman

    2015-01-01

    This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London Today’s 3D imaging techniques offer significant benefits over conventional 2D imaging techniques. The presence of natural depth information in the scene affords the observer an overall improved sense of reality and naturalness. A variety of systems attempting to reach this goal have been designed by many independent research groups, such as stereoscopic and auto-stereoscopic systems....

  16. Viewpoint-independent 3D object segmentation for randomly stacked objects using optical object detection

    International Nuclear Information System (INIS)

    This work proposes a novel approach to segmenting randomly stacked objects in unstructured 3D point clouds, which are acquired by a random-speckle 3D imaging system for the purpose of automated object detection and reconstruction. An innovative algorithm is proposed; it is based on a novel concept of 3D watershed segmentation and the strategies for resolving over-segmentation and under-segmentation problems. Acquired 3D point clouds are first transformed into a corresponding orthogonally projected depth map along the optical imaging axis of the 3D sensor. A 3D watershed algorithm based on the process of distance transformation is then performed to detect the boundary, called the edge dam, between stacked objects and thereby to segment point clouds individually belonging to two stacked objects. Most importantly, an object-matching algorithm is developed to solve the over- and under-segmentation problems that may arise during the watershed segmentation. The feasibility and effectiveness of the method are confirmed experimentally. The results reveal that the proposed method is a fast and effective scheme for the detection and reconstruction of a 3D object in a random stack of such objects. In the experiments, the precision of the segmentation exceeds 95% and the recall exceeds 80%. (paper)

  17. Multiscale 3-D shape representation and segmentation using spherical wavelets.

    Science.gov (United States)

    Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

    2007-04-01

    This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of

  18. Segmented Domain Decomposition Multigrid For 3-D Turbomachinery Flows

    Science.gov (United States)

    Celestina, M. L.; Adamczyk, J. J.; Rubin, S. G.

    2001-01-01

    A Segmented Domain Decomposition Multigrid (SDDMG) procedure was developed for three-dimensional viscous flow problems as they apply to turbomachinery flows. The procedure divides the computational domain into a coarse mesh comprised of uniformly spaced cells. To resolve smaller length scales such as the viscous layer near a surface, segments of the coarse mesh are subdivided into a finer mesh. This is repeated until adequate resolution of the smallest relevant length scale is obtained. Multigrid is used to communicate information between the different grid levels. To test the procedure, simulation results will be presented for a compressor and turbine cascade. These simulations are intended to show the ability of the present method to generate grid independent solutions. Comparisons with data will also be presented. These comparisons will further demonstrate the usefulness of the present work for they allow an estimate of the accuracy of the flow modeling equations independent of error attributed to numerical discretization.

  19. 3D Filament Network Segmentation with Multiple Active Contours

    Science.gov (United States)

    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. Extended 3D Line Segments from RGB-D Data for Pose Estimation

    DEFF Research Database (Denmark)

    Buch, Anders Glent; Jessen, Jeppe Barsøe; Kraft, Dirk;

    2013-01-01

    We propose a method for the extraction of complete and rich symbolic line segments in 3D based on RGB-D data. Edges are detected by combining cues from the RGB image and the aligned depth map. 3D line segments are then reconstructed by back-projecting 2D line segments and intersecting this with l...... this with local surface patches computed from the 3D point cloud. Different edge types are classified using the new enriched representation and the potential of this representation for the task of pose estimation is demonstrated....

  1. 3DSEM++: Adaptive and intelligent 3D SEM surface reconstruction.

    Science.gov (United States)

    Tafti, Ahmad P; Holz, Jessica D; Baghaie, Ahmadreza; Owen, Heather A; He, Max M; Yu, Zeyun

    2016-08-01

    Structural analysis of microscopic objects is a longstanding topic in several scientific disciplines, such as biological, mechanical, and materials sciences. The scanning electron microscope (SEM), as a promising imaging equipment has been around for decades to determine the surface properties (e.g., compositions or geometries) of specimens by achieving increased magnification, contrast, and resolution greater than one nanometer. Whereas SEM micrographs still remain two-dimensional (2D), many research and educational questions truly require knowledge and facts about their three-dimensional (3D) structures. 3D surface reconstruction from SEM images leads to remarkable understanding of microscopic surfaces, allowing informative and qualitative visualization of the samples being investigated. In this contribution, we integrate several computational technologies including machine learning, contrario methodology, and epipolar geometry to design and develop a novel and efficient method called 3DSEM++ for multi-view 3D SEM surface reconstruction in an adaptive and intelligent fashion. The experiments which have been performed on real and synthetic data assert the approach is able to reach a significant precision to both SEM extrinsic calibration and its 3D surface modeling.

  2. 3DSEM++: Adaptive and intelligent 3D SEM surface reconstruction.

    Science.gov (United States)

    Tafti, Ahmad P; Holz, Jessica D; Baghaie, Ahmadreza; Owen, Heather A; He, Max M; Yu, Zeyun

    2016-08-01

    Structural analysis of microscopic objects is a longstanding topic in several scientific disciplines, such as biological, mechanical, and materials sciences. The scanning electron microscope (SEM), as a promising imaging equipment has been around for decades to determine the surface properties (e.g., compositions or geometries) of specimens by achieving increased magnification, contrast, and resolution greater than one nanometer. Whereas SEM micrographs still remain two-dimensional (2D), many research and educational questions truly require knowledge and facts about their three-dimensional (3D) structures. 3D surface reconstruction from SEM images leads to remarkable understanding of microscopic surfaces, allowing informative and qualitative visualization of the samples being investigated. In this contribution, we integrate several computational technologies including machine learning, contrario methodology, and epipolar geometry to design and develop a novel and efficient method called 3DSEM++ for multi-view 3D SEM surface reconstruction in an adaptive and intelligent fashion. The experiments which have been performed on real and synthetic data assert the approach is able to reach a significant precision to both SEM extrinsic calibration and its 3D surface modeling. PMID:27200484

  3. 3D conformal planning using low segment multi-criteria IMRT optimization

    CERN Document Server

    Khan, Fazal

    2014-01-01

    Purpose: To evaluate automated multicriteria optimization (MCO)-- designed for intensity modulated radiation therapy (IMRT), but invoked with limited segmentation -- to efficiently produce high quality 3D conformal treatment (3D-CRT) plans. Methods: Ten patients previously planned with 3D-CRT were replanned with a low-segment inverse multicriteria optimized technique. The MCO-3D plans used the same number of beams, beam geometry and machine parameters of the corresponding 3D plans, but were limited to an energy of 6 MV. The MCO-3D plans were optimized using a fluence-based MCO IMRT algorithm and then, after MCO navigation, segmented with a low number of segments. The 3D and MCO-3D plans were compared by evaluating mean doses to individual organs at risk (OARs), mean doses to combined OARs, homogeneity indexes (HI), monitor units (MUs), physician preference, and qualitative assessments of planning time and plan customizability. Results: The MCO-3D plans significantly reduced the OAR mean doses and monitor unit...

  4. 3D Game Content Distributed Adaptation in Heterogeneous Environments

    Directory of Open Access Journals (Sweden)

    Berretty Robert-Paul

    2007-01-01

    Full Text Available Most current multiplayer 3D games can only be played on a single dedicated platform (a particular computer, console, or cell phone, requiring specifically designed content and communication over a predefined network. Below we show how, by using signal processing techniques such as multiresolution representation and scalable coding for all the components of a 3D graphics object (geometry, texture, and animation, we enable online dynamic content adaptation, and thus delivery of the same content over heterogeneous networks to terminals with very different profiles, and its rendering on them. We present quantitative results demonstrating how the best displayed quality versus computational complexity versus bandwidth tradeoffs have been achieved, given the distributed resources available over the end-to-end content delivery chain. Additionally, we use state-of-the-art, standardised content representation and compression formats (MPEG-4 AFX, JPEG 2000, XML, enabling deployment over existing infrastructure, while keeping hooks to well-established practices in the game industry.

  5. SEGMENTATION OF UAV-BASED IMAGES INCORPORATING 3D POINT CLOUD INFORMATION

    Directory of Open Access Journals (Sweden)

    A. Vetrivel

    2015-03-01

    Full Text Available Numerous applications related to urban scene analysis demand automatic recognition of buildings and distinct sub-elements. For example, if LiDAR data is available, only 3D information could be leveraged for the segmentation. However, this poses several risks, for instance, the in-plane objects cannot be distinguished from their surroundings. On the other hand, if only image based segmentation is performed, the geometric features (e.g., normal orientation, planarity are not readily available. This renders the task of detecting the distinct sub-elements of the building with similar radiometric characteristic infeasible. In this paper the individual sub-elements of buildings are recognized through sub-segmentation of the building using geometric and radiometric characteristics jointly. 3D points generated from Unmanned Aerial Vehicle (UAV images are used for inferring the geometric characteristics of roofs and facades of the building. However, the image-based 3D points are noisy, error prone and often contain gaps. Hence the segmentation in 3D space is not appropriate. Therefore, we propose to perform segmentation in image space using geometric features from the 3D point cloud along with the radiometric features. The initial detection of buildings in 3D point cloud is followed by the segmentation in image space using the region growing approach by utilizing various radiometric and 3D point cloud features. The developed method was tested using two data sets obtained with UAV images with a ground resolution of around 1-2 cm. The developed method accurately segmented most of the building elements when compared to the plane-based segmentation using 3D point cloud alone.

  6. 3D liver segmentation using multiple region appearances and graph cuts

    Energy Technology Data Exchange (ETDEWEB)

    Peng, Jialin, E-mail: 2004pjl@163.com; Zhang, Hongbo [College of Computer Science and Technology, Huaqiao University, Xiamen 361021 (China); Hu, Peijun; Lu, Fang; Kong, Dexing [College of Mathematics, Zhejiang University, Hangzhou 310027 (China); Peng, Zhiyi [Department of Radiology, First Affiliated Hospital, Zhejiang University, Hangzhou 310027 (China)

    2015-12-15

    Purpose: Efficient and accurate 3D liver segmentations from contrast-enhanced computed tomography (CT) images play an important role in therapeutic strategies for hepatic diseases. However, inhomogeneous appearances, ambiguous boundaries, and large variance in shape often make it a challenging task. The existence of liver abnormalities poses further difficulty. Despite the significant intensity difference, liver tumors should be segmented as part of the liver. This study aims to address these challenges, especially when the target livers contain subregions with distinct appearances. Methods: The authors propose a novel multiregion-appearance based approach with graph cuts to delineate the liver surface. For livers with multiple subregions, a geodesic distance based appearance selection scheme is introduced to utilize proper appearance constraint for each subregion. A special case of the proposed method, which uses only one appearance constraint to segment the liver, is also presented. The segmentation process is modeled with energy functions incorporating both boundary and region information. Rather than a simple fixed combination, an adaptive balancing weight is introduced and learned from training sets. The proposed method only calls initialization inside the liver surface. No additional constraints from user interaction are utilized. Results: The proposed method was validated on 50 3D CT images from three datasets, i.e., Medical Image Computing and Computer Assisted Intervention (MICCAI) training and testing set, and local dataset. On MICCAI testing set, the proposed method achieved a total score of 83.4 ± 3.1, outperforming nonexpert manual segmentation (average score of 75.0). When applying their method to MICCAI training set and local dataset, it yielded a mean Dice similarity coefficient (DSC) of 97.7% ± 0.5% and 97.5% ± 0.4%, respectively. These results demonstrated the accuracy of the method when applied to different computed tomography (CT) datasets

  7. Robust automatic high resolution segmentation of SOFC anode porosity in 3D

    DEFF Research Database (Denmark)

    Jørgensen, Peter Stanley; Bowen, Jacob R.

    2008-01-01

    anode in 3D. The technique is based on numerical approximations to partial differential equations to evolve a 3D surface to the desired phase boundary. Vector fields derived from the experimentally acquired data are used as the driving force. The automatic segmentation compared to manual delineation...

  8. 3D Fast Automatic Segmentation of Kidney Based on Modified AAM and Random Forest.

    Science.gov (United States)

    Jin, Chao; Shi, Fei; Xiang, Dehui; Jiang, Xueqing; Zhang, Bin; Wang, Ximing; Zhu, Weifang; Gao, Enting; Chen, Xinjian

    2016-06-01

    In this paper, a fully automatic method is proposed to segment the kidney into multiple components: renal cortex, renal column, renal medulla and renal pelvis, in clinical 3D CT abdominal images. The proposed fast automatic segmentation method of kidney consists of two main parts: localization of renal cortex and segmentation of kidney components. In the localization of renal cortex phase, a method which fully combines 3D Generalized Hough Transform (GHT) and 3D Active Appearance Models (AAM) is applied to localize the renal cortex. In the segmentation of kidney components phase, a modified Random Forests (RF) method is proposed to segment the kidney into four components based on the result from localization phase. During the implementation, a multithreading technology is applied to speed up the segmentation process. The proposed method was evaluated on a clinical abdomen CT data set, including 37 contrast-enhanced volume data using leave-one-out strategy. The overall true-positive volume fraction and false-positive volume fraction were 93.15%, 0.37% for renal cortex segmentation; 83.09%, 0.97% for renal column segmentation; 81.92%, 0.55% for renal medulla segmentation; and 80.28%, 0.30% for renal pelvis segmentation, respectively. The average computational time of segmenting kidney into four components took 20 seconds. PMID:26742124

  9. A method for the evaluation of thousands of automated 3D stem cell segmentations.

    Science.gov (United States)

    Bajcsy, P; Simon, M; Florczyk, S J; Simon, C G; Juba, D; Brady, M C

    2015-12-01

    There is no segmentation method that performs perfectly with any dataset in comparison to human segmentation. Evaluation procedures for segmentation algorithms become critical for their selection. The problems associated with segmentation performance evaluations and visual verification of segmentation results are exaggerated when dealing with thousands of three-dimensional (3D) image volumes because of the amount of computation and manual inputs needed. We address the problem of evaluating 3D segmentation performance when segmentation is applied to thousands of confocal microscopy images (z-stacks). Our approach is to incorporate experimental imaging and geometrical criteria, and map them into computationally efficient segmentation algorithms that can be applied to a very large number of z-stacks. This is an alternative approach to considering existing segmentation methods and evaluating most state-of-the-art algorithms. We designed a methodology for 3D segmentation performance characterization that consists of design, evaluation and verification steps. The characterization integrates manual inputs from projected surrogate 'ground truth' of statistically representative samples and from visual inspection into the evaluation. The novelty of the methodology lies in (1) designing candidate segmentation algorithms by mapping imaging and geometrical criteria into algorithmic steps, and constructing plausible segmentation algorithms with respect to the order of algorithmic steps and their parameters, (2) evaluating segmentation accuracy using samples drawn from probability distribution estimates of candidate segmentations and (3) minimizing human labour needed to create surrogate 'truth' by approximating z-stack segmentations with 2D contours from three orthogonal z-stack projections and by developing visual verification tools. We demonstrate the methodology by applying it to a dataset of 1253 mesenchymal stem cells. The cells reside on 10 different types of biomaterial

  10. Random Walk Based Segmentation for the Prostate on 3D Transrectal Ultrasound Images

    Science.gov (United States)

    Ma, Ling; Guo, Rongrong; Tian, Zhiqiang; Venkataraman, Rajesh; Sarkar, Saradwata; Liu, Xiabi; Nieh, Peter T.; Master, Viraj V.; Schuster, David M.; Fei, Baowei

    2016-01-01

    This paper proposes a new semi-automatic segmentation method for the prostate on 3D transrectal ultrasound images (TRUS) by combining the region and classification information. We use a random walk algorithm to express the region information efficiently and flexibly because it can avoid segmentation leakage and shrinking bias. We further use the decision tree as the classifier to distinguish the prostate from the non-prostate tissue because of its fast speed and superior performance, especially for a binary classification problem. Our segmentation algorithm is initialized with the user roughly marking the prostate and non-prostate points on the mid-gland slice which are fitted into an ellipse for obtaining more points. Based on these fitted seed points, we run the random walk algorithm to segment the prostate on the mid-gland slice. The segmented contour and the information from the decision tree classification are combined to determine the initial seed points for the other slices. The random walk algorithm is then used to segment the prostate on the adjacent slice. We propagate the process until all slices are segmented. The segmentation method was tested in 32 3D transrectal ultrasound images. Manual segmentation by a radiologist serves as the gold standard for the validation. The experimental results show that the proposed method achieved a Dice similarity coefficient of 91.37±0.05%. The segmentation method can be applied to 3D ultrasound-guided prostate biopsy and other applications.

  11. Segmentation of vertebral bodies in CT and MR images based on 3D deterministic models

    Science.gov (United States)

    Štern, Darko; Vrtovec, Tomaž; Pernuš, Franjo; Likar, Boštjan

    2011-03-01

    The evaluation of vertebral deformations is of great importance in clinical diagnostics and therapy of pathological conditions affecting the spine. Although modern clinical practice is oriented towards the computed tomography (CT) and magnetic resonance (MR) imaging techniques, as they can provide a detailed 3D representation of vertebrae, the established methods for the evaluation of vertebral deformations still provide only a two-dimensional (2D) geometrical description. Segmentation of vertebrae in 3D may therefore not only improve their visualization, but also provide reliable and accurate 3D measurements of vertebral deformations. In this paper we propose a method for 3D segmentation of individual vertebral bodies that can be performed in CT and MR images. Initialized with a single point inside the vertebral body, the segmentation is performed by optimizing the parameters of a 3D deterministic model of the vertebral body to achieve the best match of the model to the vertebral body in the image. The performance of the proposed method was evaluated on five CT (40 vertebrae) and five T2-weighted MR (40 vertebrae) spine images, among them five are normal and five are pathological. The results show that the proposed method can be used for 3D segmentation of vertebral bodies in CT and MR images and that the proposed model can describe a variety of vertebral body shapes. The method may be therefore used for initializing whole vertebra segmentation or reliably describing vertebral body deformations.

  12. 3-D Multiphase Segmentation of X-Ray Micro Computed Tomography Data of Geologic Materials

    Science.gov (United States)

    Tuller, M.; Kulkarni, R.; Fink, W.

    2011-12-01

    Advancements of noninvasive imaging methods such as X-Ray Computed Tomography (CT) led to a recent surge of applications in Geoscience. While substantial efforts and resources have been devoted to advance CT technology and micro-scale analysis, the development of a stable 3-D multiphase image segmentation method applicable to large datasets is lacking. To eliminate the need for wet/dry or dual energy scans, image alignment, and subtraction analysis, commonly applied in synchrotron X-Ray micro CT, a segmentation method based on a Bayesian Markov Random Field (MRF) framework amenable to true 3-D multiphase processing was developed and evaluated. Furthermore, several heuristic and deterministic combinatorial optimization schemes required to solve the labeling problem of the MRF image model were implemented and tested for computational efficiency and their impact on segmentation results. Test results for natural and artificial porous media datasets demonstrate great potential of the MRF image model for 3-D multiphase segmentation.

  13. Effects of CT image segmentation methods on the accuracy of long bone 3D reconstructions.

    Science.gov (United States)

    Rathnayaka, Kanchana; Sahama, Tony; Schuetz, Michael A; Schmutz, Beat

    2011-03-01

    An accurate and accessible image segmentation method is in high demand for generating 3D bone models from CT scan data, as such models are required in many areas of medical research. Even though numerous sophisticated segmentation methods have been published over the years, most of them are not readily available to the general research community. Therefore, this study aimed to quantify the accuracy of three popular image segmentation methods, two implementations of intensity thresholding and Canny edge detection, for generating 3D models of long bones. In order to reduce user dependent errors associated with visually selecting a threshold value, we present a new approach of selecting an appropriate threshold value based on the Canny filter. A mechanical contact scanner in conjunction with a microCT scanner was utilised to generate the reference models for validating the 3D bone models generated from CT data of five intact ovine hind limbs. When the overall accuracy of the bone model is considered, the three investigated segmentation methods generated comparable results with mean errors in the range of 0.18-0.24 mm. However, for the bone diaphysis, Canny edge detection and Canny filter based thresholding generated 3D models with a significantly higher accuracy compared to those generated through visually selected thresholds. This study demonstrates that 3D models with sub-voxel accuracy can be generated utilising relatively simple segmentation methods that are available to the general research community.

  14. 3D automatic liver segmentation using feature-constrained Mahalanobis distance in CT images.

    Science.gov (United States)

    Salman Al-Shaikhli, Saif Dawood; Yang, Michael Ying; Rosenhahn, Bodo

    2016-08-01

    Automatic 3D liver segmentation is a fundamental step in the liver disease diagnosis and surgery planning. This paper presents a novel fully automatic algorithm for 3D liver segmentation in clinical 3D computed tomography (CT) images. Based on image features, we propose a new Mahalanobis distance cost function using an active shape model (ASM). We call our method MD-ASM. Unlike the standard active shape model (ST-ASM), the proposed method introduces a new feature-constrained Mahalanobis distance cost function to measure the distance between the generated shape during the iterative step and the mean shape model. The proposed Mahalanobis distance function is learned from a public database of liver segmentation challenge (MICCAI-SLiver07). As a refinement step, we propose the use of a 3D graph-cut segmentation. Foreground and background labels are automatically selected using texture features of the learned Mahalanobis distance. Quantitatively, the proposed method is evaluated using two clinical 3D CT scan databases (MICCAI-SLiver07 and MIDAS). The evaluation of the MICCAI-SLiver07 database is obtained by the challenge organizers using five different metric scores. The experimental results demonstrate the availability of the proposed method by achieving an accurate liver segmentation compared to the state-of-the-art methods. PMID:26501155

  15. Automated 3D ultrasound image segmentation for assistant diagnosis of breast cancer

    Science.gov (United States)

    Wang, Yuxin; Gu, Peng; Lee, Won-Mean; Roubidoux, Marilyn A.; Du, Sidan; Yuan, Jie; Wang, Xueding; Carson, Paul L.

    2016-04-01

    Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer.

  16. Automated 3D ultrasound image segmentation to aid breast cancer image interpretation.

    Science.gov (United States)

    Gu, Peng; Lee, Won-Mean; Roubidoux, Marilyn A; Yuan, Jie; Wang, Xueding; Carson, Paul L

    2016-02-01

    Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer.

  17. 3D TEM reconstruction and segmentation process of laminar bio-nanocomposites

    Energy Technology Data Exchange (ETDEWEB)

    Iturrondobeitia, M., E-mail: maider.iturrondobeitia@ehu.es; Okariz, A.; Fernandez-Martinez, R.; Jimbert, P.; Guraya, T.; Ibarretxe, J. [eMERG, University of the Basque Country, Rafael Moreno Pitxitxi street 2 and 3, 48013, Bilbao (Spain)

    2015-03-30

    The microstructure of laminar bio-nanocomposites (Poly (lactic acid)(PLA)/clay) depends on the amount of clay platelet opening after integration with the polymer matrix and determines the final properties of the material. Transmission electron microscopy (TEM) technique is the only one that can provide a direct observation of the layer dispersion and the degree of exfoliation. However, the orientation of the clay platelets, which affects the final properties, is practically immeasurable from a single 2D TEM image. This issue can be overcome using transmission electron tomography (ET), a technique that allows the complete 3D characterization of the structure, including the measurement of the orientation of clay platelets, their morphology and their 3D distribution. ET involves a 3D reconstruction of the study volume and a subsequent segmentation of the study object. Currently, accurate segmentation is performed manually, which is inefficient and tedious. The aim of this work is to propose an objective/automated segmentation methodology process of a 3D TEM tomography reconstruction. In this method the segmentation threshold is optimized by minimizing the variation of the dimensions of the segmented objects and matching the segmented V{sub clay} (%) and the actual one. The method is first validated using a fictitious set of objects, and then applied on a nanocomposite.

  18. 3D automatic anatomy segmentation based on iterative graph-cut-ASM

    OpenAIRE

    Chen, Xinjian; Bagci, Ulas

    2011-01-01

    Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images.Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the...

  19. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

    International Nuclear Information System (INIS)

    different patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. Results: The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. Conclusions: A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images

  20. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Yanrong; Shao, Yeqin [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong; Price, True [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Computer Science, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Oto, Aytekin [Department of Radiology, Section of Urology, University of Chicago, Illinois 60637 (United States); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)

    2014-07-15

    different patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. Results: The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. Conclusions: A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images.

  1. 3D Segmentations of Neuronal Nuclei from Confocal Microscope Image Stacks

    Directory of Open Access Journals (Sweden)

    Antonio eLaTorre

    2013-12-01

    Full Text Available In this paper, we present an algorithm to create 3D segmentations of neuronal cells from stacks of previously segmented 2D images. The idea behind this proposal is to provide a general method to reconstruct 3D structures from 2D stacks, regardless of how these 2D stacks have been obtained. The algorithm not only reuses the information obtained in the 2D segmentation, but also attempts to correct some typical mistakes made by the 2D segmentation algorithms (for example, under segmentation of tightly-coupled clusters of cells. We have tested our algorithm in a real scenario --- the segmentation of the neuronal nuclei in different layers of the rat cerebral cortex. Several representative images from different layers of the cerebral cortex have been considered and several 2D segmentation algorithms have been compared. Furthermore, the algorithm has also been compared with the traditional 3D Watershed algorithm and the results obtained here show better performance in terms of correctly identified neuronal nuclei.

  2. A framework for automatic construction of 3D PDM from segmented volumetric neuroradiological data sets.

    Science.gov (United States)

    Fu, Yili; Gao, Wenpeng; Xiao, Yongfei; Liu, Jimin

    2010-03-01

    3D point distribution model (PDM) of subcortical structures can be applied in medical image analysis by providing priori-knowledge. However, accurate shape representation and point correspondence are still challenging for building 3D PDM. This paper presents a novel framework for the automated construction of 3D PDMs from a set of segmented volumetric images. First, a template shape is generated according to the spatial overlap. Then the corresponding landmarks among shapes are automatically identified by a novel hierarchical global-to-local approach, which combines iterative closest point based global registration and active surface model based local deformation to transform the template shape to all other shapes. Finally, a 3D PDM is constructed. Experiment results on four subcortical structures show that the proposed method is able to construct 3D PDMs with a high quality in compactness, generalization and specificity, and more efficient and effective than the state-of-art methods such as MDL and SPHARM. PMID:19631401

  3. Multi-camera sensor system for 3D segmentation and localization of multiple mobile robots.

    Science.gov (United States)

    Losada, Cristina; Mazo, Manuel; Palazuelos, Sira; Pizarro, Daniel; Marrón, Marta

    2010-01-01

    This paper presents a method for obtaining the motion segmentation and 3D localization of multiple mobile robots in an intelligent space using a multi-camera sensor system. The set of calibrated and synchronized cameras are placed in fixed positions within the environment (intelligent space). The proposed algorithm for motion segmentation and 3D localization is based on the minimization of an objective function. This function includes information from all the cameras, and it does not rely on previous knowledge or invasive landmarks on board the robots. The proposed objective function depends on three groups of variables: the segmentation boundaries, the motion parameters and the depth. For the objective function minimization, we use a greedy iterative algorithm with three steps that, after initialization of segmentation boundaries and depth, are repeated until convergence.

  4. Multi-Camera Sensor System for 3D Segmentation and Localization of Multiple Mobile Robots

    Directory of Open Access Journals (Sweden)

    Cristina Losada

    2010-04-01

    Full Text Available This paper presents a method for obtaining the motion segmentation and 3D localization of multiple mobile robots in an intelligent space using a multi-camera sensor system. The set of calibrated and synchronized cameras are placed in fixed positions within the environment (intelligent space. The proposed algorithm for motion segmentation and 3D localization is based on the minimization of an objective function. This function includes information from all the cameras, and it does not rely on previous knowledge or invasive landmarks on board the robots. The proposed objective function depends on three groups of variables: the segmentation boundaries, the motion parameters and the depth. For the objective function minimization, we use a greedy iterative algorithm with three steps that, after initialization of segmentation boundaries and depth, are repeated until convergence.

  5. Adaptive Kalman snake for semi-autonomous 3D vessel tracking.

    Science.gov (United States)

    Lee, Sang-Hoon; Lee, Sanghoon

    2015-10-01

    In this paper, we propose a robust semi-autonomous algorithm for 3D vessel segmentation and tracking based on an active contour model and a Kalman filter. For each computed tomography angiography (CTA) slice, we use the active contour model to segment the vessel boundary and the Kalman filter to track position and shape variations of the vessel boundary between slices. For successful segmentation via active contour, we select an adequate number of initial points from the contour of the first slice. The points are set manually by user input for the first slice. For the remaining slices, the initial contour position is estimated autonomously based on segmentation results of the previous slice. To obtain refined segmentation results, an adaptive control spacing algorithm is introduced into the active contour model. Moreover, a block search-based initial contour estimation procedure is proposed to ensure that the initial contour of each slice can be near the vessel boundary. Experiments were performed on synthetic and real chest CTA images. Compared with the well-known Chan-Vese (CV) model, the proposed algorithm exhibited better performance in segmentation and tracking. In particular, receiver operating characteristic analysis on the synthetic and real CTA images demonstrated the time efficiency and tracking robustness of the proposed model. In terms of computational time redundancy, processing time can be effectively reduced by approximately 20%.

  6. 3D segmentation of lung CT data with graph-cuts: analysis of parameter sensitivities

    Science.gov (United States)

    Cha, Jung won; Dunlap, Neal; Wang, Brian; Amini, Amir

    2016-03-01

    Lung boundary image segmentation is important for many tasks including for example in development of radiation treatment plans for subjects with thoracic malignancies. In this paper, we describe a method and parameter settings for accurate 3D lung boundary segmentation based on graph-cuts from X-ray CT data1. Even though previously several researchers have used graph-cuts for image segmentation, to date, no systematic studies have been performed regarding the range of parameter that give accurate results. The energy function in the graph-cuts algorithm requires 3 suitable parameter settings: K, a large constant for assigning seed points, c, the similarity coefficient for n-links, and λ, the terminal coefficient for t-links. We analyzed the parameter sensitivity with four lung data sets from subjects with lung cancer using error metrics. Large values of K created artifacts on segmented images, and relatively much larger value of c than the value of λ influenced the balance between the boundary term and the data term in the energy function, leading to unacceptable segmentation results. For a range of parameter settings, we performed 3D image segmentation, and in each case compared the results with the expert-delineated lung boundaries. We used simple 6-neighborhood systems for n-link in 3D. The 3D image segmentation took 10 minutes for a 512x512x118 ~ 512x512x190 lung CT image volume. Our results indicate that the graph-cuts algorithm was more sensitive to the K and λ parameter settings than to the C parameter and furthermore that amongst the range of parameters tested, K=5 and λ=0.5 yielded good results.

  7. 3D active surfaces for liver segmentation in multisequence MRI images.

    Science.gov (United States)

    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

  8. Parametric modelling and segmentation of vertebral bodies in 3D CT and MR spine images

    Science.gov (United States)

    Štern, Darko; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž

    2011-12-01

    Accurate and objective evaluation of vertebral deformations is of significant importance in clinical diagnostics and therapy of pathological conditions affecting the spine. Although modern clinical practice is focused on three-dimensional (3D) computed tomography (CT) and magnetic resonance (MR) imaging techniques, the established methods for evaluation of vertebral deformations are limited to measuring deformations in two-dimensional (2D) x-ray images. In this paper, we propose a method for quantitative description of vertebral body deformations by efficient modelling and segmentation of vertebral bodies in 3D. The deformations are evaluated from the parameters of a 3D superquadric model, which is initialized as an elliptical cylinder and then gradually deformed by introducing transformations that yield a more detailed representation of the vertebral body shape. After modelling the vertebral body shape with 25 clinically meaningful parameters and the vertebral body pose with six rigid body parameters, the 3D model is aligned to the observed vertebral body in the 3D image. The performance of the method was evaluated on 75 vertebrae from CT and 75 vertebrae from T2-weighted MR spine images, extracted from the thoracolumbar part of normal and pathological spines. The results show that the proposed method can be used for 3D segmentation of vertebral bodies in CT and MR images, as the proposed 3D model is able to describe both normal and pathological vertebral body deformations. The method may therefore be used for initialization of whole vertebra segmentation or for quantitative measurement of vertebral body deformations.

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

    Science.gov (United States)

    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

  10. Channeler Ant Model: 3 D segmentation of medical images through ant colonies

    International Nuclear Information System (INIS)

    In this paper the Channeler Ant Model (CAM) and some results of its application to the analysis of medical images are described. The CAM is an algorithm able to segment 3 D structures with different shapes, intensity and background. It makes use of virtual and colonies and exploits their natural capabilities to modify the environment and communicate with each other by pheromone deposition. Its performance has been validated with the segmentation of 3 D artificial objects and it has been already used successfully in lung nodules detection on Computer Tomography images. This work tries to evaluate the CAM as a candidate to solve the quantitative segmentation problem in Magnetic Resonance brain images: to evaluate the percentage of white matter, gray matter and cerebrospinal fluid in each voxel.

  11. How to Extract the Geometry and Topology from Very Large 3D Segmentations

    CERN Document Server

    Andres, Bjoern; Kroeger, Thorben; Hamprecht, Fred A

    2010-01-01

    Segmentation is often an essential intermediate step in image analysis. A volume segmentation characterizes the underlying volume image in terms of geometric information--segments, faces between segments, curves in which several faces meet--as well as a topology on these objects. Existing algorithms encode this information in designated data structures, but require that these data structures fit entirely in Random Access Memory (RAM). Today, 3D images with several billion voxels are acquired, e.g. in structural neurobiology. Since these large volumes can no longer be processed with existing methods, we present a new algorithm which performs geometry and topology extraction with a runtime linear in the number of voxels and log-linear in the number of faces and curves. The parallelizable algorithm proceeds in a block-wise fashion and constructs a consistent representation of the entire volume image on the hard drive, making the structure of very large volume segmentations accessible to image analysis. The paral...

  12. Framework for quantitative evaluation of 3D vessel segmentation approaches using vascular phantoms in conjunction with 3D landmark localization and registration

    Science.gov (United States)

    Wörz, Stefan; Hoegen, Philipp; Liao, Wei; Müller-Eschner, Matthias; Kauczor, Hans-Ulrich; von Tengg-Kobligk, Hendrik; Rohr, Karl

    2016-03-01

    We introduce a framework for quantitative evaluation of 3D vessel segmentation approaches using vascular phantoms. Phantoms are designed using a CAD system and created with a 3D printer, and comprise realistic shapes including branches and pathologies such as abdominal aortic aneurysms (AAA). To transfer ground truth information to the 3D image coordinate system, we use a landmark-based registration scheme utilizing fiducial markers integrated in the phantom design. For accurate 3D localization of the markers we developed a novel 3D parametric intensity model that is directly fitted to the markers in the images. We also performed a quantitative evaluation of different vessel segmentation approaches for a phantom of an AAA.

  13. A segmentation method for 3D visualization of neurons imaged with a confocal laser scanning microscope

    Science.gov (United States)

    Anderson, Jeffrey R.; Barrett, Steven F.; Wilcox, Michael J.

    2005-04-01

    Our understanding of the world around us is based primarily on three-dimensional information because of the environment in which we live and interact. Medical or biological image information is often collected in the form of two-dimensional, serial section images. As such, it is difficult for the observer to mentally reconstruct the three dimensional features of each object. Although many image rendering software packages allow for 3D views of the serial sections, they lack the ability to segment, or isolate different objects in the data set. Segmentation is the key to creating 3D renderings of distinct objects from serial slice images, like separate pieces to a puzzle. This paper describes a segmentation method for objects recorded with serial section images. The user defines threshold levels and object labels on a single image of the data set that are subsequently used to automatically segment each object in the remaining images of the same data set, while maintaining boundaries between contacting objects. The performance of the algorithm is verified using mathematically defined shapes. It is then applied to the visual neurons of the housefly, Musca domestica. Knowledge of the fly"s visual system may lead to improved machine visions systems. This effort has provided the impetus to develop this segmentation algorithm. The described segmentation method can be applied to any high contrast serial slice data set that is well aligned and registered. The medical field alone has many applications for rapid generation of 3D segmented models from MRI and other medical imaging modalities.

  14. Alzheimer's Disease Diagnostics by Adaptation of 3D Convolutional Network

    OpenAIRE

    Hosseini-Asl, Ehsan; Keynto, Robert; El-Baz, Ayman

    2016-01-01

    Early diagnosis, playing an important role in preventing progress and treating the Alzheimer\\{'}s disease (AD), is based on classification of features extracted from brain images. The features have to accurately capture main AD-related variations of anatomical brain structures, such as, e.g., ventricles size, hippocampus shape, cortical thickness, and brain volume. This paper proposed to predict the AD with a deep 3D convolutional neural network (3D-CNN), which can learn generic features capt...

  15. Fast Streaming 3D Level set Segmentation on the GPU for Smooth Multi-phase Segmentation

    DEFF Research Database (Denmark)

    Sharma, Ojaswa; Zhang, Qin; Anton, François;

    2011-01-01

    Level set method based segmentation provides an efficient tool for topological and geometrical shape handling, but it is slow due to high computational burden. In this work, we provide a framework for streaming computations on large volumetric images on the GPU. A streaming computational model...... allows processing large amounts of data with small memory footprint. Efficient transfer of data to and from the graphics hardware is performed via a memory manager. We show volumetric segmentation using a higher order, multi-phase level set method with speedups of the order of 5 times....

  16. Fully Automatic Method for 3D T1-Weighted Brain Magnetic Resonance Images Segmentation

    Directory of Open Access Journals (Sweden)

    Bouchaib Cherradi

    2011-05-01

    Full Text Available Accurate segmentation of brain MR images is of interest for many brain disorders. However, dueto several factors such noise, imaging artefacts, intrinsic tissue variation and partial volumeeffects, brain extraction and tissue segmentation remains a challenging task. So, in this paper, afull automatic method for segmentation of anatomical 3D brain MR images is proposed. Themethod consists of many steps. First, noise reduction by median filtering is done; secondsegmentation of brain/non-brain tissue is performed by using a Threshold Morphologic BrainExtraction method (TMBE. Then initial centroids estimation by gray level histogram analysis isexecuted, this stage yield to a Modified version of Fuzzy C-means Algorithm (MFCM that is usedfor MRI tissue segmentation. Finally 3D visualisation of the three clusters (CSF, GM and WM isperformed. The efficiency of the proposed method is demonstrated by extensive segmentationexperiments using simulated and real MR images. A confrontation of the method with similarmethods of the literature has been undertaken trough different performance measures. TheMFCM for tissue segmentation introduce a gain in rapidity of convergence of about 70%.

  17. Model based 3D segmentation and OCT image undistortion of percutaneous implants.

    Science.gov (United States)

    Müller, Oliver; Donner, Sabine; Klinder, Tobias; Dragon, Ralf; Bartsch, Ivonne; Witte, Frank; Krüger, Alexander; Heisterkamp, Alexander; Rosenhahn, Bodo

    2011-01-01

    Optical Coherence Tomography (OCT) is a noninvasive imaging technique which is used here for in vivo biocompatibility studies of percutaneous implants. A prerequisite for a morphometric analysis of the OCT images is the correction of optical distortions caused by the index of refraction in the tissue. We propose a fully automatic approach for 3D segmentation of percutaneous implants using Markov random fields. Refraction correction is done by using the subcutaneous implant base as a prior for model based estimation of the refractive index using a generalized Hough transform. Experiments show the competitiveness of our algorithm towards manual segmentations done by experts. PMID:22003731

  18. A Closed Form Solution to Segment 3D Motion Using Straight-line Optical Flow

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jing; SHI Fan-huai; MA Wen-juan; LIU Yun-cai

    2008-01-01

    A closed form solution to the problem of segmenting multiple 3D motion models was proposed fromstraight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.

  19. Intuitive Terrain Reconstruction Using Height Observation-Based Ground Segmentation and 3D Object Boundary Estimation

    Directory of Open Access Journals (Sweden)

    Sungdae Sim

    2012-12-01

    Full Text Available Mobile robot operators must make rapid decisions based on information about the robot’s surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot’s array of sensors, but some upper parts of objects are beyond the sensors’ measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances.

  20. Intuitive terrain reconstruction using height observation-based ground segmentation and 3D object boundary estimation.

    Science.gov (United States)

    Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

    2012-12-12

    Mobile robot operators must make rapid decisions based on information about the robot's surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot's array of sensors, but some upper parts of objects are beyond the sensors' measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances.

  1. A customized model for 3D human segmental kinematic coupling analysis by optoelectronic stereophotogrammetry

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The study of three-dimensional human kinematics has significant impacts on medical and healthcare technology innovations. As a non-invasive technology, optoelectronic stereophotogrammetry is widely used for in-vivo locomotor evaluations. However, relatively high testing difficulties, poor testing accuracies, and high analysis complexities prohibit its further employment. The objective of this study is to explore an improved modeling technique for quantitative measurement and analysis of human locomotion. Firstly, a 3D whole body model of 17 rigid segments was developed to describe human locomotion. Subsequently, a novel infrared reflective marker cluster for 17 body segments was constructed to calibrate and record the 3D segmental position and orientation of each functional body region simultaneously with high spatial accuracy. In addition, the novel calibration procedure and the conception of kinematic coupling of human locomotion were proposed to investigate the segmental functional characteristics of human motion. Eight healthy male subjects were evaluated with walking and running experiments using the Qualisys motion capture system. The experimental results demonstrated the followings: (i) The kinematic coupling of the upper limbs and the lower limbs both showed the significant characteristics of joint motion, while the torso motion of human possessed remarkable features of segmental motion; (ii) flexion/extension was the main motion feature in sagittal plane, while the lateral bending in coronal plane and the axial rotation in transverse plane were subsidiary motions during an entire walking cycle regarding to all the segments of the human body; (iii) compared with conventional methods, the improved techniques have a competitive advantage in the convenient measurement and accurate analysis of the segmental dynamic functional characteristics during human locomotion. The modeling technique proposed in this paper has great potentials in rehabilitation engineering

  2. Automated Segmentation of the Right Ventricle in 3D Echocardiography: A Kalman Filter State Estimation Approach.

    Science.gov (United States)

    Bersvendsen, Jorn; Orderud, Fredrik; Massey, Richard John; Fosså, Kristian; Gerard, Olivier; Urheim, Stig; Samset, Eigil

    2016-01-01

    As the right ventricle's (RV) role in cardiovascular diseases is being more widely recognized, interest in RV imaging, function and quantification is growing. However, there are currently few RV quantification methods for 3D echocardiography presented in the literature or commercially available. In this paper we propose an automated RV segmentation method for 3D echocardiographic images. We represent the RV geometry by a Doo-Sabin subdivision surface with deformation modes derived from a training set of manual segmentations. The segmentation is then represented as a state estimation problem and solved with an extended Kalman filter by combining the RV geometry with a motion model and edge detection. Validation was performed by comparing surface-surface distances, volumes and ejection fractions in 17 patients with aortic insufficiency between the proposed method, magnetic resonance imaging (MRI), and a manual echocardiographic reference. The algorithm was efficient with a mean computation time of 2.0 s. The mean absolute distances between the proposed and manual segmentations were 3.6 ± 0.7 mm. Good agreements of end diastolic volume, end systolic volume and ejection fraction with respect to MRI ( -26±24 mL , -16±26 mL and 0 ± 10%, respectively) and a manual echocardiographic reference (7 ± 30 mL, 13 ± 17 mL and -5±7% , respectively) were observed.

  3. Segmentation of Brain MRI Using SOM-FCM-Based Method and 3D Statistical Descriptors

    Directory of Open Access Journals (Sweden)

    Andrés Ortiz

    2013-01-01

    Full Text Available Current medical imaging systems provide excellent spatial resolution, high tissue contrast, and up to 65535 intensity levels. Thus, image processing techniques which aim to exploit the information contained in the images are necessary for using these images in computer-aided diagnosis (CAD systems. Image segmentation may be defined as the process of parcelling the image to delimit different neuroanatomical tissues present on the brain. In this paper we propose a segmentation technique using 3D statistical features extracted from the volume image. In addition, the presented method is based on unsupervised vector quantization and fuzzy clustering techniques and does not use any a priori information. The resulting fuzzy segmentation method addresses the problem of partial volume effect (PVE and has been assessed using real brain images from the Internet Brain Image Repository (IBSR.

  4. Stereo 3D vision adapter using commercial DIY goods

    Science.gov (United States)

    Sakamoto, Kunio; Ohara, Takashi

    2009-10-01

    The conventional display can show only one screen, but it is impossible to enlarge the size of a screen, for example twice. Meanwhile the mirror supplies us with the same image but this mirror image is usually upside down. Assume that the images on an original screen and a virtual screen in the mirror are completely different and both images can be displayed independently. It would be possible to enlarge a screen area twice. This extension method enables the observers to show the virtual image plane and to enlarge a screen area twice. Although the displaying region is doubled, this virtual display could not produce 3D images. In this paper, we present an extension method using a unidirectional diffusing image screen and an improvement for displaying a 3D image using orthogonal polarized image projection.

  5. A 3D neurovascular bundles segmentation method based on MR-TRUS deformable registration

    Science.gov (United States)

    Yang, Xiaofeng; Rossi, Peter; Jani, Ashesh B.; Mao, Hui; Ogunleye, Tomi; Curran, Walter J.; Liu, Tian

    2015-03-01

    In this paper, we propose a 3D neurovascular bundles (NVB) segmentation method for ultrasound (US) image by integrating MR and transrectal ultrasound (TRUS) images through MR-TRUS deformable registration. First, 3D NVB was contoured by a physician in MR images, and the 3D MRdefined NVB was then transformed into US images using a MR-TRUS registration method, which models the prostate tissue as an elastic material, and jointly estimates the boundary deformation and the volumetric deformations under the elastic constraint. This technique was validated with a clinical study of 6 patients undergoing radiation therapy (RT) treatment for prostate cancer. The accuracy of our approach was assessed through the locations of landmarks, as well as previous ultrasound Doppler images of patients. MR-TRUS registration was successfully performed for all patients. The mean displacement of the landmarks between the post-registration MR and TRUS images was less than 2 mm, and the average NVB volume Dice Overlap Coefficient was over 89%. This NVB segmentation technique could be a useful tool as we try to spare the NVB in prostate RT, monitor NVB response to RT, and potentially improve post-RT potency outcomes.

  6. 3D segmentation of medical images using a fast multistage hybrid algorithm

    International Nuclear Information System (INIS)

    In this paper, we propose a fast multistage hybrid algorithm for 3D segmentation of medical images. We first employ a morphological recursive erosion operation to reduce the connectivity between the object to be segmented and its neighborhood; then the fast marching method is used to greatly accelerate the initial propagation of a surface front from the user defined seed structure to a surface close to the desired boundary; a morphological reconstruction method then operates on this surface to achieve an initial segmentation result; and finally morphological recursive dilation is employed to recover any structure lost in the first stage of the algorithm. This approach is tested on 60 CT or MRI images of the brain, heart and urinary system, to demonstrate the robustness of this technique across a variety of imaging modalities and organ systems. The algorithm is also validated against datasets for which ''truth'' is known. These measurements revealed that the algorithm achieved a mean ''similarity index'' of 0.966 across the three organ systems. The execution time for this algorithm, when run on a 550 MHz Dual PIII-based PC runningWindows NT, and extracting the cortex from brain MRIs, the cardiac surface from dynamic CT, and the kidneys from 3D CT, was 38, 46 and 23 s, respectively. (orig.)

  7. Preliminary results in large bone segmentation from 3D freehand ultrasound

    Science.gov (United States)

    Fanti, Zian; Torres, Fabian; Arámbula Cosío, Fernando

    2013-11-01

    Computer Assisted Orthopedic Surgery (CAOS) requires a correct registration between the patient in the operating room and the virtual models representing the patient in the computer. In order to increase the precision and accuracy of the registration a set of new techniques that eliminated the need to use fiducial markers have been developed. The majority of these newly developed registration systems are based on costly intraoperative imaging systems like Computed Tomography (CT scan) or Magnetic resonance imaging (MRI). An alternative to these methods is the use of an Ultrasound (US) imaging system for the implementation of a more cost efficient intraoperative registration solution. In order to develop the registration solution with the US imaging system, the bone surface is segmented in both preoperative and intraoperative images, and the registration is done using the acquire surface. In this paper, we present the a preliminary results of a new approach to segment bone surface from ultrasound volumes acquired by means 3D freehand ultrasound. The method is based on the enhancement of the voxels that belongs to surface and its posterior segmentation. The enhancement process is based on the information provided by eigenanalisis of the multiscale 3D Hessian matrix. The preliminary results shows that from the enhance volume the final bone surfaces can be extracted using a singular value thresholding.

  8. 3D Finite Element Analysis of TBM Water Diversion Tunnel Segment Coupled with Seepage Field

    Institute of Scientific and Technical Information of China (English)

    钟登华; 胡能明; 程正飞; 吕鹏; 佟大威

    2016-01-01

    In most studies of tunnel boring machine(TBM)tunnelling, the groundwater pressure was not consid-ered, or was simplified and exerted on the boundary of lining structure. Meanwhile, the leakage, which mainly oc-curs in the segment joints, was often ignored in the relevant studies of TBM tunnelling. Additionally, the geological models in these studies were simplified to different extents, and mostly were simplified as homogenous bodies. Considering the deficiencies above, a 3D refined model of the surrounding rock of a tunnel is firstly established using NURBS-TIN-BReP hybrid data structure in this paper. Then the seepage field of the surrounding rock con-sidering the leakage in the segment joints is simulated. Finally, the stability of TBM water diversion tunnel is stud-ied coupled with the seepage simulation, to analyze the stress-strain conditions, the axial force and the bending moment of tunnel segment considering the leakage in the segment joints. The results illustrate that the maximum radial displacement, the minimum principal stress, the maximum principal stress and the axial force of segment lining considering the seepage effect are all larger than those disregarding the seepage effect.

  9. 3-D segmentation and quantitative analysis of inner and outer walls of thrombotic abdominal aortic aneurysms

    Science.gov (United States)

    Lee, Kyungmoo; Yin, Yin; Wahle, Andreas; Olszewski, Mark E.; Sonka, Milan

    2008-03-01

    An abdominal aortic aneurysm (AAA) is an area of a localized widening of the abdominal aorta, with a frequent presence of thrombus. A ruptured aneurysm can cause death due to severe internal bleeding. AAA thrombus segmentation and quantitative analysis are of paramount importance for diagnosis, risk assessment, and determination of treatment options. Until now, only a small number of methods for thrombus segmentation and analysis have been presented in the literature, either requiring substantial user interaction or exhibiting insufficient performance. We report a novel method offering minimal user interaction and high accuracy. Our thrombus segmentation method is composed of an initial automated luminal surface segmentation, followed by a cost function-based optimal segmentation of the inner and outer surfaces of the aortic wall. The approach utilizes the power and flexibility of the optimal triangle mesh-based 3-D graph search method, in which cost functions for thrombus inner and outer surfaces are based on gradient magnitudes. Sometimes local failures caused by image ambiguity occur, in which case several control points are used to guide the computer segmentation without the need to trace borders manually. Our method was tested in 9 MDCT image datasets (951 image slices). With the exception of a case in which the thrombus was highly eccentric, visually acceptable aortic lumen and thrombus segmentation results were achieved. No user interaction was used in 3 out of 8 datasets, and 7.80 +/- 2.71 mouse clicks per case / 0.083 +/- 0.035 mouse clicks per image slice were required in the remaining 5 datasets.

  10. 3D medical image segmentation based on a continuous modelling of the volume

    International Nuclear Information System (INIS)

    Several medical imaging/techniques, including Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) provide 3D information of the human body by means of a stack of parallel cross-sectional images. But a more sophisticated edge detection step has to be performed when the object under study is not well defined by its characteristic density or when an analytical knowledge of the surface of the object is useful for later processings. A new method for medical image segmentation has been developed: it uses the stability and differentiability properties of a continuous modelling of the 3D data. The idea is to build a system of Ordinary Differential Equations which the stable manifold is the surface of the object we are looking for. This technique has been applied to classical edge detection operators: threshold following, laplacian, gradient maximum in its direction. It can be used in 2D as well as in 3D and has been extended to seek particular points of the surface, such as local extrema. The major advantages of this method are as follows: the segmentation and boundary following steps are performed simultaneously, an analytical representation of the surface is obtained straightforwardly and complex objects in which branching problems may occur can be described automatically. Simulations on noisy synthetic images have induced a quantization step to test the sensitiveness to noise of our method with respect to each operator, and to study the influence of all the parameters. Last, this method has been applied to numerous real clinical exams: skull or femur images provided by CT, MR images of a cerebral tumor and of the ventricular system. These results show the reliability and the efficiency of this new method of segmentation

  11. 3D segmentation of liver, kidneys and spleen from CT images

    International Nuclear Information System (INIS)

    The clinicians often need to segment the abdominal organs for radiotherapy planning. Manual segmentation of these organs is very time-consuming, therefore automated methods are desired. We developed a semi-automatic segmentation method to outline liver, spleen and kidneys. It works on CT images without contrast intake that are acquired with a routine clinical protocol. From an initial surface around a user defined seed point, the segmentation of the organ is obtained by an active surface algorithm. Pre- and post-processing steps are used to adapt the general method for specific organs. The evaluation results show that the accuracy of our method is about 90%, which can be further improved with little manual editing, and that the precision is slightly higher than that of manual contouring. Our method is accurate, precise and fast enough to use in the clinical practice. (orig.)

  12. A 3-D Computational Study of a Variable Camber Continuous Trailing Edge Flap (VCCTEF) Spanwise Segment

    Science.gov (United States)

    Kaul, Upender K.; Nguyen, Nhan T.

    2015-01-01

    Results of a computational study carried out to explore the effects of various elastomer configurations joining spanwise contiguous Variable Camber Continuous Trailing Edge Flap (VCCTEF) segments are reported here. This research is carried out as a proof-of-concept study that will seek to push the flight envelope in cruise with drag optimization as the objective. The cruise conditions can be well off design such as caused by environmental conditions, maneuvering, etc. To handle these off-design conditions, flap deflection is used so when the flap is deflected in a given direction, the aircraft angle of attack changes accordingly to maintain a given lift. The angle of attack is also a design parameter along with the flap deflection. In a previous 2D study,1 the effect of camber was investigated and the results revealed some insight into the relative merit of various camber settings of the VCCTEF. The present state of the art has not advanced sufficiently to do a full 3-D viscous analysis of the whole NASA Generic Transport Model (GTM) wing with VCCTEF deployed with elastomers. Therefore, this study seeks to explore the local effects of three contiguous flap segments on lift and drag of a model devised here to determine possible trades among various flap deflections to achieve desired lift and drag results. Although this approach is an approximation, it provides new insights into the "local" effects of the relative deflections of the contiguous spanwise flap systems and various elastomer segment configurations. The present study is a natural extension of the 2-D study to assess these local 3-D effects. Design cruise condition at 36,000 feet at free stream Mach number of 0.797 and a mean aerodynamic chord (MAC) based Reynolds number of 30.734x10(exp 6) is simulated for an angle of attack (AoA) range of 0 to 6 deg. In the previous 2-D study, the calculations revealed that the parabolic arc camber (1x2x3) and circular arc camber (VCCTEF222) offered the best L

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

    Science.gov (United States)

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

    2014-03-01

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

  14. IMPROVING SEMANTIC UPDATING METHOD ON 3D CITY MODELS USING HYBRID SEMANTIC-GEOMETRIC 3D SEGMENTATION TECHNIQUE

    OpenAIRE

    Sharkawi, K.-H.; A. Abdul-Rahman

    2013-01-01

    Cities and urban areas entities such as building structures are becoming more complex as the modern human civilizations continue to evolve. The ability to plan and manage every territory especially the urban areas is very important to every government in the world. Planning and managing cities and urban areas based on printed maps and 2D data are getting insufficient and inefficient to cope with the complexity of the new developments in big cities. The emergence of 3D city models hav...

  15. Visualising, segmenting and analysing heterogenous glacigenic sediments using 3D x-ray CT.

    Science.gov (United States)

    Carr, Simon; Diggens, Lucy; Groves, John; O'Sullivan, Catherine; Marsland, Rhona

    2015-04-01

    , especially with regard to using such data to improve understanding of mechanisms of particle motion and fabric development during subglacial strain. In this study, we present detailed investigation of subglacial tills from the UK, Iceland and Poland, to explore the challenges in segmenting these highly variable sediment bodies for 3D microfabric analysis. A calibration study is reported to compare various approaches to CT data segmentation to manually segmented datasets, from which an optimal workflow is developed, using a combination of the WEKA Trainable Segmentation tool within ImageJ to segment the data, followed by object-based analysis using Blob3D. We then demonstrate the value of this analysis through the analysis of true 3D microfabric data from a Last Glacial Maximum till deposit located at Morston, North Norfolk. Seven undisturbed sediment samples were scanned and analysed using high-resolution 3D X-ray computed tomography. Large (~5,000 to ~16,000) populations of individual particles are objectively and systematically segmented and identified. These large datasets are then subject to detailed interrogation using bespoke code for analysing particle fabric within Matlab, including the application of fabric-tensor analysis, by which fabrics can be weighted and scaled by key variables such as size and shape. We will present initial findings from these datasets, focusing particularly on overcoming the methodological challenges of obtaining robust datasets of sediments with highly complex, mixed compositional sediments.

  16. TU-F-BRF-06: 3D Pancreas MRI Segmentation Using Dictionary Learning and Manifold Clustering

    International Nuclear Information System (INIS)

    Purpose: The recent advent of MRI guided radiotherapy machines has lent an exciting platform for soft tissue target localization during treatment. However, tools to efficiently utilize MRI images for such purpose have not been developed. Specifically, to efficiently quantify the organ motion, we develop an automated segmentation method using dictionary learning and manifold clustering (DLMC). Methods: Fast 3D HASTE and VIBE MR images of 2 healthy volunteers and 3 patients were acquired. A bounding box was defined to include pancreas and surrounding normal organs including the liver, duodenum and stomach. The first slice of the MRI was used for dictionary learning based on mean-shift clustering and K-SVD sparse representation. Subsequent images were iteratively reconstructed until the error is less than a preset threshold. The preliminarily segmentation was subject to the constraints of manifold clustering. The segmentation results were compared with the mean shift merging (MSM), level set (LS) and manual segmentation methods. Results: DLMC resulted in consistently higher accuracy and robustness than comparing methods. Using manual contours as the ground truth, the mean Dices indices for all subjects are 0.54, 0.56 and 0.67 for MSM, LS and DLMC, respectively based on the HASTE image. The mean Dices indices are 0.70, 0.77 and 0.79 for the three methods based on VIBE images. DLMC is clearly more robust on the patients with the diseased pancreas while LS and MSM tend to over-segment the pancreas. DLMC also achieved higher sensitivity (0.80) and specificity (0.99) combining both imaging techniques. LS achieved equivalent sensitivity on VIBE images but was more computationally inefficient. Conclusion: We showed that pancreas and surrounding normal organs can be reliably segmented based on fast MRI using DLMC. This method will facilitate both planning volume definition and imaging guidance during treatment

  17. Image intensity standardization in 3D rotational angiography and its application to vascular segmentation

    Science.gov (United States)

    Bogunović, Hrvoje; Radaelli, Alessandro G.; De Craene, Mathieu; Delgado, David; Frangi, Alejandro F.

    2008-03-01

    Knowledge-based vascular segmentation methods typically rely on a pre-built training set of segmented images, which is used to estimate the probability of each voxel to belong to a particular tissue. In 3D Rotational Angiography (3DRA) the same tissue can correspond to different intensity ranges depending on the imaging device, settings and contrast injection protocol. As a result, pre-built training sets do not apply to all images and the best segmentation results are often obtained when the training set is built specifically for each individual image. We present an Image Intensity Standardization (IIS) method designed to ensure a correspondence between specific tissues and intensity ranges common to every image that undergoes the standardization process. The method applies a piecewise linear transformation to the image that aligns the intensity histogram to the histogram taken as reference. The reference histogram has been selected from a high quality image not containing artificial objects such as coils or stents. This is a pre-processing step that allows employing a training set built on a limited number of standardized images for the segmentation of standardized images which were not part of the training set. The effectiveness of the presented IIS technique in combination with a well-validated knowledge-based vasculature segmentation method is quantified on a variety of 3DRA images depicting cerebral arteries and intracranial aneurysms. The proposed IIS method offers a solution to the standardization of tissue classes in routine medical images and effectively improves automation and usability of knowledge-based vascular segmentation algorithms.

  18. TU-F-BRF-06: 3D Pancreas MRI Segmentation Using Dictionary Learning and Manifold Clustering

    Energy Technology Data Exchange (ETDEWEB)

    Gou, S; Rapacchi, S; Hu, P; Sheng, K [UCLA School of Medicine, Los Angeles, CA (United States)

    2014-06-15

    Purpose: The recent advent of MRI guided radiotherapy machines has lent an exciting platform for soft tissue target localization during treatment. However, tools to efficiently utilize MRI images for such purpose have not been developed. Specifically, to efficiently quantify the organ motion, we develop an automated segmentation method using dictionary learning and manifold clustering (DLMC). Methods: Fast 3D HASTE and VIBE MR images of 2 healthy volunteers and 3 patients were acquired. A bounding box was defined to include pancreas and surrounding normal organs including the liver, duodenum and stomach. The first slice of the MRI was used for dictionary learning based on mean-shift clustering and K-SVD sparse representation. Subsequent images were iteratively reconstructed until the error is less than a preset threshold. The preliminarily segmentation was subject to the constraints of manifold clustering. The segmentation results were compared with the mean shift merging (MSM), level set (LS) and manual segmentation methods. Results: DLMC resulted in consistently higher accuracy and robustness than comparing methods. Using manual contours as the ground truth, the mean Dices indices for all subjects are 0.54, 0.56 and 0.67 for MSM, LS and DLMC, respectively based on the HASTE image. The mean Dices indices are 0.70, 0.77 and 0.79 for the three methods based on VIBE images. DLMC is clearly more robust on the patients with the diseased pancreas while LS and MSM tend to over-segment the pancreas. DLMC also achieved higher sensitivity (0.80) and specificity (0.99) combining both imaging techniques. LS achieved equivalent sensitivity on VIBE images but was more computationally inefficient. Conclusion: We showed that pancreas and surrounding normal organs can be reliably segmented based on fast MRI using DLMC. This method will facilitate both planning volume definition and imaging guidance during treatment.

  19. Segmentation, Reconstruction, and Analysis of Blood Thrombus Formation in 3D 2-Photon Microscopy Images

    Directory of Open Access Journals (Sweden)

    Xu Zhiliang

    2010-01-01

    Full Text Available We study the problem of segmenting, reconstructing, and analyzing the structure growth of thrombi (clots in blood vessels in vivo based on 2-photon microscopic image data. First, we develop an algorithm for segmenting clots in 3D microscopic images based on density-based clustering and methods for dealing with imaging artifacts. Next, we apply the union-of-balls (or alpha-shape algorithm to reconstruct the boundary of clots in 3D. Finally, we perform experimental studies and analysis on the reconstructed clots and obtain quantitative data of thrombus growth and structures. We conduct experiments on laser-induced injuries in vessels of two types of mice (the wild type and the type with low levels of coagulation factor VII and analyze and compare the developing clot structures based on their reconstructed clots from image data. The results we obtain are of biomedical significance. Our quantitative analysis of the clot composition leads to better understanding of the thrombus development, and is valuable to the modeling and verification of computational simulation of thrombogenesis.

  20. 3D Compressible Melt Transport with Mesh Adaptivity

    Science.gov (United States)

    Dannberg, J.; Heister, T.

    2015-12-01

    Melt generation and migration have been the subject of numerous investigations. However, their typical time and length scales are vastly different from mantle convection, and the material properties are highly spatially variable and make the problem strongly non-linear. These challenges make it difficult to study these processes in a unified framework and in three dimensions. We present our extension of the mantle convection code ASPECT that allows for solving additional equations describing the behavior of melt percolating through and interacting with a viscously deforming host rock. One particular advantage is ASPECT's adaptive mesh refinement, as the resolution can be increased in areas where melt is present and viscosity gradients are steep, whereas a lower resolution is sufficient in regions without melt. Our approach includes both melt migration and melt generation, allowing for different melting parametrizations. In contrast to previous formulations, we consider the individual compressibilities of the solid and fluid phases in addition to compaction flow. This ensures self-consistency when linking melt generation to processes in the deeper mantle, where the compressibility of the solid phase becomes more important. We evaluate the functionality and potential of this method using a series of benchmarks and applications, including solitary waves, magmatic shear bands and melt generation and transport in a rising mantle plume. We compare results of the compressible and incompressible formulation and find melt volume differences of up to 15%. Moreover, we demonstrate that adaptive mesh refinement has the potential to reduce the runtime of a computation by more than one order of magnitude. Our model of magma dynamics provides a framework for investigating links between the deep mantle and melt generation and migration. This approach could prove particularly useful applied to modeling the generation of komatiites or other melts originating in greater depths.

  1. 3-D Adaptive Sparsity Based Image Compression With Applications to Optical Coherence Tomography.

    Science.gov (United States)

    Fang, Leyuan; Li, Shutao; Kang, Xudong; Izatt, Joseph A; Farsiu, Sina

    2015-06-01

    We present a novel general-purpose compression method for tomographic images, termed 3D adaptive sparse representation based compression (3D-ASRC). In this paper, we focus on applications of 3D-ASRC for the compression of ophthalmic 3D optical coherence tomography (OCT) images. The 3D-ASRC algorithm exploits correlations among adjacent OCT images to improve compression performance, yet is sensitive to preserving their differences. Due to the inherent denoising mechanism of the sparsity based 3D-ASRC, the quality of the compressed images are often better than the raw images they are based on. Experiments on clinical-grade retinal OCT images demonstrate the superiority of the proposed 3D-ASRC over other well-known compression methods. PMID:25561591

  2. Pancreas segmentation from 3D abdominal CT images using patient-specific weighted subspatial probabilistic atlases

    Science.gov (United States)

    Karasawa, Kenichi; Oda, Masahiro; Hayashi, Yuichiro; Nimura, Yukitaka; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Rueckert, Daniel; Mori, Kensaku

    2015-03-01

    Abdominal organ segmentations from CT volumes are now widely used in the computer-aided diagnosis and surgery assistance systems. Among abdominal organs, the pancreas is especially difficult to segment because of its large individual differences of the shape and position. In this paper, we propose a new pancreas segmentation method from 3D abdominal CT volumes using patient-specific weighted-subspatial probabilistic atlases. First of all, we perform normalization of organ shapes in training volumes and an input volume. We extract the Volume Of Interest (VOI) of the pancreas from the training volumes and an input volume. We divide each training VOI and input VOI into some cubic regions. We use a nonrigid registration method to register these cubic regions of the training VOI to corresponding regions of the input VOI. Based on the registration results, we calculate similarities between each cubic region of the training VOI and corresponding region of the input VOI. We select cubic regions of training volumes having the top N similarities in each cubic region. We subspatially construct probabilistic atlases weighted by the similarities in each cubic region. After integrating these probabilistic atlases in cubic regions into one, we perform a rough-to-precise segmentation of the pancreas using the atlas. The results of the experiments showed that utilization of the training volumes having the top N similarities in each cubic region led good results of the pancreas segmentation. The Jaccard Index and the average surface distance of the result were 58.9% and 2.04mm on average, respectively.

  3. CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation.

    Science.gov (United States)

    Hodneland, Erlend; Kögel, Tanja; Frei, Dominik Michael; Gerdes, Hans-Hermann; Lundervold, Arvid

    2013-08-09

    : The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.

  4. 3D Compressible Melt Transport with Adaptive Mesh Refinement

    Science.gov (United States)

    Dannberg, Juliane; Heister, Timo

    2015-04-01

    Melt generation and migration have been the subject of numerous investigations, but their typical time and length-scales are vastly different from mantle convection, which makes it difficult to study these processes in a unified framework. The equations that describe coupled Stokes-Darcy flow have been derived a long time ago and they have been successfully implemented and applied in numerical models (Keller et al., 2013). However, modelling magma dynamics poses the challenge of highly non-linear and spatially variable material properties, in particular the viscosity. Applying adaptive mesh refinement to this type of problems is particularly advantageous, as the resolution can be increased in mesh cells where melt is present and viscosity gradients are high, whereas a lower resolution is sufficient in regions without melt. In addition, previous models neglect the compressibility of both the solid and the fluid phase. However, experiments have shown that the melt density change from the depth of melt generation to the surface leads to a volume increase of up to 20%. Considering these volume changes in both phases also ensures self-consistency of models that strive to link melt generation to processes in the deeper mantle, where the compressibility of the solid phase becomes more important. We describe our extension of the finite-element mantle convection code ASPECT (Kronbichler et al., 2012) that allows for solving additional equations describing the behaviour of silicate melt percolating through and interacting with a viscously deforming host rock. We use the original compressible formulation of the McKenzie equations, augmented by an equation for the conservation of energy. This approach includes both melt migration and melt generation with the accompanying latent heat effects. We evaluate the functionality and potential of this method using a series of simple model setups and benchmarks, comparing results of the compressible and incompressible formulation and

  5. Chest-wall segmentation in automated 3D breast ultrasound images using thoracic volume classification

    Science.gov (United States)

    Tan, Tao; van Zelst, Jan; Zhang, Wei; Mann, Ritse M.; Platel, Bram; Karssemeijer, Nico

    2014-03-01

    Computer-aided detection (CAD) systems are expected to improve effectiveness and efficiency of radiologists in reading automated 3D breast ultrasound (ABUS) images. One challenging task on developing CAD is to reduce a large number of false positives. A large amount of false positives originate from acoustic shadowing caused by ribs. Therefore determining the location of the chestwall in ABUS is necessary in CAD systems to remove these false positives. Additionally it can be used as an anatomical landmark for inter- and intra-modal image registration. In this work, we extended our previous developed chestwall segmentation method that fits a cylinder to automated detected rib-surface points and we fit the cylinder model by minimizing a cost function which adopted a term of region cost computed from a thoracic volume classifier to improve segmentation accuracy. We examined the performance on a dataset of 52 images where our previous developed method fails. Using region-based cost, the average mean distance of the annotated points to the segmented chest wall decreased from 7.57±2.76 mm to 6.22±2.86 mm.art.

  6. Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields.

    Directory of Open Access Journals (Sweden)

    Sean Robinson

    Full Text Available Organotypic, three dimensional (3D cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs. The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.

  7. Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields

    Science.gov (United States)

    Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi

    2015-01-01

    Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy. PMID:26630674

  8. 3D segmentation of rodent brain structures using hierarchical shape priors and deformable models.

    Science.gov (United States)

    Zhang, Shaoting; Huang, Junzhou; Uzunbas, Mustafa; Shen, Tian; Delis, Foteini; Huang, Xiaolei; Volkow, Nora; Thanos, Panayotis; Metaxas, Dimitris N

    2011-01-01

    In this paper, we propose a method to segment multiple rodent brain structures simultaneously. This method combines deformable models and hierarchical shape priors within one framework. The deformation module employs both gradient and appearance information to generate image forces to deform the shape. The shape prior module uses Principal Component Analysis to hierarchically model the multiple structures at both global and local levels. At the global level, the statistics of relative positions among different structures are modeled. At the local level, the shape statistics within each structure is learned from training samples. Our segmentation method adaptively employs both priors to constrain the intermediate deformation result. This prior constraint improves the robustness of the model and benefits the segmentation accuracy. Another merit of our prior module is that the size of the training data can be small, because the shape prior module models each structure individually and combines them using global statistics. This scheme can preserve shape details better than directly applying PCA on all structures. We use this method to segment rodent brain structures, such as the cerebellum, the left and right striatum, and the left and right hippocampus. The experiments show that our method works effectively and this hierarchical prior improves the segmentation performance. PMID:22003750

  9. 3D MR ventricle segmentation in pre-term infants with post-hemorrhagic ventricle dilation

    Science.gov (United States)

    Qiu, Wu; Yuan, Jing; Kishimoto, Jessica; Chen, Yimin; de Ribaupierre, Sandrine; Chiu, Bernard; Fenster, Aaron

    2015-03-01

    Intraventricular hemorrhage (IVH) or bleed within the brain is a common condition among pre-term infants that occurs in very low birth weight preterm neonates. The prognosis is further worsened by the development of progressive ventricular dilatation, i.e., post-hemorrhagic ventricle dilation (PHVD), which occurs in 10-30% of IVH patients. In practice, predicting PHVD accurately and determining if that specific patient with ventricular dilatation requires the ability to measure accurately ventricular volume. While monitoring of PHVD in infants is typically done by repeated US and not MRI, once the patient has been treated, the follow-up over the lifetime of the patient is done by MRI. While manual segmentation is still seen as a gold standard, it is extremely time consuming, and therefore not feasible in a clinical context, and it also has a large inter- and intra-observer variability. This paper proposes a segmentation algorithm to extract the cerebral ventricles from 3D T1- weighted MR images of pre-term infants with PHVD. The proposed segmentation algorithm makes use of the convex optimization technique combined with the learned priors of image intensities and label probabilistic map, which is built from a multi-atlas registration scheme. The leave-one-out cross validation using 7 PHVD patient T1 weighted MR images showed that the proposed method yielded a mean DSC of 89.7% +/- 4.2%, a MAD of 2.6 +/- 1.1 mm, a MAXD of 17.8 +/- 6.2 mm, and a VD of 11.6% +/- 5.9%, suggesting a good agreement with manual segmentations.

  10. 3D automatic anatomy segmentation based on iterative graph-cut-ASM

    International Nuclear Information System (INIS)

    Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images. Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al.[Proc. SPIE, 7259, 72590C1-72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine. Results: The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10 deg. and 0.03, and over all foot bones are about 3.5709 mm, 0.35 deg. and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and

  11. 3D automatic anatomy segmentation based on iterative graph-cut-ASM

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Xinjian; Bagci, Ulas [Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10 Room 1C515, Bethesda, Maryland 20892-1182 and Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xi' an 710071 (China); Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10 Room 1C515, Bethesda, Maryland 20892-1182 (United States)

    2011-08-15

    Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images. Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al.[Proc. SPIE, 7259, 72590C1-72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine. Results: The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10 deg. and 0.03, and over all foot bones are about 3.5709 mm, 0.35 deg. and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and

  12. Segmentation and Classification of Human Actions and Actor Characteristics with 3d Motion Data

    Directory of Open Access Journals (Sweden)

    S. Ali Etemad

    2012-08-01

    Full Text Available In this paper we have used 3D motion capture data with the aim of detecting and classifying specifichuman actions. In addition to recognition of basic action classes, actor styles and characteristics such asgender, age, and energy level have also been subject to classification. We have applied and compared threemain methods: nearest neighbour search, hidden Markov models, and artificial neural networks. Usingthese techniques, we have proposed exhaustive algorithms for detection of actions in a motion piece andsubsequently classifying the segmented actions and respective characteristics of the actors. We have testedthe methods for various sequences and compared the results for a comprehensive evaluation of each of theproposed techniques. Our findings can be largely used for general classification of human motion data formultimedia applications as well as sorting and classifying data sets of human motion data especially thoseacquired using visual marker-based motion capture systems such as the one employed in this research.

  13. Visualization of Segmented Structures in 3D Multimodal Medical Data Sets

    Directory of Open Access Journals (Sweden)

    HERGHELEGIU, P.

    2011-08-01

    Full Text Available The simultaneous inspection of images obtained using different medical scanning methods represents a common practice for accurate medical diagnosis. The term multimodality refers to multiple medical data sets obtained by scanning a patient with the same method at different time moments or with different scanning techniques. Recent research efforts in computer graphics have attempted to solve the problem of visualizing multimodal data in the same scene, for a better understanding of human anatomy or for pathology tracking. This paper proposes a method of integrating segmented structures from a contrast enhanced MRI sequence into the volume reconstructed from the slices of another MRI sequence obtained with different scanning parameters. A direct volume rendering (DVR approach is used to represent focus and context information from the 3D data. The presented approach aims to help physicians in understanding pathologies and in the process of accurate diagnosis establishment.

  14. Acquisition and automated 3-D segmentation of respiratory/cardiac-gated PET transmission images

    International Nuclear Information System (INIS)

    To evaluate the impact of respiratory motion on attenuation correction of cardiac PET data, we acquired and automatically segmented gated transmission data for a dog breathing on its own under gas anesthesia. Data were acquired for 20 min on a CTI/Siemens ECAT EXACT HR (47-slice) scanner configured for 12 gates in a static study, Two respiratory gates were obtained using data from a pneumatic bellows placed around the dog's chest, in conjunction with 6 cardiac gates from standard EKG gating. Both signals were directed to a LabVIEW-controlled Macintosh, which translated them into one of 12 gate addresses. The respiratory gating threshold was placed near end-expiration to acquire 6 cardiac-gated datasets at end-expiration and 6 cardiac-gated datasets during breaths. Breaths occurred about once every 10 sec and lasted about 1-1.5 sec. For each respiratory gate, data were summed over cardiac gates and torso and lung surfaces were segmented automatically using a differential 3-D edge detection algorithm. Three-dimensional visualizations showed that lung surfaces adjacent to the heart translated 9 mm inferiorly during breaths. Our results suggest that respiration-compensated attenuation correction is feasible with a modest amount of gated transmission data and is necessary for accurate quantitation of high-resolution gated cardiac PET data

  15. Electro-bending characterization of adaptive 3D fiber reinforced plastics based on shape memory alloys

    Science.gov (United States)

    Ashir, Moniruddoza; Hahn, Lars; Kluge, Axel; Nocke, Andreas; Cherif, Chokri

    2016-03-01

    The industrial importance of fiber reinforced plastics (FRPs) is growing steadily in recent years, which are mostly used in different niche products, has been growing steadily in recent years. The integration of sensors and actuators in FRP is potentially valuable for creating innovative applications and therefore the market acceptance of adaptive FRP is increasing. In particular, in the field of highly stressed FRP, structural integrated systems for continuous component parts monitoring play an important role. This presented work focuses on the electro-mechanical characterization of adaptive three-dimensional (3D)FRP with integrated textile-based actuators. Here, the friction spun hybrid yarn, consisting of shape memory alloy (SMA) in wire form as core, serves as an actuator. Because of the shape memory effect, the SMA-hybrid yarn returns to its original shape upon heating that also causes the deformation of adaptive 3D FRP. In order to investigate the influences of the deformation behavior of the adaptive 3D FRP, investigations in this research are varied according to the structural parameters such as radius of curvature of the adaptive 3D FRP, fabric types and number of layers of the fabric in the composite. Results show that reproducible deformations can be realized with adaptive 3D FRP and that structural parameters have a significant impact on the deformation capability.

  16. 3-D segmentation of retinal blood vessels in spectral-domain OCT volumes of the optic nerve head

    Science.gov (United States)

    Lee, Kyungmoo; Abràmoff, Michael D.; Niemeijer, Meindert; Garvin, Mona K.; Sonka, Milan

    2010-03-01

    Segmentation of retinal blood vessels can provide important information for detecting and tracking retinal vascular diseases including diabetic retinopathy, arterial hypertension, arteriosclerosis and retinopathy of prematurity (ROP). Many studies on 2-D segmentation of retinal blood vessels from a variety of medical images have been performed. However, 3-D segmentation of retinal blood vessels from spectral-domain optical coherence tomography (OCT) volumes, which is capable of providing geometrically accurate vessel models, to the best of our knowledge, has not been previously studied. The purpose of this study is to develop and evaluate a method that can automatically detect 3-D retinal blood vessels from spectral-domain OCT scans centered on the optic nerve head (ONH). The proposed method utilized a fast multiscale 3-D graph search to segment retinal surfaces as well as a triangular mesh-based 3-D graph search to detect retinal blood vessels. An experiment on 30 ONH-centered OCT scans (15 right eye scans and 15 left eye scans) from 15 subjects was performed, and the mean unsigned error in 3-D of the computer segmentations compared with the independent standard obtained from a retinal specialist was 3.4 +/- 2.5 voxels (0.10 +/- 0.07 mm).

  17. Complex adaptation-based LDR image rendering for 3D image reconstruction

    Science.gov (United States)

    Lee, Sung-Hak; Kwon, Hyuk-Ju; Sohng, Kyu-Ik

    2014-07-01

    A low-dynamic tone-compression technique is developed for realistic image rendering that can make three-dimensional (3D) images similar to realistic scenes by overcoming brightness dimming in the 3D display mode. The 3D surround provides varying conditions for image quality, illuminant adaptation, contrast, gamma, color, sharpness, and so on. In general, gain/offset adjustment, gamma compensation, and histogram equalization have performed well in contrast compression; however, as a result of signal saturation and clipping effects, image details are removed and information is lost on bright and dark areas. Thus, an enhanced image mapping technique is proposed based on space-varying image compression. The performance of contrast compression is enhanced with complex adaptation in a 3D viewing surround combining global and local adaptation. Evaluating local image rendering in view of tone and color expression, noise reduction, and edge compensation confirms that the proposed 3D image-mapping model can compensate for the loss of image quality in the 3D mode.

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

    International Nuclear Information System (INIS)

    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

  19. Segmentation and Classification of Human Actions and Actor Characteristics with 3d Motion Data

    Directory of Open Access Journals (Sweden)

    S. Ali Etemad

    2012-07-01

    Full Text Available In this paper we have used 3D motion capture data with the aim of detecting and classifying specific human actions. In addition to recognition of basic action classes, actor styles and characteristics such as gender, age, and energy level have also been subject to classification. We have applied and compared three main methods: nearest neighbour search, hidden Markov models, and artificial neural networks. Using these techniques, we have proposed exhaustive algorithms for detection of actions in a motion piece and subsequently classifying the segmented actions and respective characteristics of the actors. We have tested the methods for various sequences and compared the results for a comprehensive evaluation of each of the proposed techniques. Our findings can be largely used for general classification of human motion data for multimedia applications as well as sorting and classifying data sets of human motion data especially those acquired using visual marker-based motion capture systems such as the one employed in this research.

  20. Soft computing approach to 3D lung nodule segmentation in CT.

    Science.gov (United States)

    Badura, P; Pietka, E

    2014-10-01

    This paper presents a novel, multilevel approach to the segmentation of various types of pulmonary nodules in computed tomography studies. It is based on two branches of computational intelligence: the fuzzy connectedness (FC) and the evolutionary computation. First, the image and auxiliary data are prepared for the 3D FC analysis during the first stage of an algorithm - the masks generation. Its main goal is to process some specific types of nodules connected to the pleura or vessels. It consists of some basic image processing operations as well as dedicated routines for the specific cases of nodules. The evolutionary computation is performed on the image and seed points in order to shorten the FC analysis and improve its accuracy. After the FC application, the remaining vessels are removed during the postprocessing stage. The method has been validated using the first dataset of studies acquired and described by the Lung Image Database Consortium (LIDC) and by its latest release - the LIDC-IDRI (Image Database Resource Initiative) database.

  1. METHOD FOR ADAPTIVE MESH GENERATION BASED ON GEOMETRICAL FEATURES OF 3D SOLID

    Institute of Scientific and Technical Information of China (English)

    HUANG Xiaodong; DU Qungui; YE Bangyan

    2006-01-01

    In order to provide a guidance to specify the element size dynamically during adaptive finite element mesh generation, adaptive criteria are firstly defined according to the relationships between the geometrical features and the elements of 3D solid. Various modes based on different datum geometrical elements, such as vertex, curve, surface, and so on, are then designed for generating local refmed mesh. With the guidance of the defined criteria, different modes are automatically selected to apply on the appropriate datum objects to program the element size in the local special areas. As a result, the control information of element size is successfully programmed coveting the entire domain based on the geometrical features of 3D solid. A new algorithm based on Delaunay triangulation is then developed for generating 3D adaptive fmite element mesh, in which the element size is dynamically specified to catch the geometrical features and suitable tetrahedron facets are selected to locate interior nodes continuously. As a result, adaptive mesh with good-quality elements is generated. Examples show that the proposed method can be successfully applied to adaptive finite element mesh automatic generation based on the geometrical features of 3D solid.

  2. A Learning Approach for Adaptive Image Segmentation

    OpenAIRE

    Martin, Vincent; Thonnat, Monique

    2007-01-01

    In this chapter, we have proposed a learning approach for three major issues of image segmentation: context adaptation, algorithm selection and parameter tuning according to the image content and the application need. This supervised learning approach relies on hand-labelled samples. The learning process is guided by the goal of the segmentation and therefore makes the approach reliable for a broad range of applications. The user effort is restrained compared to other supervised methods since...

  3. Segmentation and Recognition of Highway Assets using Image-based 3D Point Clouds and Semantic Texton Forests

    OpenAIRE

    Golparvar-Fard, Mani; Balali, Vahid; de la Garza, Jesus M.

    2013-01-01

    This dataset was collected as part of research work on segmentation and recognition of highway assets in images and viedo. The research is described in detail in Journal of Computing in Civil Engineering - ASCE paper "Segmentation and Recognition of Highway Assets using Image-based 3D Point Clouds and Semantic Texton Forests". The dataset include: 12 highway asset catgegories, 3 different dataset which is divided in three groups: (a)Ground Truth images with #_#_s_GT.jpg filename...

  4. 3D-SoftChip: A Novel Architecture for Next-Generation Adaptive Computing Systems

    Directory of Open Access Journals (Sweden)

    Lee Mike Myung-Ok

    2006-01-01

    Full Text Available This paper introduces a novel architecture for next-generation adaptive computing systems, which we term 3D-SoftChip. The 3D-SoftChip is a 3-dimensional (3D vertically integrated adaptive computing system combining state-of-the-art processing and 3D interconnection technology. It comprises the vertical integration of two chips (a configurable array processor and an intelligent configurable switch through an indium bump interconnection array (IBIA. The configurable array processor (CAP is an array of heterogeneous processing elements (PEs, while the intelligent configurable switch (ICS comprises a switch block, 32-bit dedicated RISC processor for control, on-chip program/data memory, data frame buffer, along with a direct memory access (DMA controller. This paper introduces the novel 3D-SoftChip architecture for real-time communication and multimedia signal processing as a next-generation computing system. The paper further describes the advanced HW/SW codesign and verification methodology, including high-level system modeling of the 3D-SoftChip using SystemC, being used to determine the optimum hardware specification in the early design stage.

  5. Integrated 3D density modelling and segmentation of the Dead Sea Transform

    Science.gov (United States)

    Götze, H.-J.; El-Kelani, R.; Schmidt, S.; Rybakov, M.; Hassouneh, M.; Förster, H.-J.; Ebbing, J.

    2007-04-01

    A 3D interpretation of the newly compiled Bouguer anomaly in the area of the “Dead Sea Rift” is presented. A high-resolution 3D model constrained with the seismic results reveals the crustal thickness and density distribution beneath the Arava/Araba Valley (AV), the region between the Dead Sea and the Gulf of Aqaba/Elat. The Bouguer anomalies along the axial portion of the AV, as deduced from the modelling results, are mainly caused by deep-seated sedimentary basins ( D > 10 km). An inferred zone of intrusion coincides with the maximum gravity anomaly on the eastern flank of the AV. The intrusion is displaced at different sectors along the NNW-SSE direction. The zone of maximum crustal thinning (depth 30 km) is attained in the western sector at the Mediterranean. The southeastern plateau, on the other hand, shows by far the largest crustal thickness of the region (38-42 km). Linked to the left lateral movement of approx. 105 km at the boundary between the African and Arabian plate, and constrained with recent seismic data, a small asymmetric topography of the Moho beneath the Dead Sea Transform (DST) was modelled. The thickness and density of the crust suggest that the AV is underlain by continental crust. The deep basins, the relatively large intrusion and the asymmetric topography of the Moho lead to the conclusion that a small-scale asthenospheric upwelling could be responsible for the thinning of the crust and subsequent creation of the Dead Sea basin during the left lateral movement. A clear segmentation along the strike of the DST was obtained by curvature analysis: the northern part in the neighbourhood of the Dead Sea is characterised by high curvature of the residual gravity field. Flexural rigidity calculations result in very low values of effective elastic lithospheric thickness ( t e < 5 km). This points to decoupling of crust in the Dead Sea area. In the central, AV the curvature is less pronounced and t e increases to approximately 10 km

  6. 3D Human model adaptation by frame selection and shape–texture optimization

    NARCIS (Netherlands)

    Hofmann, K.M.; Gavrila, D.M.

    2011-01-01

    We present a novel approach for 3D human body shape model adaptation to a sequence of multi-view images, given an initial shape model and initial pose sequence. In a first step, the most informative frames are determined by optimization of an objective function that maximizes a shape–texture likelih

  7. Segment-interaction in sprint start: Analysis of 3D angular velocity and kinetic energy in elite sprinters

    OpenAIRE

    Slawinski, Jean; BONNEFOY, Alice; ONTANON, Guy; LEVEQUE, Jean-Michel; Miller, Christian; RIQUET, Annie; CHEZE, Laurence; Dumas, Raphaël

    2010-01-01

    The aim of the present study was to measure during a sprint start the joint angularv elocity and the kinetic energy of the different segments in elite sprinters.This was performed using a 3D kinematic analysis of the wholebody.

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

    Science.gov (United States)

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

    2015-08-19

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

  9. Fast and memory-efficient LOGISMOS graph search for intraretinal layer segmentation of 3D macular OCT scans

    Science.gov (United States)

    Lee, Kyungmoo; Zhang, Li; Abramoff, Michael D.; Sonka, Milan

    2015-03-01

    Image segmentation is important for quantitative analysis of medical image data. Recently, our research group has introduced a 3-D graph search method which can simultaneously segment optimal interacting surfaces with respect to the cost function in volumetric images. Although it provides excellent segmentation accuracy, it is computationally demanding (both CPU and memory) to simultaneously segment multiple surfaces from large volumetric images. Therefore, we propose a new, fast, and memory-efficient graph search method for intraretinal layer segmentation of 3-D macular optical coherence tomograpy (OCT) scans. The key idea is to reduce the size of a graph by combining the nodes with high costs based on the multiscale approach. The new approach requires significantly less memory and achieves significantly faster processing speeds (p segmentation differences compared to the original graph search method. This paper discusses sub-optimality of this approach and assesses trade-off relationships between decreasing processing speed and increasing segmentation differences from that of the original method as a function of employed scale of the underlying graph construction.

  10. Adaptation of Zerotrees Using Signed Binary Digit Representations for 3D Image Coding

    Directory of Open Access Journals (Sweden)

    Mailhes Corinne

    2007-01-01

    Full Text Available Zerotrees of wavelet coefficients have shown a good adaptability for the compression of three-dimensional images. EZW, the original algorithm using zerotree, shows good performance and was successfully adapted to 3D image compression. This paper focuses on the adaptation of EZW for the compression of hyperspectral images. The subordinate pass is suppressed to remove the necessity to keep the significant pixels in memory. To compensate the loss due to this removal, signed binary digit representations are used to increase the efficiency of zerotrees. Contextual arithmetic coding with very limited contexts is also used. Finally, we show that this simplified version of 3D-EZW performs almost as well as the original one.

  11. 3D segmentation of great vessels using active contours and morphological image processing techniques

    OpenAIRE

    Montejo Garcia, Cristina

    2010-01-01

    The scope of this project is to present a semi-automated vessels segmentation algorithm, to describe its usage and results. This will be achieved combining several segmentation algorithms to get proper vessel segmentation and visualization. Consequently, automatic segmentation can significantly reduce the scan-to-diagnosis time, thus helping the clinicians to reach the fundamental goal of efficient patient management. In order to complete our project, we can identify different phases...

  12. Fuzzy segmentation of cerebral tissues in a 3-D MR image: a possibilistic approach versus other methods; Segmentation floue des tissus cerebraux en IRM 3D: approche possibiliste versus autres methodes

    Energy Technology Data Exchange (ETDEWEB)

    Barra, V.; Boire, J.Y. [Universite d' Auvergne, ERIM, Equipe de Recherche en Imagerie Medicale, Faculte de Medecine, 63 - Clercmont Ferrand (France)

    1999-07-01

    An algorithm for the segmentation of a single sequence of 3-D magnetic resonance images into cerebrospinal Fluid (CSF), Grey (GM) and White Matter (WM) classes is proposed. The method is a possibilistic clustering algorithm on the wavelet coefficients of the voxels. Possibilistic logic allows for modeling the uncertainty and the impreciseness inherent in MR images of the brain, while the wavelet representation allows to take into account both spatial and textural information. The procedure is fast, unsupervised and totally independent of statistical assumptions. In method is validated on a phantom, and then compared with other very used brain tissues segmentation algorithms. (authors)

  13. Sample based 3D face reconstruction from a single frontal image by adaptive locally linear embedding

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jian; ZHUANG Yue-ting

    2007-01-01

    In this paper, we propose a highly automatic approach for 3D photorealistic face reconstruction from a single frontal image. The key point of our work is the implementation of adaptive manifold learning approach. Beforehand, an active appearance model (AAM) is trained for automatic feature extraction and adaptive locally linear embedding (ALLE) algorithm is utilized to reduce the dimensionality of the 3D database. Then, given an input frontal face image, the corresponding weights between 3D samples and the image are synthesized adaptively according to the AAM selected facial features. Finally, geometry reconstruction is achieved by linear weighted combination of adaptively selected samples. Radial basis function (RBF) is adopted to map facial texture from the frontal image to the reconstructed face geometry. The texture of invisible regions between the face and the ears is interpolated by sampling from the frontal image. This approach has several advantages: (1) Only a single frontal face image is needed for highly automatic face reconstruction; (2) Compared with former works, our reconstruction approach provides higher accuracy; (3) Constraint based RBF texture mapping provides natural appearance for reconstructed face.

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

    Science.gov (United States)

    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.

  15. Web-based Visualization and Query of semantically segmented multiresolution 3D Models in the Field of Cultural Heritage

    Science.gov (United States)

    Auer, M.; Agugiaro, G.; Billen, N.; Loos, L.; Zipf, A.

    2014-05-01

    Many important Cultural Heritage sites have been studied over long periods of time by different means of technical equipment, methods and intentions by different researchers. This has led to huge amounts of heterogeneous "traditional" datasets and formats. The rising popularity of 3D models in the field of Cultural Heritage in recent years has brought additional data formats and makes it even more necessary to find solutions to manage, publish and study these data in an integrated way. The MayaArch3D project aims to realize such an integrative approach by establishing a web-based research platform bringing spatial and non-spatial databases together and providing visualization and analysis tools. Especially the 3D components of the platform use hierarchical segmentation concepts to structure the data and to perform queries on semantic entities. This paper presents a database schema to organize not only segmented models but also different Levels-of-Details and other representations of the same entity. It is further implemented in a spatial database which allows the storing of georeferenced 3D data. This enables organization and queries by semantic, geometric and spatial properties. As service for the delivery of the segmented models a standardization candidate of the OpenGeospatialConsortium (OGC), the Web3DService (W3DS) has been extended to cope with the new database schema and deliver a web friendly format for WebGL rendering. Finally a generic user interface is presented which uses the segments as navigation metaphor to browse and query the semantic segmentation levels and retrieve information from an external database of the German Archaeological Institute (DAI).

  16. Patellar segmentation from 3D magnetic resonance images using guided recursive ray-tracing for edge pattern detection

    Science.gov (United States)

    Cheng, Ruida; Jackson, Jennifer N.; McCreedy, Evan S.; Gandler, William; Eijkenboom, J. J. F. A.; van Middelkoop, M.; McAuliffe, Matthew J.; Sheehan, Frances T.

    2016-03-01

    The paper presents an automatic segmentation methodology for the patellar bone, based on 3D gradient recalled echo and gradient recalled echo with fat suppression magnetic resonance images. Constricted search space outlines are incorporated into recursive ray-tracing to segment the outer cortical bone. A statistical analysis based on the dependence of information in adjacent slices is used to limit the search in each image to between an outer and inner search region. A section based recursive ray-tracing mechanism is used to skip inner noise regions and detect the edge boundary. The proposed method achieves higher segmentation accuracy (0.23mm) than the current state-of-the-art methods with the average dice similarity coefficient of 96.0% (SD 1.3%) agreement between the auto-segmentation and ground truth surfaces.

  17. Estimation of 3-D pore network coordination number of rocks from watershed segmentation of a single 2-D image

    Science.gov (United States)

    Rabbani, Arash; Ayatollahi, Shahab; Kharrat, Riyaz; Dashti, Nader

    2016-08-01

    In this study, we have utilized 3-D micro-tomography images of real and synthetic rocks to introduce two mathematical correlations which estimate the distribution parameters of 3-D coordination number using a single 2-D cross-sectional image. By applying a watershed segmentation algorithm, it is found that the distribution of 3-D coordination number is acceptably predictable by statistical analysis of the network extracted from 2-D images. In this study, we have utilized 25 volumetric images of rocks in order to propose two mathematical formulas. These formulas aim to approximate the average and standard deviation of coordination number in 3-D pore networks. Then, the formulas are applied for five independent test samples to evaluate the reliability. Finally, pore network flow modeling is used to find the error of absolute permeability prediction using estimated and measured coordination numbers. Results show that the 2-D images are considerably informative about the 3-D network of the rocks and can be utilized to approximate the 3-D connectivity of the porous spaces with determination coefficient of about 0.85 that seems to be acceptable considering the variety of the studied samples.

  18. Parallel Adaptive Computation of Blood Flow in a 3D ``Whole'' Body Model

    Science.gov (United States)

    Zhou, M.; Figueroa, C. A.; Taylor, C. A.; Sahni, O.; Jansen, K. E.

    2008-11-01

    Accurate numerical simulations of vascular trauma require the consideration of a larger portion of the vasculature than previously considered, due to the systemic nature of the human body's response. A patient-specific 3D model composed of 78 connected arterial branches extending from the neck to the lower legs is constructed to effectively represent the entire body. Recently developed outflow boundary conditions that appropriately represent the downstream vasculature bed which is not included in the 3D computational domain are applied at 78 outlets. In this work, the pulsatile blood flow simulations are started on a fairly uniform, unstructured mesh that is subsequently adapted using a solution-based approach to efficiently resolve the flow features. The adapted mesh contains non-uniform, anisotropic elements resulting in resolution that conforms with the physical length scales present in the problem. The effects of the mesh resolution on the flow field are studied, specifically on relevant quantities of pressure, velocity and wall shear stress.

  19. Estimation of regeneration coverage in a temperate forest by 3D segmentation using airborne laser scanning data

    Science.gov (United States)

    Amiri, Nina; Yao, Wei; Heurich, Marco; Krzystek, Peter; Skidmore, Andrew K.

    2016-10-01

    Forest understory and regeneration are important factors in sustainable forest management. However, understanding their spatial distribution in multilayered forests requires accurate and continuously updated field data, which are difficult and time-consuming to obtain. Therefore, cost-efficient inventory methods are required, and airborne laser scanning (ALS) is a promising tool for obtaining such information. In this study, we examine a clustering-based 3D segmentation in combination with ALS data for regeneration coverage estimation in a multilayered temperate forest. The core of our method is a two-tiered segmentation of the 3D point clouds into segments associated with regeneration trees. First, small parts of trees (super-voxels) are constructed through mean shift clustering, a nonparametric procedure for finding the local maxima of a density function. In the second step, we form a graph based on the mean shift clusters and merge them into larger segments using the normalized cut algorithm. These segments are used to obtain regeneration coverage of the target plot. Results show that, based on validation data from field inventory and terrestrial laser scanning (TLS), our approach correctly estimates up to 70% of regeneration coverage across the plots with different properties, such as tree height and tree species. The proposed method is negatively impacted by the density of the overstory because of decreasing ground point density. In addition, the estimated coverage has a strong relationship with the overstory tree species composition.

  20. Improving Segmentation of 3D Retina Layers Based on Graph Theory Approach for Low Quality OCT Images

    Directory of Open Access Journals (Sweden)

    Stankiewicz Agnieszka

    2016-06-01

    Full Text Available This paper presents signal processing aspects for automatic segmentation of retinal layers of the human eye. The paper draws attention to the problems that occur during the computer image processing of images obtained with the use of the Spectral Domain Optical Coherence Tomography (SD OCT. Accuracy of the retinal layer segmentation for a set of typical 3D scans with a rather low quality was shown. Some possible ways to improve quality of the final results are pointed out. The experimental studies were performed using the so-called B-scans obtained with the OCT Copernicus HR device.

  1. Adaptive Optics Concept For Multi-Objects 3D Spectroscopy on ELTs

    CERN Document Server

    Neichel, B; Puech, M; Conan, J M; Lelouarn, M; Gendron, E; Hammer, F; Rousset, G; Jagourel, P; Bouchet, P

    2005-01-01

    In this paper, we present a first comparison of different Adaptive Optics (AO) concepts to reach a given scientific specification for 3D spectroscopy on Extremely Large Telescope (ELT). We consider that a range of 30%-50% of Ensquarred Energy (EE) in H band (1.65um) and in an aperture size from 25 to 100mas is representative of the scientific requirements. From these preliminary choices, different kinds of AO concepts are investigated : Ground Layer Adaptive Optics (GLAO), Multi-Object AO (MOAO) and Laser Guide Stars AO (LGS). Using Fourier based simulations we study the performance of these AO systems depending on the telescope diameter.

  2. A density-based segmentation for 3D images, an application for X-ray micro-tomography

    Energy Technology Data Exchange (ETDEWEB)

    Tran, Thanh N., E-mail: thanh.tran@merck.com [Center for Mathematical Sciences Merck, MSD Molenstraat 110, 5342 CC Oss, PO Box 20, 5340 BH Oss (Netherlands); Nguyen, Thanh T.; Willemsz, Tofan A. [Department of Pharmaceutical Technology and Biopharmacy, University of Groningen, Groningen (Netherlands); Pharmaceutical Sciences and Clinical Supplies, Merck MSD, PO Box 20, 5340 BH Oss (Netherlands); Kessel, Gijs van [Center for Mathematical Sciences Merck, MSD Molenstraat 110, 5342 CC Oss, PO Box 20, 5340 BH Oss (Netherlands); Frijlink, Henderik W. [Department of Pharmaceutical Technology and Biopharmacy, University of Groningen, Groningen (Netherlands); Voort Maarschalk, Kees van der [Department of Pharmaceutical Technology and Biopharmacy, University of Groningen, Groningen (Netherlands); Competence Center Process Technology, Purac Biochem, Gorinchem (Netherlands)

    2012-05-06

    Highlights: Black-Right-Pointing-Pointer We revised the DBSCAN algorithm for segmentation and clustering of large 3D image dataset and classified multivariate image. Black-Right-Pointing-Pointer The algorithm takes into account the coordinate system of the image data to improve the computational performance. Black-Right-Pointing-Pointer The algorithm solved the instability problem in boundaries detection of the original DBSCAN. Black-Right-Pointing-Pointer The segmentation results were successfully validated with synthetic 3D image and 3D XMT image of a pharmaceutical powder. - Abstract: Density-based spatial clustering of applications with noise (DBSCAN) is an unsupervised classification algorithm which has been widely used in many areas with its simplicity and its ability to deal with hidden clusters of different sizes and shapes and with noise. However, the computational issue of the distance table and the non-stability in detecting the boundaries of adjacent clusters limit the application of the original algorithm to large datasets such as images. In this paper, the DBSCAN algorithm was revised and improved for image clustering and segmentation. The proposed clustering algorithm presents two major advantages over the original one. Firstly, the revised DBSCAN algorithm made it applicable for large 3D image dataset (often with millions of pixels) by using the coordinate system of the image data. Secondly, the revised algorithm solved the non-stability issue of boundary detection in the original DBSCAN. For broader applications, the image dataset can be ordinary 3D images or in general, it can also be a classification result of other type of image data e.g. a multivariate image.

  3. SATZ An Adaptive Sentence Segmentation System

    CERN Document Server

    Palmer, D D

    1995-01-01

    This paper provides a detailed description of the sentence segmentation system first introduced in cmp-lg/9411022. It provides results of systematic experiments involving sentence boundary determination, including context size, lexicon size, and single-case texts. Also included are the results of successfully adapting the system to German and French. The source code for the system is available as a compressed tar file at ftp://cs-tr.CS.Berkeley.EDU/pub/cstr/satz.tar.Z .

  4. A Simple Fault-Tolerant Adaptive and Minimal Routing Approach in 3-D Meshes

    Institute of Scientific and Technical Information of China (English)

    WU Jie(吴杰)

    2003-01-01

    In this paper we propose a sufficient condition for minimal routing in 3-dimensional (3-D) meshes with faulty nodes. It is based on an early work of the author on minimal routing in 2-dimensional (2-D) meshes. Unlike many traditional models that assume all the nodes know global fault distribution or just adjacent fault information, our approach is based on the concept of limited global fault information. First, we propose a fault model called faulty cube in which all faulty nodes in the system are contained in a set of faulty cubes. Fault information is then distributed to limited number of nodes while it is still sufficient to support minimal routing. The limited fault information collected at each node is represented by a vector called extended safety level. The extended safety level associated with a node can be used to determine the existence of a minimal path from this node to a given destination. Specifically, we study the existence of minimal paths at a given source node, limited distribution of fault information, minimal routing, and deadlock-free and livelock-free routing. Our results show that any minimal routing that is partially adaptive can be applied in our model as long as the destination node meets a certain condition. We also propose a dynamic planar-adaptive routing scheme that offers better fault tolerance and adaptivity than the planar-adaptive routing scheme in 3-D meshes. Our approach is the first attempt to address adaptive and minimal routing in 3-D meshes with faulty nodes using limited fault information.

  5. Combining Population and Patient-Specific Characteristics for Prostate Segmentation on 3D CT Images

    Science.gov (United States)

    Ma, Ling; Guo, Rongrong; Tian, Zhiqiang; Venkataraman, Rajesh; Sarkar, Saradwata; Liu, Xiabi; Tade, Funmilayo; Schuster, David M.; Fei, Baowei

    2016-01-01

    Prostate segmentation on CT images is a challenging task. In this paper, we explore the population and patient-specific characteristics for the segmentation of the prostate on CT images. Because population learning does not consider the inter-patient variations and because patient-specific learning may not perform well for different patients, we are combining the population and patient-specific information to improve segmentation performance. Specifically, we train a population model based on the population data and train a patient-specific model based on the manual segmentation on three slice of the new patient. We compute the similarity between the two models to explore the influence of applicable population knowledge on the specific patient. By combining the patient-specific knowledge with the influence, we can capture the population and patient-specific characteristics to calculate the probability of a pixel belonging to the prostate. Finally, we smooth the prostate surface according to the prostate-density value of the pixels in the distance transform image. We conducted the leave-one-out validation experiments on a set of CT volumes from 15 patients. Manual segmentation results from a radiologist serve as the gold standard for the evaluation. Experimental results show that our method achieved an average DSC of 85.1% as compared to the manual segmentation gold standard. This method outperformed the population learning method and the patient-specific learning approach alone. The CT segmentation method can have various applications in prostate cancer diagnosis and therapy.

  6. Multi-domain, higher order level set scheme for 3D image segmentation on the GPU

    DEFF Research Database (Denmark)

    Sharma, Ojaswa; Zhang, Qin; Anton, François;

    2010-01-01

    to evaluate level set surfaces that are $C^2$ continuous, but are slow due to high computational burden. In this paper, we provide a higher order GPU based solver for fast and efficient segmentation of large volumetric images. We also extend the higher order method to multi-domain segmentation. Our streaming......Level set method based segmentation provides an efficient tool for topological and geometrical shape handling. Conventional level set surfaces are only $C^0$ continuous since the level set evolution involves linear interpolation to compute derivatives. Bajaj et al. present a higher order method...

  7. Segmentation Based Classification of 3D Urban Point Clouds: A Super-Voxel Based Approach with Evaluation

    Directory of Open Access Journals (Sweden)

    Laurent Trassoudaine

    2013-03-01

    Full Text Available Segmentation and classification of urban range data into different object classes have several challenges due to certain properties of the data, such as density variation, inconsistencies due to missing data and the large data size that require heavy computation and large memory. A method to classify urban scenes based on a super-voxel segmentation of sparse 3D data obtained from LiDAR sensors is presented. The 3D point cloud is first segmented into voxels, which are then characterized by several attributes transforming them into super-voxels. These are joined together by using a link-chain method rather than the usual region growing algorithm to create objects. These objects are then classified using geometrical models and local descriptors. In order to evaluate the results, a new metric that combines both segmentation and classification results simultaneously is presented. The effects of voxel size and incorporation of RGB color and laser reflectance intensity on the classification results are also discussed. The method is evaluated on standard data sets using different metrics to demonstrate its efficacy.

  8. 3D active shape modeling for cardiac MR and CT image segmentation

    NARCIS (Netherlands)

    Assen, Hans Christiaan van

    2006-01-01

    3D Active Shape Modeling is a technique to capture shape information from a training set containing characteristic shapes of, e.g., a heart. The description contains a mean shape, and shape variations (e.g. eigen deformations and eigen values). Many models based on these statistics, and used for med

  9. Intra-chain 3D segment swapping spawns the evolution of new multidomain protein architectures.

    Science.gov (United States)

    Szilágyi, András; Zhang, Yang; Závodszky, Péter

    2012-01-01

    Multidomain proteins form in evolution through the concatenation of domains, but structural domains may comprise multiple segments of the chain. In this work, we demonstrate that new multidomain architectures can evolve by an apparent three-dimensional swap of segments between structurally similar domains within a single-chain monomer. By a comprehensive structural search of the current Protein Data Bank (PDB), we identified 32 well-defined segment-swapped proteins (SSPs) belonging to 18 structural families. Nearly 13% of all multidomain proteins in the PDB may have a segment-swapped evolutionary precursor as estimated by more permissive searching criteria. The formation of SSPs can be explained by two principal evolutionary mechanisms: (i) domain swapping and fusion (DSF) and (ii) circular permutation (CP). By large-scale comparative analyses using structural alignment and hidden Markov model methods, it was found that the majority of SSPs have evolved via the DSF mechanism, and a much smaller fraction, via CP. Functional analyses further revealed that segment swapping, which results in two linkers connecting the domains, may impart directed flexibility to multidomain proteins and contributes to the development of new functions. Thus, inter-domain segment swapping represents a novel general mechanism by which new protein folds and multidomain architectures arise in evolution, and SSPs have structural and functional properties that make them worth defining as a separate group. PMID:22079367

  10. A 3D global-to-local deformable mesh model based registration and anatomy-constrained segmentation method for image guided prostate radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Jinghao; Kim, Sung; Jabbour, Salma; Goyal, Sharad; Haffty, Bruce; Chen, Ting; Levinson, Lydia; Metaxas, Dimitris; Yue, Ning J. [Department of Radiation Oncology, UMDNJ-Robert Wood Johnson Medical School, Cancer Institute of New Jersey, New Brunswick, New Jersey 08903 (United States); Department of Bioinformatics, UMDNJ-Robert Wood Johnson Medical School, Cancer Institute of New Jersey, New Brunswick, New Jersey 08903 (United States); Department of Radiation Oncology, UMDNJ-Robert Wood Johnson Medical School, Cancer Institute of New Jersey, New Brunswick, New Jersey 08903 (United States); Department of Computer Science, Rutgers, State University of New Jersey, Piscataway, New Jersey 08854 (United States); Department of Radiation Oncology, UMDNJ-Robert Wood Johnson Medical School, Cancer Institute of New Jersey, New Brunswick, New Jersey 08903 (United States)

    2010-03-15

    Purpose: In the external beam radiation treatment of prostate cancers, successful implementation of adaptive radiotherapy and conformal radiation dose delivery is highly dependent on precise and expeditious segmentation and registration of the prostate volume between the simulation and the treatment images. The purpose of this study is to develop a novel, fast, and accurate segmentation and registration method to increase the computational efficiency to meet the restricted clinical treatment time requirement in image guided radiotherapy. Methods: The method developed in this study used soft tissues to capture the transformation between the 3D planning CT (pCT) images and 3D cone-beam CT (CBCT) treatment images. The method incorporated a global-to-local deformable mesh model based registration framework as well as an automatic anatomy-constrained robust active shape model (ACRASM) based segmentation algorithm in the 3D CBCT images. The global registration was based on the mutual information method, and the local registration was to minimize the Euclidian distance of the corresponding nodal points from the global transformation of deformable mesh models, which implicitly used the information of the segmented target volume. The method was applied on six data sets of prostate cancer patients. Target volumes delineated by the same radiation oncologist on the pCT and CBCT were chosen as the benchmarks and were compared to the segmented and registered results. The distance-based and the volume-based estimators were used to quantitatively evaluate the results of segmentation and registration. Results: The ACRASM segmentation algorithm was compared to the original active shape model (ASM) algorithm by evaluating the values of the distance-based estimators. With respect to the corresponding benchmarks, the mean distance ranged from -0.85 to 0.84 mm for ACRASM and from -1.44 to 1.17 mm for ASM. The mean absolute distance ranged from 1.77 to 3.07 mm for ACRASM and from 2.45 to

  11. Cardiac Multi-detector CT Segmentation Based on Multiscale Directional Edge Detector and 3D Level Set.

    Science.gov (United States)

    Antunes, Sofia; Esposito, Antonio; Palmisano, Anna; Colantoni, Caterina; Cerutti, Sergio; Rizzo, Giovanna

    2016-05-01

    Extraction of the cardiac surfaces of interest from multi-detector computed tomographic (MDCT) data is a pre-requisite step for cardiac analysis, as well as for image guidance procedures. Most of the existing methods need manual corrections, which is time-consuming. We present a fully automatic segmentation technique for the extraction of the right ventricle, left ventricular endocardium and epicardium from MDCT images. The method consists in a 3D level set surface evolution approach coupled to a new stopping function based on a multiscale directional second derivative Gaussian filter, which is able to stop propagation precisely on the real boundary of the structures of interest. We validated the segmentation method on 18 MDCT volumes from healthy and pathologic subjects using manual segmentation performed by a team of expert radiologists as gold standard. Segmentation errors were assessed for each structure resulting in a surface-to-surface mean error below 0.5 mm and a percentage of surface distance with errors less than 1 mm above 80%. Moreover, in comparison to other segmentation approaches, already proposed in previous work, our method presented an improved accuracy (with surface distance errors less than 1 mm increased of 8-20% for all structures). The obtained results suggest that our approach is accurate and effective for the segmentation of ventricular cavities and myocardium from MDCT images. PMID:26319010

  12. Segment-interaction in sprint start: Analysis of 3D angular velocity and kinetic energy in elite sprinters.

    Science.gov (United States)

    Slawinski, J; Bonnefoy, A; Ontanon, G; Leveque, J M; Miller, C; Riquet, A; Chèze, L; Dumas, R

    2010-05-28

    The aim of the present study was to measure during a sprint start the joint angular velocity and the kinetic energy of the different segments in elite sprinters. This was performed using a 3D kinematic analysis of the whole body. Eight elite sprinters (10.30+/-0.14s 100 m time), equipped with 63 passive reflective markers, realised four maximal 10 m sprints start on an indoor track. An opto-electronic Motion Analysis system consisting of 12 digital cameras (250 Hz) was used to collect the 3D marker trajectories. During the pushing phase on the blocks, the 3D angular velocity vector and its norm were calculated for each joint. The kinetic energy of 16 segments of the lower and upper limbs and of the total body was calculated. The 3D kinematic analysis of the whole body demonstrated that joints such as shoulders, thoracic or hips did not reach their maximal angular velocity with a movement of flexion-extension, but with a combination of flexion-extension, abduction-adduction and internal-external rotation. The maximal kinetic energy of the total body was reached before clearing block (respectively, 537+/-59.3 J vs. 514.9+/-66.0 J; p< or =0.01). These results suggested that a better synchronization between the upper and lower limbs could increase the efficiency of pushing phase on the blocks. Besides, to understand low interindividual variances in the sprint start performance in elite athletes, a 3D complete body kinematic analysis shall be used. PMID:20226465

  13. 3D structural analysis of proteins using electrostatic surfaces based on image segmentation

    Science.gov (United States)

    Vlachakis, Dimitrios; Champeris Tsaniras, Spyridon; Tsiliki, Georgia; Megalooikonomou, Vasileios; Kossida, Sophia

    2016-01-01

    Herein, we present a novel strategy to analyse and characterize proteins using protein molecular electro-static surfaces. Our approach starts by calculating a series of distinct molecular surfaces for each protein that are subsequently flattened out, thus reducing 3D information noise. RGB images are appropriately scaled by means of standard image processing techniques whilst retaining the weight information of each protein’s molecular electrostatic surface. Then homogeneous areas in the protein surface are estimated based on unsupervised clustering of the 3D images, while performing similarity searches. This is a computationally fast approach, which efficiently highlights interesting structural areas among a group of proteins. Multiple protein electrostatic surfaces can be combined together and in conjunction with their processed images, they can provide the starting material for protein structural similarity and molecular docking experiments.

  14. Aeroacoustic Simulation of Nose Landing Gear on Adaptive Unstructured Grids With FUN3D

    Science.gov (United States)

    Vatsa, Veer N.; Khorrami, Mehdi R.; Park, Michael A.; Lockhard, David P.

    2013-01-01

    Numerical simulations have been performed for a partially-dressed, cavity-closed nose landing gear configuration that was tested in NASA Langley s closed-wall Basic Aerodynamic Research Tunnel (BART) and in the University of Florida's open-jet acoustic facility known as the UFAFF. The unstructured-grid flow solver FUN3D, developed at NASA Langley Research center, is used to compute the unsteady flow field for this configuration. Starting with a coarse grid, a series of successively finer grids were generated using the adaptive gridding methodology available in the FUN3D code. A hybrid Reynolds-averaged Navier-Stokes/large eddy simulation (RANS/LES) turbulence model is used for these computations. Time-averaged and instantaneous solutions obtained on these grids are compared with the measured data. In general, the correlation with the experimental data improves with grid refinement. A similar trend is observed for sound pressure levels obtained by using these CFD solutions as input to a FfowcsWilliams-Hawkings noise propagation code to compute the farfield noise levels. In general, the numerical solutions obtained on adapted grids compare well with the hand-tuned enriched fine grid solutions and experimental data. In addition, the grid adaption strategy discussed here simplifies the grid generation process, and results in improved computational efficiency of CFD simulations.

  15. Automatic segmentation of cerebral white matter hyperintensities using only 3D FLAIR images

    NARCIS (Netherlands)

    Lopes Simoes, A.R.; Monninghoff, C.; Dlugaj, M.; Weimar, C.; Wanke, I.; Cappellen van Walsum, A.; Slump, C.H.

    2013-01-01

    Magnetic Resonance (MR) white matter hyperintensities have been shown to predict an increased risk of developing cognitive decline. However, their actual role in the conversion to dementia is still not fully understood. Automatic segmentation methods can help in the screening and monitoring of Mild

  16. Automatic segmentation of cerebral white matter hyperintensities using only 3D FLAIR images.

    NARCIS (Netherlands)

    Simoes, R.; Monninghoff, C.; Dlugaj, M.; Weimar, C.; Wanke, I.; Cappellen van Walsum, A.M. van; Slump, C.

    2013-01-01

    Magnetic Resonance (MR) white matter hyperintensities have been shown to predict an increased risk of developing cognitive decline. However, their actual role in the conversion to dementia is still not fully understood. Automatic segmentation methods can help in the screening and monitoring of Mild

  17. Towards better segmentation of large floating point 3D astronomical data sets : first results

    NARCIS (Netherlands)

    Moschini, Ugo; Teeninga, Paul; Wilkinson, Michael; Giese, Nadine; Punzo, Davide; van der Hulst, Jan M.; Trager, Scott

    2014-01-01

    In any image segmentation task, noise must be separated from the actual information and the relevant pixels grouped into objects of interest, on which measures can later be applied. This should be done efficiently on large astronomical surveys with floating point datasets with resolution of the orde

  18. 3D segmentation of annulus fibrosus and nucleus pulposus from T2-weighted magnetic resonance images

    Science.gov (United States)

    Castro-Mateos, Isaac; Pozo, Jose M.; Eltes, Peter E.; Del Rio, Luis; Lazary, Aron; Frangi, Alejandro F.

    2014-12-01

    Computational medicine aims at employing personalised computational models in diagnosis and treatment planning. The use of such models to help physicians in finding the best treatment for low back pain (LBP) is becoming popular. One of the challenges of creating such models is to derive patient-specific anatomical and tissue models of the lumbar intervertebral discs (IVDs), as a prior step. This article presents a segmentation scheme that obtains accurate results irrespective of the degree of IVD degeneration, including pathological discs with protrusion or herniation. The segmentation algorithm, employing a novel feature selector, iteratively deforms an initial shape, which is projected into a statistical shape model space at first and then, into a B-Spline space to improve accuracy. The method was tested on a MR dataset of 59 patients suffering from LBP. The images follow a standard T2-weighted protocol in coronal and sagittal acquisitions. These two image volumes were fused in order to overcome large inter-slice spacing. The agreement between expert-delineated structures, used here as gold-standard, and our automatic segmentation was evaluated using Dice Similarity Index and surface-to-surface distances, obtaining a mean error of 0.68 mm in the annulus segmentation and 1.88 mm in the nucleus, which are the best results with respect to the image resolution in the current literature.

  19. 3D Wavelet Sub-Bands Mixing for Image De-noising and Segmentation of Brain Images

    Directory of Open Access Journals (Sweden)

    Joyjit Patra

    2016-07-01

    Full Text Available A critical issue in image restoration is the problem of noise removal while keeping the integrity of relevant image information. The method proposed in this paper is a fully automatic 3D block wise version of the Non Local (NL Means filter with wavelet sub-bands mixing. The proposed a wavelet sub-bands mixing is based on a multi-resolution approach for improving the quality of image de-noising filter. Quantitative validation was carried out on synthetic datasets generated with the Brain Web simulator. The results show that our NL-means filter with wavelet sub-band mixing outperforms the classical implementation of the NL-means filter in of de -noising quality and computation time. Comparison with well established methods, such as non linear diffusion filter and total variation minimization, shows that the proposed NL-means filter produces better de-noising results. Finally, qualitative results on real data are presented. And this paper presents an algorithm for medical 3D image de-noising and segmentation using redundant discrete wavelet transform. First, we present a two stage de-noising algorithm using the image fusion concept. The algorithm starts with globally de-noising the brain images (3D volume using Perona Malik’s algorithm and RDWT based algorithms followed by combining the outputs using entropy based fusion approach. Next, a region segmentation algorithm is proposed using texture information and k-means clustering. The proposed algorithms are evaluated using brain 3D image/volume data. The results suggest that the proposed algorithms provide improved performance compared to existing algorithms.

  20. Automatic 3D segmentation of the prostate on magnetic resonance images for radiotherapy planning

    OpenAIRE

    Alvarez Jiménez, Charlems

    2015-01-01

    Abstract. Accurate segmentation of the prostate, the seminal vesicles, the bladder and the rectum is a crucial step for planning radiotherapy (RT) procedures. Modern radiotherapy protocols have included the delineation of the pelvic organs in magnetic resonance images (MRI), as the guide to the therapeutic beam irradiation over the target organ. However, this task is highly inter and intra-expert variable and may take about 20 minutes per patient, even for trained experts, constituting an imp...

  1. Thrust fault segmentation and downward fault propagation in accretionary wedges: New Insights from 3D seismic reflection data

    Science.gov (United States)

    Orme, Haydn; Bell, Rebecca; Jackson, Christopher

    2016-04-01

    The shallow parts of subduction megathrust faults are typically thought to be aseismic and incapable of propagating seismic rupture. The 2011 Tohoku-Oki earthquake, however, ruptured all the way to the trench, proving that in some locations rupture can propagate through the accretionary wedge. An improved understanding of the structural character and physical properties of accretionary wedges is therefore crucial to begin to assess why such anomalously shallow seismic rupture occurs. Despite its importance, we know surprisingly little regarding the 3D geometry and kinematics of thrust network development in accretionary prisms, largely due to a lack of 3D seismic reflection data providing high-resolution, 3D images of entire networks. Thus our current understanding is largely underpinned by observations from analogue and numerical modelling, with limited observational data from natural examples. In this contribution we use PSDM, 3D seismic reflection data from the Nankai margin (3D Muroto dataset, available from the UTIG Academic Seismic Portal, Marine Geoscience Data System) to examine how imbricate thrust fault networks evolve during accretionary wedge growth. We unravel the evolution of faults within the protothrust and imbricate thrust zones by interpreting multiple horizons across faults and measuring fault displacement and fold amplitude along-strike; by doing this, we are able to investigate the three dimensional accrual of strain. We document a number of local displacement minima along-strike of faults, suggesting that, the protothrust and imbricate thrusts developed from the linkage of smaller, previously isolated fault segments. Although we often assume imbricate faults are likely to have propagated upwards from the décollement we show strong evidence for fault nucleation at shallow depths and downward propagation to intersect the décollement. The complex fault interactions documented here have implications for hydraulic compartmentalisation and pore

  2. LiDAR Segmentation using Suitable Seed Points for 3D Building Extraction

    Science.gov (United States)

    Abdullah, S. M.; Awrangjeb, M.; Lu, G.

    2014-08-01

    Effective building detection and roof reconstruction has an influential demand over the remote sensing research community. In this paper, we present a new automatic LiDAR point cloud segmentation method using suitable seed points for building detection and roof plane extraction. Firstly, the LiDAR point cloud is separated into "ground" and "non-ground" points based on the analysis of DEM with a height threshold. Each of the non-ground point is marked as coplanar or non-coplanar based on a coplanarity analysis. Commencing from the maximum LiDAR point height towards the minimum, all the LiDAR points on each height level are extracted and separated into several groups based on 2D distance. From each group, lines are extracted and a coplanar point which is the nearest to the midpoint of each line is considered as a seed point. This seed point and its neighbouring points are utilised to generate the plane equation. The plane is grown in a region growing fashion until no new points can be added. A robust rule-based tree removal method is applied subsequently to remove planar segments on trees. Four different rules are applied in this method. Finally, the boundary of each object is extracted from the segmented LiDAR point cloud. The method is evaluated with six different data sets consisting hilly and densely vegetated areas. The experimental results indicate that the proposed method offers a high building detection and roof plane extraction rates while compared to a recently proposed method.

  3. LiDAR Segmentation using Suitable Seed Points for 3D Building Extraction

    OpenAIRE

    S. M. Abdullah; M. Awrangjeb; Lu, G.

    2014-01-01

    Effective building detection and roof reconstruction has an influential demand over the remote sensing research community. In this paper, we present a new automatic LiDAR point cloud segmentation method using suitable seed points for building detection and roof plane extraction. Firstly, the LiDAR point cloud is separated into "ground" and "non-ground" points based on the analysis of DEM with a height threshold. Each of the non-ground point is marked as coplanar or non-coplanar based...

  4. 3D Simulation of Flow with Free Surface Based on Adaptive Octree Mesh System

    Institute of Scientific and Technical Information of China (English)

    Li Shaowu; Zhuang Qian; Huang Xiaoyun; Wang Dong

    2015-01-01

    The technique of adaptive tree mesh is an effective way to reduce computational cost through automatic adjustment of cell size according to necessity. In the present study, the 2D numerical N-S solver based on the adaptive quadtree mesh system was extended to a 3D one, in which a spatially adaptive octree mesh system and multiple parti-cle level set method were adopted for the convenience to deal with the air-water-structure multiple-medium coexisting domain. The stretching process of a dumbbell was simulated and the results indicate that the meshes are well adaptable to the free surface. The collapsing process of water column impinging a circle cylinder was simulated and from the results, it can be seen that the processes of fluid splitting and merging are properly simulated. The interaction of sec-ond-order Stokes waves with a square cylinder was simulated and the obtained drag force is consistent with the result by the Morison’s wave force formula with the coefficient values of the stable drag component and the inertial force component being set as 2.54.

  5. Fully automated prostate segmentation in 3D MR based on normalized gradient fields cross-correlation initialization and LOGISMOS refinement

    Science.gov (United States)

    Yin, Yin; Fotin, Sergei V.; Periaswamy, Senthil; Kunz, Justin; Haldankar, Hrishikesh; Muradyan, Naira; Cornud, François; Turkbey, Baris; Choyke, Peter

    2012-02-01

    Manual delineation of the prostate is a challenging task for a clinician due to its complex and irregular shape. Furthermore, the need for precisely targeting the prostate boundary continues to grow. Planning for radiation therapy, MR-ultrasound fusion for image-guided biopsy, multi-parametric MRI tissue characterization, and context-based organ retrieval are examples where accurate prostate delineation can play a critical role in a successful patient outcome. Therefore, a robust automated full prostate segmentation system is desired. In this paper, we present an automated prostate segmentation system for 3D MR images. In this system, the prostate is segmented in two steps: the prostate displacement and size are first detected, and then the boundary is refined by a shape model. The detection approach is based on normalized gradient fields cross-correlation. This approach is fast, robust to intensity variation and provides good accuracy to initialize a prostate mean shape model. The refinement model is based on a graph-search based framework, which contains both shape and topology information during deformation. We generated the graph cost using trained classifiers and used coarse-to-fine search and region-specific classifier training. The proposed algorithm was developed using 261 training images and tested on another 290 cases. The segmentation performance using mean DSC ranging from 0.89 to 0.91 depending on the evaluation subset demonstrates state of the art performance. Running time for the system is about 20 to 40 seconds depending on image size and resolution.

  6. Global left ventricular function in cardiac CT. Evaluation of an automated 3D region-growing segmentation algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Muehlenbruch, Georg; Das, Marco; Hohl, Christian; Wildberger, Joachim E.; Guenther, Rolf W.; Mahnken, Andreas H. [University Hospital (RWTH) Aachen, Department of Diagnostic Radiology, Aachen (Germany); Rinck, Daniel; Flohr, Thomas G. [Siemens Medical Solutions, Forchheim (Germany); Koos, Ralf; Knackstedt, Christian [University Hospital (RWTH) Aachen, Department of Cardiology, Aachen (Germany)

    2006-05-15

    The purpose was to evaluate a new semi-automated 3D region-growing segmentation algorithm for functional analysis of the left ventricle in multislice CT (MSCT) of the heart. Twenty patients underwent contrast-enhanced MSCT of the heart (collimation 16 x 0.75 mm; 120 kV; 550 mAseff). Multiphase image reconstructions with 1-mm axial slices and 8-mm short-axis slices were performed. Left ventricular volume measurements (end-diastolic volume, end-systolic volume, ejection fraction and stroke volume) from manually drawn endocardial contours in the short axis slices were compared to semi-automated region-growing segmentation of the left ventricle from the 1-mm axial slices. The post-processing-time for both methods was recorded. Applying the new region-growing algorithm in 13/20 patients (65%), proper segmentation of the left ventricle was feasible. In these patients, the signal-to-noise ratio was higher than in the remaining patients (3.2{+-}1.0 vs. 2.6{+-}0.6). Volume measurements of both segmentation algorithms showed an excellent correlation (all P{<=}0.0001); the limits of agreement for the ejection fraction were 2.3{+-}8.3 ml. In the patients with proper segmentation the mean post-processing time using the region-growing algorithm was diminished by 44.2%. On the basis of a good contrast-enhanced data set, a left ventricular volume analysis using the new semi-automated region-growing segmentation algorithm is technically feasible, accurate and more time-effective. (orig.)

  7. Automated torso organ segmentation from 3D CT images using conditional random field

    Science.gov (United States)

    Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Misawa, Kazunari; Mori, Kensaku

    2016-03-01

    This paper presents a segmentation method for torso organs using conditional random field (CRF) from medical images. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. In this paper, we propose an organ segmentation method using structured output learning which is based on probabilistic graphical model. The proposed method utilizes CRF on three-dimensional grids as probabilistic graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weight parameters of the CRF using stochastic gradient descent algorithm and estimate organ labels for a given image by maximum a posteriori (MAP) estimation. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 6.6%. The DICE coefficients of right lung, left lung, heart, liver, spleen, right kidney, and left kidney are 0.94, 0.92, 0.65, 0.67, 0.36, 0.38, and 0.37, respectively.

  8. Automated torso organ segmentation from 3D CT images using structured perceptron and dual decomposition

    Science.gov (United States)

    Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Mori, Kensaku

    2015-03-01

    This paper presents a method for torso organ segmentation from abdominal CT images using structured perceptron and dual decomposition. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. This paper proposes an organ segmentation method using structured output learning. Our method utilizes a graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weights of the graphical model by structured perceptron and estimate the best organ label for a given image by dynamic programming and dual decomposition. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 4.4%. The DICE coefficients of left lung, right lung, heart, liver, spleen, pancreas, left kidney, right kidney, and gallbladder were 0.91, 0.95, 0.77, 0.81, 0.74, 0.08, 0.83, 0.84, and 0.03, respectively.

  9. 3D fast adaptive correlation imaging for large-scale gravity data based on GPU computation

    Science.gov (United States)

    Chen, Z.; Meng, X.; Guo, L.; Liu, G.

    2011-12-01

    In recent years, large scale gravity data sets have been collected and employed to enhance gravity problem-solving abilities of tectonics studies in China. Aiming at the large scale data and the requirement of rapid interpretation, previous authors have carried out a lot of work, including the fast gradient module inversion and Euler deconvolution depth inversion ,3-D physical property inversion using stochastic subspaces and equivalent storage, fast inversion using wavelet transforms and a logarithmic barrier method. So it can be say that 3-D gravity inversion has been greatly improved in the last decade. Many authors added many different kinds of priori information and constraints to deal with nonuniqueness using models composed of a large number of contiguous cells of unknown property and obtained good results. However, due to long computation time, instability and other shortcomings, 3-D physical property inversion has not been widely applied to large-scale data yet. In order to achieve 3-D interpretation with high efficiency and precision for geological and ore bodies and obtain their subsurface distribution, there is an urgent need to find a fast and efficient inversion method for large scale gravity data. As an entirely new geophysical inversion method, 3D correlation has a rapid development thanks to the advantage of requiring no a priori information and demanding small amount of computer memory. This method was proposed to image the distribution of equivalent excess masses of anomalous geological bodies with high resolution both longitudinally and transversely. In order to tranform the equivalence excess masses into real density contrasts, we adopt the adaptive correlation imaging for gravity data. After each 3D correlation imaging, we change the equivalence into density contrasts according to the linear relationship, and then carry out forward gravity calculation for each rectangle cells. Next, we compare the forward gravity data with real data, and

  10. Adaptive multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model

    Science.gov (United States)

    Navarro, Cristóbal A.; Huang, Wei; Deng, Youjin

    2016-08-01

    This work presents an adaptive multi-GPU Exchange Monte Carlo approach for the simulation of the 3D Random Field Ising Model (RFIM). The design is based on a two-level parallelization. The first level, spin-level parallelism, maps the parallel computation as optimal 3D thread-blocks that simulate blocks of spins in shared memory with minimal halo surface, assuming a constant block volume. The second level, replica-level parallelism, uses multi-GPU computation to handle the simulation of an ensemble of replicas. CUDA's concurrent kernel execution feature is used in order to fill the occupancy of each GPU with many replicas, providing a performance boost that is more notorious at the smallest values of L. In addition to the two-level parallel design, the work proposes an adaptive multi-GPU approach that dynamically builds a proper temperature set free of exchange bottlenecks. The strategy is based on mid-point insertions at the temperature gaps where the exchange rate is most compromised. The extra work generated by the insertions is balanced across the GPUs independently of where the mid-point insertions were performed. Performance results show that spin-level performance is approximately two orders of magnitude faster than a single-core CPU version and one order of magnitude faster than a parallel multi-core CPU version running on 16-cores. Multi-GPU performance is highly convenient under a weak scaling setting, reaching up to 99 % efficiency as long as the number of GPUs and L increase together. The combination of the adaptive approach with the parallel multi-GPU design has extended our possibilities of simulation to sizes of L = 32 , 64 for a workstation with two GPUs. Sizes beyond L = 64 can eventually be studied using larger multi-GPU systems.

  11. Automatic Detection, Segmentation and Classification of Retinal Horizontal Neurons in Large-scale 3D Confocal Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Karakaya, Mahmut [ORNL; Kerekes, Ryan A [ORNL; Gleason, Shaun Scott [ORNL; Martins, Rodrigo [St. Jude Children' s Research Hospital; Dyer, Michael [St. Jude Children' s Research Hospital

    2011-01-01

    Automatic analysis of neuronal structure from wide-field-of-view 3D image stacks of retinal neurons is essential for statistically characterizing neuronal abnormalities that may be causally related to neural malfunctions or may be early indicators for a variety of neuropathies. In this paper, we study classification of neuron fields in large-scale 3D confocal image stacks, a challenging neurobiological problem because of the low spatial resolution imagery and presence of intertwined dendrites from different neurons. We present a fully automated, four-step processing approach for neuron classification with respect to the morphological structure of their dendrites. In our approach, we first localize each individual soma in the image by using morphological operators and active contours. By using each soma position as a seed point, we automatically determine an appropriate threshold to segment dendrites of each neuron. We then use skeletonization and network analysis to generate the morphological structures of segmented dendrites, and shape-based features are extracted from network representations of each neuron to characterize the neuron. Based on qualitative results and quantitative comparisons, we show that we are able to automatically compute relevant features that clearly distinguish between normal and abnormal cases for postnatal day 6 (P6) horizontal neurons.

  12. Fast Semantic Segmentation of 3d Point Clouds with Strongly Varying Density

    Science.gov (United States)

    Hackel, Timo; Wegner, Jan D.; Schindler, Konrad

    2016-06-01

    We describe an effective and efficient method for point-wise semantic classification of 3D point clouds. The method can handle unstructured and inhomogeneous point clouds such as those derived from static terrestrial LiDAR or photogammetric reconstruction; and it is computationally efficient, making it possible to process point clouds with many millions of points in a matter of minutes. The key issue, both to cope with strong variations in point density and to bring down computation time, turns out to be careful handling of neighborhood relations. By choosing appropriate definitions of a point's (multi-scale) neighborhood, we obtain a feature set that is both expressive and fast to compute. We evaluate our classification method both on benchmark data from a mobile mapping platform and on a variety of large, terrestrial laser scans with greatly varying point density. The proposed feature set outperforms the state of the art with respect to per-point classification accuracy, while at the same time being much faster to compute.

  13. Automatic segmentation and 3D reconstruction of intravascular ultrasound images for a fast preliminar evaluation of vessel pathologies.

    Science.gov (United States)

    Sanz-Requena, Roberto; Moratal, David; García-Sánchez, Diego Ramón; Bodí, Vicente; Rieta, José Joaquín; Sanchis, Juan Manuel

    2007-03-01

    Intravascular ultrasound (IVUS) imaging is used along with X-ray coronary angiography to detect vessel pathologies. Manual analysis of IVUS images is slow and time-consuming and it is not feasible for clinical purposes. A semi-automated method is proposed to generate 3D reconstructions from IVUS video sequences, so that a fast diagnose can be easily done, quantifying plaque length and severity as well as plaque volume of the vessels under study. The methodology described in this work has four steps: a pre-processing of IVUS images, a segmentation of media-adventitia contour, a detection of intima and plaque and a 3D reconstruction of the vessel. Preprocessing is intended to remove noise from the images without blurring the edges. Segmentation of media-adventitia contour is achieved using active contours (snakes). In particular, we use the gradient vector flow (GVF) as external force for the snakes. The detection of lumen border is obtained taking into account gray-level information of the inner part of the previously detected contours. A knowledge-based approach is used to determine which level of gray corresponds statistically to the different regions of interest: intima, plaque and lumen. The catheter region is automatically discarded. An estimate of plaque type is also given. Finally, 3D reconstruction of all detected regions is made. The suitability of this methodology has been verified for the analysis and visualization of plaque length, stenosis severity, automatic detection of the most problematic regions, calculus of plaque volumes and a preliminary estimation of plaque type obtaining for automatic measures of lumen and vessel area an average error smaller than 1mm(2) (equivalent aproximately to 10% of the average measure), for calculus of plaque and lumen volume errors smaller than 0.5mm(3) (equivalent approximately to 20% of the average measure) and for plaque type estimates a mismatch of less than 8% in the analysed frames. PMID:17215103

  14. 3D medical image segmentation based on a continuous modelling of the volume; Segmentation d`images medicales tridimensionnelles basee sur une modelisation continue du volume

    Energy Technology Data Exchange (ETDEWEB)

    Marque, I.

    1990-12-01

    Several medical imaging/techniques, including Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) provide 3D information of the human body by means of a stack of parallel cross-sectional images. But a more sophisticated edge detection step has to be performed when the object under study is not well defined by its characteristic density or when an analytical knowledge of the surface of the object is useful for later processings. A new method for medical image segmentation has been developed: it uses the stability and differentiability properties of a continuous modelling of the 3D data. The idea is to build a system of Ordinary Differential Equations which the stable manifold is the surface of the object we are looking for. This technique has been applied to classical edge detection operators: threshold following, laplacian, gradient maximum in its direction. It can be used in 2D as well as in 3D and has been extended to seek particular points of the surface, such as local extrema. The major advantages of this method are as follows: the segmentation and boundary following steps are performed simultaneously, an analytical representation of the surface is obtained straightforwardly and complex objects in which branching problems may occur can be described automatically. Simulations on noisy synthetic images have induced a quantization step to test the sensitiveness to noise of our method with respect to each operator, and to study the influence of all the parameters. Last, this method has been applied to numerous real clinical exams: skull or femur images provided by CT, MR images of a cerebral tumor and of the ventricular system. These results show the reliability and the efficiency of this new method of segmentation.

  15. 3D design and electric simulation of a silicon drift detector using a spiral biasing adapter

    Science.gov (United States)

    Li, Yu-yun; Xiong, Bo; Li, Zheng

    2016-09-01

    The detector system of combining a spiral biasing adapter (SBA) with a silicon drift detector (SBA-SDD) is largely different from the traditional silicon drift detector (SDD), including the spiral SDD. It has a spiral biasing adapter of the same design as a traditional spiral SDD and an SDD with concentric rings having the same radius. Compared with the traditional spiral SDD, the SBA-SDD separates the spiral's functions of biasing adapter and the p-n junction definition. In this paper, the SBA-SDD is simulated using a Sentaurus TCAD tool, which is a full 3D device simulation tool. The simulated electric characteristics include electric potential, electric field, electron concentration, and single event effect. Because of the special design of the SBA-SDD, the SBA can generate an optimum drift electric field in the SDD, comparable with the conventional spiral SDD, while the SDD can be designed with concentric rings to reduce surface area. Also the current and heat generated in the SBA are separated from the SDD. To study the single event response, we simulated the induced current caused by incident heavy ions (20 and 50 μm penetration length) with different linear energy transfer (LET). The SBA-SDD can be used just like a conventional SDD, such as X-ray detector for energy spectroscopy and imaging, etc.

  16. Geometric and topological feature extraction of linear segments from 2D cross-section data of 3D point clouds

    Science.gov (United States)

    Ramamurthy, Rajesh; Harding, Kevin; Du, Xiaoming; Lucas, Vincent; Liao, Yi; Paul, Ratnadeep; Jia, Tao

    2015-05-01

    Optical measurement techniques are often employed to digitally capture three dimensional shapes of components. The digital data density output from these probes range from a few discrete points to exceeding millions of points in the point cloud. The point cloud taken as a whole represents a discretized measurement of the actual 3D shape of the surface of the component inspected to the measurement resolution of the sensor. Embedded within the measurement are the various features of the part that make up its overall shape. Part designers are often interested in the feature information since those relate directly to part function and to the analytical models used to develop the part design. Furthermore, tolerances are added to these dimensional features, making their extraction a requirement for the manufacturing quality plan of the product. The task of "extracting" these design features from the point cloud is a post processing task. Due to measurement repeatability and cycle time requirements often automated feature extraction from measurement data is required. The presence of non-ideal features such as high frequency optical noise and surface roughness can significantly complicate this feature extraction process. This research describes a robust process for extracting linear and arc segments from general 2D point clouds, to a prescribed tolerance. The feature extraction process generates the topology, specifically the number of linear and arc segments, and the geometry equations of the linear and arc segments automatically from the input 2D point clouds. This general feature extraction methodology has been employed as an integral part of the automated post processing algorithms of 3D data of fine features.

  17. An adaptive algorithm for tracking 3D bead displacements: application in biological experiments

    International Nuclear Information System (INIS)

    This paper presents a feature-vector-based relaxation method (FVRM) to track bead displacements within a three-dimensional (3D) volume. The FVRM merges the feature vector method, a technique used in tracking bead displacements in biological gels, with the relaxation method, an algorithm employed successfully in tracking bead pairs in fluids. More specifically, the FVRM evaluates the probability of a bead pairing event based on the quasi-rigidity condition between the feature vectors of a bead and its candidate positions within a searching domain. Computational efficiency is improved via the introduction of an adaptive searching domain size and mismatches are reduced via a two-directional matching strategy. The algorithm is validated using simulated 3D bead displacements caused by a force dipole within a linear elastic gel. Results demonstrate a consistently high recovery ratio (above 98%) and low mismatch ratio (below 0.1%) for tracking parameter (mean bead distance/maximum bead displacement) greater than 0.73. (paper)

  18. The Singularity Threshold of the Nonlinear Sigma Model Using 3D Adaptive Mesh Refinement

    CERN Document Server

    Liebling, S L

    2002-01-01

    Numerical solutions to the nonlinear sigma model (NLSM), a wave map from 3+1 Minkowski space to S^3, are computed in three spatial dimensions (3D) using adaptive mesh refinement (AMR). For initial data with compact support the model is known to have two regimes, one in which regular initial data forms a singularity and another in which the energy is dispersed to infinity. The transition between these regimes has been shown in spherical symmetry to demonstrate threshold behavior similar to that between black hole formation and dispersal in gravitating theories. Here, I generalize the result by removing the assumption of spherical symmetry. The evolutions suggest that the spherically symmetric critical solution remains an intermediate attractor separating the two end states.

  19. Adaptive Probabilistic Tracking Embedded in Smart Cameras for Distributed Surveillance in a 3D Model

    Directory of Open Access Journals (Sweden)

    Sven Fleck

    2006-12-01

    Full Text Available Tracking applications based on distributed and embedded sensor networks are emerging today, both in the fields of surveillance and industrial vision. Traditional centralized approaches have several drawbacks, due to limited communication bandwidth, computational requirements, and thus limited spatial camera resolution and frame rate. In this article, we present network-enabled smart cameras for probabilistic tracking. They are capable of tracking objects adaptively in real time and offer a very bandwidthconservative approach, as the whole computation is performed embedded in each smart camera and only the tracking results are transmitted, which are on a higher level of abstraction. Based on this, we present a distributed surveillance system. The smart cameras' tracking results are embedded in an integrated 3D environment as live textures and can be viewed from arbitrary perspectives. Also a georeferenced live visualization embedded in Google Earth is presented.

  20. Implementation of an adaptive feed speed 3D NURBS interpolation algorithm

    Institute of Scientific and Technical Information of China (English)

    LIANG Hong-bin; WANG Yong-zhang; LI Xia

    2006-01-01

    NURBS (non-uniform rational B-spline) interpolation algorithms have been provided in modern CNC(computer numerical control) systems.However,most of them focus on a constant feed speed without considering the contour accuracy.In order to deal with this problem,an adaptive feed speed interpolation algorithm for 3D NURBS parametric curves with confined chord errors is proposed.When the instantaneous radius of the curvature is small enough,the proposed interpolation algorithm automatically reduces the feed speed to meet the specified chord error.In the other situation it uses the second-order Taylor's expansions approximation interpolation algorithm to obtain a constant feed speed so that the contour accuracy in the CNC system is guaranteed.Experimental results were provided to verify the feasibility and precision of the proposed interpolation algorithm.

  1. 3D Continuum Radiative Transfer. An adaptive grid construction algorithm based on the Monte Carlo method

    Science.gov (United States)

    Niccolini, G.; Alcolea, J.

    Solving the radiative transfer problem is a common problematic to may fields in astrophysics. With the increasing angular resolution of spatial or ground-based telescopes (VLTI, HST) but also with the next decade instruments (NGST, ALMA, ...), astrophysical objects reveal and will certainly reveal complex spatial structures. Consequently, it is necessary to develop numerical tools being able to solve the radiative transfer equation in three dimensions in order to model and interpret these observations. I present a 3D radiative transfer program, using a new method for the construction of an adaptive spatial grid, based on the Monte Claro method. With the help of this tools, one can solve the continuum radiative transfer problem (e.g. a dusty medium), computes the temperature structure of the considered medium and obtain the flux of the object (SED and images).

  2. Assessment of DICOM Viewers Capable of Loading Patient-specific 3D Models Obtained by Different Segmentation Platforms in the Operating Room.

    Science.gov (United States)

    Lo Presti, Giuseppe; Carbone, Marina; Ciriaci, Damiano; Aramini, Daniele; Ferrari, Mauro; Ferrari, Vincenzo

    2015-10-01

    Patient-specific 3D models obtained by the segmentation of volumetric diagnostic images play an increasingly important role in surgical planning. Surgeons use the virtual models reconstructed through segmentation to plan challenging surgeries. Many solutions exist for the different anatomical districts and surgical interventions. The possibility to bring the 3D virtual reconstructions with native radiological images in the operating room is essential for fostering the use of intraoperative planning. To the best of our knowledge, current DICOM viewers are not able to simultaneously connect to the picture archiving and communication system (PACS) and import 3D models generated by external platforms to allow a straight integration in the operating room. A total of 26 DICOM viewers were evaluated: 22 open source and four commercial. Two DICOM viewers can connect to PACS and import segmentations achieved by other applications: Synapse 3D® by Fujifilm and OsiriX by University of Geneva. We developed a software network that converts diffuse visual tool kit (VTK) format 3D model segmentations, obtained by any software platform, to a DICOM format that can be displayed using OsiriX or Synapse 3D. Both OsiriX and Synapse 3D were suitable for our purposes and had comparable performance. Although Synapse 3D loads native images and segmentations faster, the main benefits of OsiriX are its user-friendly loading of elaborated images and it being both free of charge and open source. PMID:25739346

  3. CT and MRI assessment and characterization using segmentation and 3D modeling techniques: applications to muscle, bone and brain

    Directory of Open Access Journals (Sweden)

    Paolo Gargiulo

    2014-03-01

    Full Text Available This paper reviews the novel use of CT and MRI data and image processing tools to segment and reconstruct tissue images in 3D to determine characteristics of muscle, bone and brain.This to study and simulate the structural changes occurring in healthy and pathological conditions as well as in response to clinical treatments. Here we report the application of this methodology to evaluate and quantify: 1. progression of atrophy in human muscle subsequent to permanent lower motor neuron (LMN denervation, 2. muscle recovery as induced by functional electrical stimulation (FES, 3. bone quality in patients undergoing total hip replacement and 4. to model the electrical activity of the brain. Study 1: CT data and segmentation techniques were used to quantify changes in muscle density and composition by associating the Hounsfield unit values of muscle, adipose and fibrous connective tissue with different colors. This method was employed to monitor patients who have permanent muscle LMN denervation in the lower extremities under two different conditions: permanent LMN denervated not electrically stimulated and stimulated. Study 2: CT data and segmentation techniques were employed, however, in this work we assessed bone and muscle conditions in the pre-operative CT scans of patients scheduled to undergo total hip replacement. In this work, the overall anatomical structure, the bone mineral density (BMD and compactness of quadriceps muscles and proximal femoral was computed to provide a more complete view for surgeons when deciding which implant technology to use. Further, a Finite element analysis provided a map of the strains around the proximal femur socket when solicited by typical stresses caused by an implant press fitting. Study 3 describes a method to model the electrical behavior of human brain using segmented MR images. The aim of the work is to use these models to predict the electrical activity of the human brain under normal and pathological

  4. Automatic Segmentation of Colon in 3D CT Images and Removal of Opacified Fluid Using Cascade Feed Forward Neural Network

    Directory of Open Access Journals (Sweden)

    K. Gayathri Devi

    2015-01-01

    Full Text Available Purpose. Colon segmentation is an essential step in the development of computer-aided diagnosis systems based on computed tomography (CT images. The requirement for the detection of the polyps which lie on the walls of the colon is much needed in the field of medical imaging for diagnosis of colorectal cancer. Methods. The proposed work is focused on designing an efficient automatic colon segmentation algorithm from abdominal slices consisting of colons, partial volume effect, bowels, and lungs. The challenge lies in determining the exact colon enhanced with partial volume effect of the slice. In this work, adaptive thresholding technique is proposed for the segmentation of air packets, machine learning based cascade feed forward neural network enhanced with boundary detection algorithms are used which differentiate the segments of the lung and the fluids which are sediment at the side wall of colon and by rejecting bowels based on the slice difference removal method. The proposed neural network method is trained with Bayesian regulation algorithm to determine the partial volume effect. Results. Experiment was conducted on CT database images which results in 98% accuracy and minimal error rate. Conclusions. The main contribution of this work is the exploitation of neural network algorithm for removal of opacified fluid to attain desired colon segmentation result.

  5. Adaptive Iterative Dose Reduction Using Three Dimensional Processing (AIDR3D improves chest CT image quality and reduces radiation exposure.

    Directory of Open Access Journals (Sweden)

    Tsuneo Yamashiro

    Full Text Available To assess the advantages of Adaptive Iterative Dose Reduction using Three Dimensional Processing (AIDR3D for image quality improvement and dose reduction for chest computed tomography (CT.Institutional Review Boards approved this study and informed consent was obtained. Eighty-eight subjects underwent chest CT at five institutions using identical scanners and protocols. During a single visit, each subject was scanned using different tube currents: 240, 120, and 60 mA. Scan data were converted to images using AIDR3D and a conventional reconstruction mode (without AIDR3D. Using a 5-point scale from 1 (non-diagnostic to 5 (excellent, three blinded observers independently evaluated image quality for three lung zones, four patterns of lung disease (nodule/mass, emphysema, bronchiolitis, and diffuse lung disease, and three mediastinal measurements (small structure visibility, streak artifacts, and shoulder artifacts. Differences in these scores were assessed by Scheffe's test.At each tube current, scans using AIDR3D had higher scores than those without AIDR3D, which were significant for lung zones (p<0.0001 and all mediastinal measurements (p<0.01. For lung diseases, significant improvements with AIDR3D were frequently observed at 120 and 60 mA. Scans with AIDR3D at 120 mA had significantly higher scores than those without AIDR3D at 240 mA for lung zones and mediastinal streak artifacts (p<0.0001, and slightly higher or equal scores for all other measurements. Scans with AIDR3D at 60 mA were also judged superior or equivalent to those without AIDR3D at 120 mA.For chest CT, AIDR3D provides better image quality and can reduce radiation exposure by 50%.

  6. A Rapid and Efficient 2D/3D Nuclear Segmentation Method for Analysis of Early Mouse Embryo and Stem Cell Image Data

    Directory of Open Access Journals (Sweden)

    Xinghua Lou

    2014-03-01

    Full Text Available Segmentation is a fundamental problem that dominates the success of microscopic image analysis. In almost 25 years of cell detection software development, there is still no single piece of commercial software that works well in practice when applied to early mouse embryo or stem cell image data. To address this need, we developed MINS (modular interactive nuclear segmentation as a MATLAB/C++-based segmentation tool tailored for counting cells and fluorescent intensity measurements of 2D and 3D image data. Our aim was to develop a tool that is accurate and efficient yet straightforward and user friendly. The MINS pipeline comprises three major cascaded modules: detection, segmentation, and cell position classification. An extensive evaluation of MINS on both 2D and 3D images, and comparison to related tools, reveals improvements in segmentation accuracy and usability. Thus, its accuracy and ease of use will allow MINS to be implemented for routine single-cell-level image analyses.

  7. A systematic review of image segmentation methodology, used in the additive manufacture of patient-specific 3D printed models of the cardiovascular system

    Science.gov (United States)

    Byrne, N; Velasco Forte, M; Tandon, A; Valverde, I

    2016-01-01

    Background Shortcomings in existing methods of image segmentation preclude the widespread adoption of patient-specific 3D printing as a routine decision-making tool in the care of those with congenital heart disease. We sought to determine the range of cardiovascular segmentation methods and how long each of these methods takes. Methods A systematic review of literature was undertaken. Medical imaging modality, segmentation methods, segmentation time, segmentation descriptive quality (SDQ) and segmentation software were recorded. Results Totally 136 studies met the inclusion criteria (1 clinical trial; 80 journal articles; 55 conference, technical and case reports). The most frequently used image segmentation methods were brightness thresholding, region growing and manual editing, as supported by the most popular piece of proprietary software: Mimics (Materialise NV, Leuven, Belgium, 1992–2015). The use of bespoke software developed by individual authors was not uncommon. SDQ indicated that reporting of image segmentation methods was generally poor with only one in three accounts providing sufficient detail for their procedure to be reproduced. Conclusions and implication of key findings Predominantly anecdotal and case reporting precluded rigorous assessment of risk of bias and strength of evidence. This review finds a reliance on manual and semi-automated segmentation methods which demand a high level of expertise and a significant time commitment on the part of the operator. In light of the findings, we have made recommendations regarding reporting of 3D printing studies. We anticipate that these findings will encourage the development of advanced image segmentation methods. PMID:27170842

  8. A systematic review of image segmentation methodology, used in the additive manufacture of patient-specific 3D printed models of the cardiovascular system

    Directory of Open Access Journals (Sweden)

    N Byrne

    2016-04-01

    Full Text Available Background Shortcomings in existing methods of image segmentation preclude the widespread adoption of patient-specific 3D printing as a routine decision-making tool in the care of those with congenital heart disease. We sought to determine the range of cardiovascular segmentation methods and how long each of these methods takes. Methods A systematic review of literature was undertaken. Medical imaging modality, segmentation methods, segmentation time, segmentation descriptive quality (SDQ and segmentation software were recorded. Results Totally 136 studies met the inclusion criteria (1 clinical trial; 80 journal articles; 55 conference, technical and case reports. The most frequently used image segmentation methods were brightness thresholding, region growing and manual editing, as supported by the most popular piece of proprietary software: Mimics (Materialise NV, Leuven, Belgium, 1992–2015. The use of bespoke software developed by individual authors was not uncommon. SDQ indicated that reporting of image segmentation methods was generally poor with only one in three accounts providing sufficient detail for their procedure to be reproduced. Conclusions and implication of key findings Predominantly anecdotal and case reporting precluded rigorous assessment of risk of bias and strength of evidence. This review finds a reliance on manual and semi-automated segmentation methods which demand a high level of expertise and a significant time commitment on the part of the operator. In light of the findings, we have made recommendations regarding reporting of 3D printing studies. We anticipate that these findings will encourage the development of advanced image segmentation methods.

  9. Comparative evaluation of a novel 3D segmentation algorithm on in-treatment radiotherapy cone beam CT images

    Science.gov (United States)

    Price, Gareth; Moore, Chris

    2007-03-01

    Image segmentation and delineation is at the heart of modern radiotherapy, where the aim is to deliver as high a radiation dose as possible to a cancerous target whilst sparing the surrounding healthy tissues. This, of course, requires that a radiation oncologist dictates both where the tumour and any nearby critical organs are located. As well as in treatment planning, delineation is of vital importance in image guided radiotherapy (IGRT): organ motion studies demand that features across image databases are accurately segmented, whilst if on-line adaptive IGRT is to become a reality, speedy and correct target identification is a necessity. Recently, much work has been put into the development of automatic and semi-automatic segmentation tools, often using prior knowledge to constrain some grey level, or derivative thereof, interrogation algorithm. It is hoped that such techniques can be applied to organ at risk and tumour segmentation in radiotherapy. In this work, however, we make the assumption that grey levels do not necessarily determine a tumour's extent, especially in CT where the attenuation coefficient can often vary little between cancerous and normal tissue. In this context we present an algorithm that generates a discontinuity free delineation surface driven by user placed, evidence based support points. In regions of sparse user supplied information, prior knowledge, in the form of a statistical shape model, provides guidance. A small case study is used to illustrate the method. Multiple observers (between 3 and 7) used both the presented tool and a commercial manual contouring package to delineate the bladder on a serially imaged (10 cone beam CT volumes ) prostate patient. A previously presented shape analysis technique is used to quantitatively compare the observer variability.

  10. Locally adaptive 2D-3D registration using vascular structure model for liver catheterization.

    Science.gov (United States)

    Kim, Jihye; Lee, Jeongjin; Chung, Jin Wook; Shin, Yeong-Gil

    2016-03-01

    Two-dimensional-three-dimensional (2D-3D) registration between intra-operative 2D digital subtraction angiography (DSA) and pre-operative 3D computed tomography angiography (CTA) can be used for roadmapping purposes. However, through the projection of 3D vessels, incorrect intersections and overlaps between vessels are produced because of the complex vascular structure, which makes it difficult to obtain the correct solution of 2D-3D registration. To overcome these problems, we propose a registration method that selects a suitable part of a 3D vascular structure for a given DSA image and finds the optimized solution to the partial 3D structure. The proposed algorithm can reduce the registration errors because it restricts the range of the 3D vascular structure for the registration by using only the relevant 3D vessels with the given DSA. To search for the appropriate 3D partial structure, we first construct a tree model of the 3D vascular structure and divide it into several subtrees in accordance with the connectivity. Then, the best matched subtree with the given DSA image is selected using the results from the coarse registration between each subtree and the vessels in the DSA image. Finally, a fine registration is conducted to minimize the difference between the selected subtree and the vessels of the DSA image. In experimental results obtained using 10 clinical datasets, the average distance errors in the case of the proposed method were 2.34±1.94mm. The proposed algorithm converges faster and produces more correct results than the conventional method in evaluations on patient datasets. PMID:26824922

  11. [An adaptive threshloding segmentation method for urinary sediment image].

    Science.gov (United States)

    Li, Yongming; Zeng, Xiaoping; Qin, Jian; Han, Liang

    2009-02-01

    In this paper is proposed a new method to solve the segmentation of the complicated defocusing urinary sediment image. The main points of the method are: (1) using wavelet transforms and morphology to erase the effect of defocusing and realize the first segmentation, (2) using adaptive threshold processing in accordance to the subimages after wavelet processing, and (3) using 'peel off' algorithm to deal with the overlapped cells' segmentations. The experimental results showed that this method was not affected by the defocusing, and it made good use of many kinds of characteristics of the images. So this new mehtod can get very precise segmentation; it is effective for defocusing urinary sediment image segmentation.

  12. Liver Tumor Segmentation from MR Images Using 3D Fast Marching Algorithm and Single Hidden Layer Feedforward Neural Network

    Directory of Open Access Journals (Sweden)

    Trong-Ngoc Le

    2016-01-01

    Full Text Available Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods. Our proposed scheme consists of four main stages. Firstly, the region of interest (ROI image which contains the liver tumor region in the T1-weighted MR image series was extracted by using seed points. The noise in this ROI image was reduced and the boundaries were enhanced. A 3D fast marching algorithm was applied to generate the initial labeled regions which are considered as teacher regions. A single hidden layer feedforward neural network (SLFN, which was trained by a noniterative algorithm, was employed to classify the unlabeled voxels. Finally, the postprocessing stage was applied to extract and refine the liver tumor boundaries. The liver tumors determined by our scheme were compared with those manually traced by a radiologist, used as the “ground truth.” Results. The study was evaluated on two datasets of 25 tumors from 16 patients. The proposed scheme obtained the mean volumetric overlap error of 27.43% and the mean percentage volume error of 15.73%. The mean of the average surface distance, the root mean square surface distance, and the maximal surface distance were 0.58 mm, 1.20 mm, and 6.29 mm, respectively.

  13. Multi-view 3D human pose estimation combining single-frame recovery, temporal integration and model adaptation

    NARCIS (Netherlands)

    Hofmann, K.M.; Gavrilla, D.M.

    2009-01-01

    We present a system for the estimation of unconstrained 3D human upper body movement from multiple cameras. Its main novelty lies in the integration of three components: single frame pose recovery, temporal integration and model adaptation. Single frame pose recovery consists of a hypothesis generat

  14. Multi-view 3D human pose estimation combining single-frame recovery, temporal integration and model adaptation

    NARCIS (Netherlands)

    Hofmann, K.M.; Gavrila, D.M.

    2009-01-01

    We present a system for the estimation of unconstrained 3D human upper body movement from multiple cameras. Its main novelty lies in the integration of three components: single-frame pose recovery, temporal integration and model adaptation. Single-frame pose recovery consists of a hypothesis generat

  15. Adaptive segmentation of digital mammograms through reinforcement learning

    Institute of Scientific and Technical Information of China (English)

    LIU Xin-yue; FANG Xiao-xuan; HUANG Lian-qing

    2005-01-01

    An approach based on reinfocement learning for the automated segmentation is presented. The approach consists of two modules:segmentation module and learning module. The segmentation module uses the region-growing algorithm combined with the smooth filtering and the morphological filtering to segment mammograms. The learning module uses the segmentation output as the feedback to learn to select the optimal parameter settings of the segmentation algorithm according to the image properties using reinforcement learning techniques. The approach can adapt itself to various kinds of mammograms through training and therefore obviates the tedious and error-prone tuning of parameter settings manually. Quantitative test results show that the approach is accurate for several kinds of mammograms. Compared to previously proposed approaches,the approach is more adaptable to different mammograms.

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

    OpenAIRE

    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 to...

  17. Alzheimer's Disease Diagnostics by a Deeply Supervised Adaptable 3D Convolutional Network

    OpenAIRE

    Hosseini-Asl, Ehsan; Gimel'farb, Georgy; El-Baz, Ayman

    2016-01-01

    Early diagnosis, playing an important role in preventing progress and treating the Alzheimer's disease (AD), is based on classification of features extracted from brain images. The features have to accurately capture main AD-related variations of anatomical brain structures, such as, e.g., ventricles size, hippocampus shape, cortical thickness, and brain volume. This paper proposes to predict the AD with a deep 3D convolutional neural network (3D-CNN), which can learn generic features capturi...

  18. The two sides of complement C3d: evolution of electrostatics in a link between innate and adaptive immunity.

    Directory of Open Access Journals (Sweden)

    Chris A Kieslich

    Full Text Available The interaction between complement fragment C3d and complement receptor 2 (CR2 is a key aspect of complement immune system activation, and is a component in a link between innate and adaptive immunities. The complement immune system is an ancient mechanism for defense, and can be found in species that have been on Earth for the last 600 million years. However, the link between the complement system and adaptive immunity, which is formed through the association of the B-cell co-receptor complex, including the C3d-CR2 interaction, is a much more recent adaptation. Human C3d and CR2 have net charges of -1 and +7 respectively, and are believed to have evolved favoring the role of electrostatics in their functions. To investigate the role of electrostatics in the function and evolution of human C3d and CR2, we have applied electrostatic similarity methods to identify regions of evolutionarily conserved electrostatic potential based on 24 homologues of complement C3d and 4 homologues of CR2. We also examine the effects of structural perturbation, as introduced through molecular dynamics and mutations, on spatial distributions of electrostatic potential to identify perturbation resistant regions, generated by so-called electrostatic "hot-spots". Distributions of electrostatic similarity based on families of perturbed structures illustrate the presence of electrostatic "hot-spots" at the two functional sites of C3d, while the surface of CR2 lacks electrostatic "hot-spots" despite its excessively positive nature. We propose that the electrostatic "hot-spots" of C3d have evolved to optimize its dual-functionality (covalently attaching to pathogen surfaces and interaction with CR2, which are both necessary for the formation B-cell co-receptor complexes. Comparison of the perturbation resistance of the electrostatic character of the homologues of C3d suggests that there was an emergence of a new role of electrostatics, and a transition in the function of C3

  19. A mesh adaptivity scheme on the Landau-de Gennes functional minimization case in 3D, and its driving efficiency

    Science.gov (United States)

    Bajc, Iztok; Hecht, Frédéric; Žumer, Slobodan

    2016-09-01

    This paper presents a 3D mesh adaptivity strategy on unstructured tetrahedral meshes by a posteriori error estimates based on metrics derived from the Hessian of a solution. The study is made on the case of a nonlinear finite element minimization scheme for the Landau-de Gennes free energy functional of nematic liquid crystals. Newton's iteration for tensor fields is employed with steepest descent method possibly stepping in. Aspects relating the driving of mesh adaptivity within the nonlinear scheme are considered. The algorithmic performance is found to depend on at least two factors: when to trigger each single mesh adaptation, and the precision of the correlated remeshing. Each factor is represented by a parameter, with its values possibly varying for every new mesh adaptation. We empirically show that the time of the overall algorithm convergence can vary considerably when different sequences of parameters are used, thus posing a question about optimality. The extensive testings and debugging done within this work on the simulation of systems of nematic colloids substantially contributed to the upgrade of an open source finite element-oriented programming language to its 3D meshing possibilities, as also to an outer 3D remeshing module.

  20. Object-oriented philosophy in designing adaptive finite-element package for 3D elliptic deferential equations

    Science.gov (United States)

    Zhengyong, R.; Jingtian, T.; Changsheng, L.; Xiao, X.

    2007-12-01

    Although adaptive finite-element (AFE) analysis is becoming more and more focused in scientific and engineering fields, its efficient implementations are remain to be a discussed problem as its more complex procedures. In this paper, we propose a clear C++ framework implementation to show the powerful properties of Object-oriented philosophy (OOP) in designing such complex adaptive procedure. In terms of the modal functions of OOP language, the whole adaptive system is divided into several separate parts such as the mesh generation or refinement, a-posterior error estimator, adaptive strategy and the final post processing. After proper designs are locally performed on these separate modals, a connected framework of adaptive procedure is formed finally. Based on the general elliptic deferential equation, little efforts should be added in the adaptive framework to do practical simulations. To show the preferable properties of OOP adaptive designing, two numerical examples are tested. The first one is the 3D direct current resistivity problem in which the powerful framework is efficiently shown as only little divisions are added. And then, in the second induced polarization£¨IP£©exploration case, new adaptive procedure is easily added which adequately shows the strong extendibility and re-usage of OOP language. Finally we believe based on the modal framework adaptive implementation by OOP methodology, more advanced adaptive analysis system will be available in future.

  1. Value of MR 3D-FIESTA sequence in displaying the cavernous segment of oculomotor nerve%MR3D-FIESTA序列对动眼神经海绵窦段的显示情况及意义

    Institute of Scientific and Technical Information of China (English)

    安奇; 杨靖; 朱越; 黄立新; 周军

    2011-01-01

    目的:应用MR 3D-FIESTA序列对动眼神经海绵窦段进行解剖显示与研究,为临床提供进一步MR影像解剖信息.方法:38例正常志愿者与8例动眼神经麻痹患者均行常规SE序列及3D-FIESTA序列扫描,利用多平面重组(MPR)和曲面重建(CR)技术从不同角度显示动眼神经海绵窦段的走行情况.结果:38例正常志愿者中40.8%(15例)可以清晰显示动眼神经海绵窦段,57.8%(22例)海绵窦段显示欠清晰,可显示部分动眼神经,1.3%(1例)海绵窦段未见显示.8例动眼神经麻痹患者,12.5%可清晰显示动眼神经海绵窦段,62.5%动眼神经部分显示,25%动眼神经未见显示.结论:MR 3D-FIESTA序列结合MR后处理技术能够在一定程度上提供动眼神经海绵窦段的解剖信息,对于病变累及海绵窦区显示情况较差,但是可提供间接解剖形态信息,为诊断及进一步的手术提供帮助.%Objective: To asses the value of 3D-FIESTA sequence in displaying the cavernous sinus segment of oculomotor nerve in order to obtain more detailed MR anatomical data of this nerve for clinical application. Methods: Thirty-eight normal volunteers and 8 patients with oculomotor nerve palsy underwent conventional sequence and 3D-FIESTA sequence associated with multi-planar reformation(MPR) and curved planar reconstruction(CR) from different angle to show the pathway of the cavernous sinus segment of oculomotor nerve. Results: In the 38 normal volunteers, the cavernous segment of oculomotor nerve can be showed clearly in 40.8%(15 cases), can not be showed clearly in 57.8%(22 cases), only a part of the segment was showed, and the nerve can not be showed in 1.3%(1 case). In the 8 patients with oculomotor nerve palsy, the cavernous segment of the nerve can be showed clearly in 12.5%, only a part of the nerve can be showed in 62.5%, in 25% of cases the nerve was not showed. Conclusion: To some extent, MR 3D-FIESTA sequence with post-processing techniques can be

  2. Graphic 3D ergonomic database in evaluation of virtual models of kitchen design/adaptation for needs of handicapped persons

    OpenAIRE

    Branowski, B.; Rychlik, M.; Sydor, M.; Zabłocki, M.

    2011-01-01

    The paper presents a concept for the utilisation of anthropometric and biomechanical graphic 3D database of a motorically handicapped person using a wheelchair for purposes of analysis and assessment of kitchen space design. Contemporary tendencies in kitchen design or adaptation for disabled persons or senior citizens were discussed. Methodological assumptions as well as a test station for measurements of reach of arms and forces for a male disabled person sitting in a wheelchair were presen...

  3. The Two Sides of Complement C3d: Evolution of Electrostatics in a Link between Innate and Adaptive Immunity

    OpenAIRE

    Kieslich, Chris A.; Dimitrios Morikis

    2012-01-01

    The interaction between complement fragment C3d and complement receptor 2 (CR2) is a key aspect of complement immune system activation, and is a component in a link between innate and adaptive immunities. The complement immune system is an ancient mechanism for defense, and can be found in species that have been on Earth for the last 600 million years. However, the link between the complement system and adaptive immunity, which is formed through the association of the B-cell co-receptor compl...

  4. Adaptive optofluidic lens(es) for switchable 2D and 3D imaging

    Science.gov (United States)

    Huang, Hanyang; Wei, Kang; Zhao, Yi

    2016-03-01

    The stereoscopic image is often captured using dual cameras arranged side-by-side and optical path switching systems such as two separate solid lenses or biprism/mirrors. The miniaturization of the overall size of current stereoscopic devices down to several millimeters is at a sacrifice of further device size shrinkage. The limited light entry worsens the final image resolution and brightness. It is known that optofluidics offer good re-configurability for imaging systems. Leveraging this technique, we report a reconfigurable optofluidic system whose optical layout can be swapped between a singlet lens with 10 mm in diameter and a pair of binocular lenses with each lens of 3 mm in diameter for switchable two-dimensional (2D) and three-dimensional (3D) imaging. The singlet and the binoculars share the same optical path and the same imaging sensor. The singlet acquires a 3D image with better resolution and brightness, while the binoculars capture stereoscopic image pairs for 3D vision and depth perception. The focusing power tuning capability of the singlet and the binoculars enable image acquisition at varied object planes by adjusting the hydrostatic pressure across the lens membrane. The vari-focal singlet and binoculars thus work interchangeably and complementarily. The device is thus expected to have applications in robotic vision, stereoscopy, laparoendoscopy and miniaturized zoom lens system.

  5. A mesh adaptivity scheme on the Landau-de Gennes functional minimization case in 3D, and its driving efficiency

    CERN Document Server

    Bajc, Iztok; Žumer, Slobodan

    2015-01-01

    This paper presents a 3D mesh adaptivity strategy on unstructured tetrahedral meshes by a posteriori error estimates based on metrics, studied on the case of a nonlinear finite element minimization scheme for the Landau-de Gennes free energy functional of nematic liquid crystals. Newton's iteration for tensor fields is employed with steepest descent method possibly stepping in. Aspects relating the driving of mesh adaptivity within the nonlinear scheme are considered. The algorithmic performance is found to depend on at least two factors: when to trigger each single mesh adaptation, and the precision of the correlated remeshing. Each factor is represented by a parameter, with its values possibly varying for every new mesh adaptation. We empirically show that the time of the overall algorithm convergence can vary considerably when different sequences of parameters are used, thus posing a question about optimality. The extensive testings and debugging done within this work on the simulation of systems of nemati...

  6. MO-G-17A-03: MR-Based Cortical Bone Segmentation for PET Attenuation Correction with a Non-UTE 3D Fast GRE Sequence

    Energy Technology Data Exchange (ETDEWEB)

    Ai, H; Pan, T [The University of Texas MD Anderson Cancer Center, Houston, TX (United States); The University of Texas Graduate School of Biomedical Science, Houston, TX (United States); Hwang, K [GE Healthcare, Houston, TX (United States)

    2014-06-15

    Purpose: To determine the feasibility of identifying cortical bone on MR images with a short-TE 3D fast-GRE sequence for attenuation correction of PET data in PET/MR. Methods: A water-fat-bone phantom was constructed with two pieces of beef shank. MR scans were performed on a 3T MR scanner (GE Discovery™ MR750). A 3D GRE sequence was first employed to measure the level of residual signal in cortical bone (TE{sub 1}/TE{sub 2}/TE{sub 3}=2.2/4.4/6.6ms, TR=20ms, flip angle=25°). For cortical bone segmentation, a 3D fast-GRE sequence (TE/TR=0.7/1.9ms, acquisition voxel size=2.5×2.5×3mm{sup 3}) was implemented along with a 3D Dixon sequence (TE{sub 1}/TE{sub 2}/TR=1.2/2.3/4.0ms, acquisition voxel size=1.25×1.25×3mm{sup 3}) for water/fat imaging. Flip angle (10°), acquisition bandwidth (250kHz), FOV (480×480×144mm{sup 3}) and reconstructed voxel size (0.94×0.94×1.5mm{sup 3}) were kept the same for both sequences. Soft tissue and fat tissue were first segmented on the reconstructed water/fat image. A tissue mask was created by combining the segmented water/fat masks, which was then applied on the fast-GRE image (MRFGRE). A second mask was created to remove the Gibbs artifacts present in regions in close vicinity to the phantom. MRFGRE data was smoothed with a 3D anisotropic diffusion filter for noise reduction, after which cortical bone and air was separated using a threshold determined from the histogram. Results: There is signal in the cortical bone region in the 3D GRE images, indicating the possibility of separating cortical bone and air based on signal intensity from short-TE MR image. The acquisition time for the 3D fast-GRE sequence was 17s, which can be reduced to less than 10s with parallel imaging. The attenuation image created from water-fat-bone segmentation is visually similar compared to reference CT. Conclusion: Cortical bone and air can be separated based on intensity in MR image with a short-TE 3D fast-GRE sequence. Further research is required

  7. MO-G-17A-03: MR-Based Cortical Bone Segmentation for PET Attenuation Correction with a Non-UTE 3D Fast GRE Sequence

    International Nuclear Information System (INIS)

    Purpose: To determine the feasibility of identifying cortical bone on MR images with a short-TE 3D fast-GRE sequence for attenuation correction of PET data in PET/MR. Methods: A water-fat-bone phantom was constructed with two pieces of beef shank. MR scans were performed on a 3T MR scanner (GE Discovery™ MR750). A 3D GRE sequence was first employed to measure the level of residual signal in cortical bone (TE1/TE2/TE3=2.2/4.4/6.6ms, TR=20ms, flip angle=25°). For cortical bone segmentation, a 3D fast-GRE sequence (TE/TR=0.7/1.9ms, acquisition voxel size=2.5×2.5×3mm3) was implemented along with a 3D Dixon sequence (TE1/TE2/TR=1.2/2.3/4.0ms, acquisition voxel size=1.25×1.25×3mm3) for water/fat imaging. Flip angle (10°), acquisition bandwidth (250kHz), FOV (480×480×144mm3) and reconstructed voxel size (0.94×0.94×1.5mm3) were kept the same for both sequences. Soft tissue and fat tissue were first segmented on the reconstructed water/fat image. A tissue mask was created by combining the segmented water/fat masks, which was then applied on the fast-GRE image (MRFGRE). A second mask was created to remove the Gibbs artifacts present in regions in close vicinity to the phantom. MRFGRE data was smoothed with a 3D anisotropic diffusion filter for noise reduction, after which cortical bone and air was separated using a threshold determined from the histogram. Results: There is signal in the cortical bone region in the 3D GRE images, indicating the possibility of separating cortical bone and air based on signal intensity from short-TE MR image. The acquisition time for the 3D fast-GRE sequence was 17s, which can be reduced to less than 10s with parallel imaging. The attenuation image created from water-fat-bone segmentation is visually similar compared to reference CT. Conclusion: Cortical bone and air can be separated based on intensity in MR image with a short-TE 3D fast-GRE sequence. Further research is required to optimize the strategy to reduce Gibbs artifacts

  8. Adaptive foreground and shadow segmentation using hidden conditional random fields

    Institute of Scientific and Technical Information of China (English)

    CHU Yi-ping; YE Xiu-zi; QIAN Jiang; ZHANG Yin; ZHANG San-yuan

    2007-01-01

    Video object segmentation is important for video surveillance, object tracking, video object recognition and video editing. An adaptive video segmentation algorithm based on hidden conditional random fields (HCRFs) is proposed, which models spatio-temporal constraints of video sequence. In order to improve the segmentation quality, the weights of spatio-temporal constraints are adaptively updated by on-line learning for HCRFs. Shadows are the factors affecting segmentation quality. To separate foreground objects from the shadows they cast, linear transform for Gaussian distribution of the background is adopted to model the shadow. The experimental results demonstrated that the error ratio of our algorithm is reduced by 23% and 19% respectively,compared with the Gaussian mixture model (GMM) and spatio-temporal Markov random fields (MRFs).

  9. Autonomous Image Segmentation using Density-Adaptive Dendritic Cell Algorithm

    Directory of Open Access Journals (Sweden)

    Vishwambhar Pathak

    2013-08-01

    Full Text Available Contemporary image processing based applications like medical diagnosis automation and analysis of satellite imagery include autonomous image segmentation as inevitable facility. The research done shows the efficiency of an adaptive evolutionary algorithm based on immune system dynamics for the task of autonomous image segmentation. The recognition dynamics of immune-kernels modeled with infinite Gaussian mixture models exhibit the capability to automatically determine appropriate number of segments in presence of noise. In addition, the model using representative density-kernel-parameters processes the information with much reduced space requirements. Experiments conducted with synthetic images as well as real images recorded assured convergence and optimal autonomous model estimation. The segmentation results tested in terms of PBM-index values have been found comparable to those of the Fuzzy C-Means (FCM for the same number of segments as generated by our algorithm.

  10. A comparison study of atlas-based 3D cardiac MRI segmentation: global versus global and local transformations

    Science.gov (United States)

    Daryanani, Aditya; Dangi, Shusil; Ben-Zikri, Yehuda Kfir; Linte, Cristian A.

    2016-03-01

    Magnetic Resonance Imaging (MRI) is a standard-of-care imaging modality for cardiac function assessment and guidance of cardiac interventions thanks to its high image quality and lack of exposure to ionizing radiation. Cardiac health parameters such as left ventricular volume, ejection fraction, myocardial mass, thickness, and strain can be assessed by segmenting the heart from cardiac MRI images. Furthermore, the segmented pre-operative anatomical heart models can be used to precisely identify regions of interest to be treated during minimally invasive therapy. Hence, the use of accurate and computationally efficient segmentation techniques is critical, especially for intra-procedural guidance applications that rely on the peri-operative segmentation of subject-specific datasets without delaying the procedure workflow. Atlas-based segmentation incorporates prior knowledge of the anatomy of interest from expertly annotated image datasets. Typically, the ground truth atlas label is propagated to a test image using a combination of global and local registration. The high computational cost of non-rigid registration motivated us to obtain an initial segmentation using global transformations based on an atlas of the left ventricle from a population of patient MRI images and refine it using well developed technique based on graph cuts. Here we quantitatively compare the segmentations obtained from the global and global plus local atlases and refined using graph cut-based techniques with the expert segmentations according to several similarity metrics, including Dice correlation coefficient, Jaccard coefficient, Hausdorff distance, and Mean absolute distance error.

  11. GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures

    OpenAIRE

    Craven, Michael P; Curtis, K. Mervyn

    2004-01-01

    A complete microcomputer system is described, GesRec3D, which facilitates the data acquisition, segmentation, learning, and recognition of 3-Dimensional arm gestures, with application as a Augmentative and Alternative Communication (AAC) aid for people with motor and speech disability. The gesture data is acquired from a Polhemus electro-magnetic tracker system, with sensors attached to the finger, wrist and elbow of one arm. Coded gestures are linked to user-defined text, to be spoken by a t...

  12. Adaptive Multi-resolution 3D Hartree-Fock-Bogoliubov Solver for Nuclear Structure

    CERN Document Server

    Pei, Junchen; Harrison, Robert; Nazarewicz, Witold; Shi, Yue; Thornton, Scott

    2014-01-01

    Complex many-body systems, such as triaxial and reflection-asymmetric nuclei, weakly-bound halo states, cluster configurations, nuclear fragments produced in heavy-ion fusion reactions, cold Fermi gases, and pasta phases in neutron star crust, they are all characterized by large sizes and complex topologies, in which many geometrical symmetries characteristic of ground-state configurations are broken. A tool of choice to study such complex forms of matter is an adaptive multi-resolution wavelet analysis. This method has generated much excitement since it provides a common framework linking many diversified methodologies across different fields, including signal processing, data compression, harmonic analysis and operator theory, fractals, and quantum field theory. To describe complex superfluid many-fermion systems, we introduce an adaptive pseudo-spectral method for solving self-consistent equations of nuclear density functional theory in three dimensions, without symmetry restrictions. The new adaptive mult...

  13. Accessible bioprinting: adaptation of a low-cost 3D-printer for precise cell placement and stem cell differentiation.

    Science.gov (United States)

    Reid, John A; Mollica, Peter A; Johnson, Garett D; Ogle, Roy C; Bruno, Robert D; Sachs, Patrick C

    2016-06-01

    The precision and repeatability offered by computer-aided design and computer-numerically controlled techniques in biofabrication processes is quickly becoming an industry standard. However, many hurdles still exist before these techniques can be used in research laboratories for cellular and molecular biology applications. Extrusion-based bioprinting systems have been characterized by high development costs, injector clogging, difficulty achieving small cell number deposits, decreased cell viability, and altered cell function post-printing. To circumvent the high-price barrier to entry of conventional bioprinters, we designed and 3D printed components for the adaptation of an inexpensive 'off-the-shelf' commercially available 3D printer. We also demonstrate via goal based computer simulations that the needle geometries of conventional commercially standardized, 'luer-lock' syringe-needle systems cause many of the issues plaguing conventional bioprinters. To address these performance limitations we optimized flow within several microneedle geometries, which revealed a short tapered injector design with minimal cylindrical needle length was ideal to minimize cell strain and accretion. We then experimentally quantified these geometries using pulled glass microcapillary pipettes and our modified, low-cost 3D printer. This systems performance validated our models exhibiting: reduced clogging, single cell print resolution, and maintenance of cell viability without the use of a sacrificial vehicle. Using this system we show the successful printing of human induced pluripotent stem cells (hiPSCs) into Geltrex and note their retention of a pluripotent state 7 d post printing. We also show embryoid body differentiation of hiPSC by injection into differentiation conducive environments, wherein we observed continuous growth, emergence of various evaginations, and post-printing gene expression indicative of the presence of all three germ layers. These data demonstrate an

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

    Science.gov (United States)

    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.

  15. Graph-based Active Learning of Agglomeration (GALA): a Python library to segment 2D and 3D neuroimages

    OpenAIRE

    Juan eNunez-Iglesias; Ryan eKennedy; Plaza, Stephen M.; Anirban eChakraborty; 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 is to perform automatic segmentation of EM images, followed by manual proofreading by experts to fix errors. We developed an algorithm and software library to not only improve the accuracy of the initial automatic segmentation, but also point out the image c...

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

    Science.gov (United States)

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

    2016-03-01

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

  17. Adaptive laser beam forming for laser shock micro-forming for 3D MEMS devices fabrication

    Science.gov (United States)

    Zou, Ran; Wang, Shuliang; Wang, Mohan; Li, Shuo; Huang, Sheng; Lin, Yankun; Chen, Kevin P.

    2016-07-01

    Laser shock micro-forming is a non-thermal laser forming method that use laser-induced shockwave to modify surface properties and to adjust shapes and geometry of work pieces. In this paper, we present an adaptive optical technique to engineer spatial profiles of the laser beam to exert precision control on the laser shock forming process for free-standing MEMS structures. Using a spatial light modulator, on-target laser energy profiles are engineered to control shape, size, and deformation magnitude, which has led to significant improvement of the laser shock processing outcome at micrometer scales. The results presented in this paper show that the adaptive-optics laser beam forming is an effective method to improve both quality and throughput of the laser forming process at micrometer scales.

  18. Wavelet-based adaptive numerical simulation of unsteady 3D flow around a bluff body

    Science.gov (United States)

    de Stefano, Giuliano; Vasilyev, Oleg

    2012-11-01

    The unsteady three-dimensional flow past a two-dimensional bluff body is numerically simulated using a wavelet-based method. The body is modeled by exploiting the Brinkman volume-penalization method, which results in modifying the governing equations with the addition of an appropriate forcing term inside the spatial region occupied by the obstacle. The volume-penalized incompressible Navier-Stokes equations are numerically solved by means of the adaptive wavelet collocation method, where the non-uniform spatial grid is dynamically adapted to the flow evolution. The combined approach is successfully applied to the simulation of vortex shedding flow behind a stationary prism with square cross-section. The computation is conducted at transitional Reynolds numbers, where fundamental unstable three-dimensional vortical structures exist, by well-predicting the unsteady forces arising from fluid-structure interaction.

  19. Electrowetting-based adaptive vari-focal liquid lens array for 3D display

    Science.gov (United States)

    Won, Yong Hyub

    2014-10-01

    Electrowetting is a phenomenon that can control the surface tension of liquid when a voltage is applied. This paper introduces the fabrication method of liquid lens array by the electrowetting phenomenon. The fabricated 23 by 23 lens array has 1mm diameter size with 1.6 mm interval distance between adjacent lenses. The diopter of each lens was - 24~27 operated at 0V to 50V. The lens array chamber fabricated by Deep Reactive-Ion Etching (DRIE) is deposited with IZO and parylene C and tantalum oxide. To prevent water penetration and achieve high dielectric constant, parylene C and tantalum oxide (ɛ = 23 ~ 25) are used respectively. Hydrophobic surface which enables the range of contact angle from 60 to 160 degree is coated to maximize the effect of electrowetting causing wide band of dioptric power. Liquid is injected into each lens chamber by two different ways. First way was self water-oil dosing that uses cosolvent and diffusion effect, while the second way was micro-syringe by the hydrophobic surface properties. To complete the whole process of the lens array fabrication, underwater sealing was performed using UV adhesive that does not dissolve in water. The transient time for changing from concave to convex lens was measured <33ms (at frequency of 1kHz AC voltage.). The liquid lens array was tested unprecedentedly for integral imaging to achieve more advanced depth information of 3D image.

  20. 3D positional control of magnetic levitation system using adaptive control: improvement of positioning control in horizontal plane

    Science.gov (United States)

    Nishino, Toshimasa; Fujitani, Yasuhiro; Kato, Norihiko; Tsuda, Naoaki; Nomura, Yoshihiko; Matsui, Hirokazu

    2012-01-01

    The objective of this paper is to establish a technique that levitates and conveys a hand, a kind of micro-robot, by applying magnetic forces: the hand is assumed to have a function of holding and detaching the objects. The equipment to be used in our experiments consists of four pole-pieces of electromagnets, and is expected to work as a 4DOF drive unit within some restricted range of 3D space: the three DOF are corresponding to 3D positional control and the remaining one DOF, rotational oscillation damping control. Having used the same equipment, Khamesee et al. had manipulated the impressed voltages on the four electric magnetics by a PID controller by the use of the feedback signal of the hand's 3D position, the controlled variable. However, in this system, there were some problems remaining: in the horizontal direction, when translating the hand out of restricted region, positional control performance was suddenly degraded. The authors propose a method to apply an adaptive control to the horizontal directional control. It is expected that the technique to be presented in this paper contributes not only to the improvement of the response characteristic but also to widening the applicable range in the horizontal directional control.

  1. Adaptive multi-resolution 3D Hartree-Fock-Bogoliubov solver for nuclear structure

    Science.gov (United States)

    Pei, J. C.; Fann, G. I.; Harrison, R. J.; Nazarewicz, W.; Shi, Yue; Thornton, S.

    2014-08-01

    Background: Complex many-body systems, such as triaxial and reflection-asymmetric nuclei, weakly bound halo states, cluster configurations, nuclear fragments produced in heavy-ion fusion reactions, cold Fermi gases, and pasta phases in neutron star crust, are all characterized by large sizes and complex topologies in which many geometrical symmetries characteristic of ground-state configurations are broken. A tool of choice to study such complex forms of matter is an adaptive multi-resolution wavelet analysis. This method has generated much excitement since it provides a common framework linking many diversified methodologies across different fields, including signal processing, data compression, harmonic analysis and operator theory, fractals, and quantum field theory. Purpose: To describe complex superfluid many-fermion systems, we introduce an adaptive pseudospectral method for solving self-consistent equations of nuclear density functional theory in three dimensions, without symmetry restrictions. Methods: The numerical method is based on the multi-resolution and computational harmonic analysis techniques with a multi-wavelet basis. The application of state-of-the-art parallel programming techniques include sophisticated object-oriented templates which parse the high-level code into distributed parallel tasks with a multi-thread task queue scheduler for each multi-core node. The internode communications are asynchronous. The algorithm is variational and is capable of solving coupled complex-geometric systems of equations adaptively, with functional and boundary constraints, in a finite spatial domain of very large size, limited by existing parallel computer memory. For smooth functions, user-defined finite precision is guaranteed. Results: The new adaptive multi-resolution Hartree-Fock-Bogoliubov (HFB) solver madness-hfb is benchmarked against a two-dimensional coordinate-space solver hfb-ax that is based on the B-spline technique and a three-dimensional solver

  2. A low order flow/acoustics interaction method for the prediction of sound propagation using 3D adaptive hybrid grids

    International Nuclear Information System (INIS)

    A low-order flow/acoustics interaction method for the prediction of sound propagation and diffraction in unsteady subsonic compressible flow using adaptive 3-D hybrid grids is investigated. The total field is decomposed into the flow field described by the Euler equations, and the acoustics part described by the Nonlinear Perturbation Equations. The method is shown capable of predicting monopole sound propagation, while employment of acoustics-guided adapted grid refinement improves the accuracy of capturing the acoustic field. Interaction of sound with solid boundaries is also examined in terms of reflection, and diffraction. Sound propagation through an unsteady flow field is examined using static and dynamic flow/acoustics coupling demonstrating the importance of the latter.

  3. A low order flow/acoustics interaction method for the prediction of sound propagation using 3D adaptive hybrid grids

    Energy Technology Data Exchange (ETDEWEB)

    Kallinderis, Yannis, E-mail: kallind@otenet.gr [Dept. of Mechanical and Aeronautical Engineering, University of Patras, Rio Patras 26504 (Greece); Vitsas, Panagiotis A.; Menounou, Penelope [Dept. of Mechanical and Aeronautical Engineering, University of Patras, Rio Patras 26504 (Greece)

    2012-07-15

    A low-order flow/acoustics interaction method for the prediction of sound propagation and diffraction in unsteady subsonic compressible flow using adaptive 3-D hybrid grids is investigated. The total field is decomposed into the flow field described by the Euler equations, and the acoustics part described by the Nonlinear Perturbation Equations. The method is shown capable of predicting monopole sound propagation, while employment of acoustics-guided adapted grid refinement improves the accuracy of capturing the acoustic field. Interaction of sound with solid boundaries is also examined in terms of reflection, and diffraction. Sound propagation through an unsteady flow field is examined using static and dynamic flow/acoustics coupling demonstrating the importance of the latter.

  4. Quantitative Evaluation of Tissue Surface Adaption of CAD-Designed and 3D Printed Wax Pattern of Maxillary Complete Denture

    Directory of Open Access Journals (Sweden)

    Hu Chen

    2015-01-01

    Full Text Available Objective. To quantitatively evaluate the tissue surface adaption of a maxillary complete denture wax pattern produced by CAD and 3DP. Methods. A standard edentulous maxilla plaster cast model was used, for which a wax pattern of complete denture was designed using CAD software developed in our previous study and printed using a 3D wax printer, while another wax pattern was manufactured by the traditional manual method. The cast model and the two wax patterns were scanned in the 3D scanner as “DataModel,” “DataWaxRP,” and “DataWaxManual.” After setting each wax pattern on the plaster cast, the whole model was scanned for registration. After registration, the deviations of tissue surface between “DataModel” and “DataWaxRP” and between “DataModel” and “DataWaxManual” were measured. The data was analyzed by paired t-test. Results. For both wax patterns produced by the CAD&RP method and the manual method, scanning data of tissue surface and cast surface showed a good fit in the majority. No statistically significant (P>0.05 difference was observed between the CAD&RP method and the manual method. Conclusions. Wax pattern of maxillary complete denture produced by the CAD&3DP method is comparable with traditional manual method in the adaption to the edentulous cast model.

  5. 3D Multi-Object Segmentation of Cardiac MSCT Imaging by using a Multi-Agent Approach

    Science.gov (United States)

    Fleureau, Julien; Garreau, Mireille; Boulmier, Dominique; Hernandez, Alfredo

    2007-01-01

    We propose a new technique for general purpose, semi-interactive and multi-object segmentation in N-dimensional images, applied to the extraction of cardiac structures in MultiSlice Computed Tomography (MSCT) imaging. The proposed approach makes use of a multi-agent scheme combined with a supervised classification methodology allowing the introduction of a priori information and presenting fast computing times. The multi-agent system is organised around a communicating agent which manages a population of situated agents which segment the image through cooperative and competitive interactions. The proposed technique has been tested on several patient data sets. Some typical results are finally presented and discussed. PMID:18003382

  6. Hybrid Characteristics: 3D radiative transfer for parallel adaptive mesh refinement hydrodynamics

    CERN Document Server

    Rijkhorst, E J; Dubey, A; Mellema, G R; Rijkhorst, Erik-Jan; Plewa, Tomasz; Dubey, Anshu; Mellema, Garrelt

    2005-01-01

    We have developed a three-dimensional radiative transfer method designed specifically for use with parallel adaptive mesh refinement hydrodynamics codes. This new algorithm, which we call hybrid characteristics, introduces a novel form of ray tracing that can neither be classified as long, nor as short characteristics, but which applies the underlying principles, i.e. efficient execution through interpolation and parallelizability, of both. Primary applications of the hybrid characteristics method are radiation hydrodynamics problems that take into account the effects of photoionization and heating due to point sources of radiation. The method is implemented in the hydrodynamics package FLASH. The ionization, heating, and cooling processes are modelled using the DORIC ionization package. Upon comparison with the long characteristics method, we find that our method calculates the column density with a similarly high accuracy and produces sharp and well defined shadows. We show the quality of the new algorithm ...

  7. Graph-based Active Learning of Agglomeration (GALA: a Python library to segment 2D and 3D neuroimages

    Directory of Open Access Journals (Sweden)

    Juan eNunez-Iglesias

    2014-04-01

    Full Text Available 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 is to perform automatic segmentation of EM images, followed by manual proofreading by experts to fix errors. We 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 limitations of the gala library and how we intend to address them.

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

    Science.gov (United States)

    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

  9. Joint segmentation of lumen and outer wall from femoral artery MR images: Towards 3D imaging measurements of peripheral arterial disease.

    Science.gov (United States)

    Ukwatta, Eranga; Yuan, Jing; Qiu, Wu; Rajchl, Martin; Chiu, Bernard; Fenster, Aaron

    2015-12-01

    Three-dimensional (3D) measurements of peripheral arterial disease (PAD) plaque burden extracted from fast black-blood magnetic resonance (MR) images have shown to be more predictive of clinical outcomes than PAD stenosis measurements. To this end, accurate segmentation of the femoral artery lumen and outer wall is required for generating volumetric measurements of PAD plaque burden. Here, we propose a semi-automated algorithm to jointly segment the femoral artery lumen and outer wall surfaces from 3D black-blood MR images, which are reoriented and reconstructed along the medial axis of the femoral artery to obtain improved spatial coherence between slices of the long, thin femoral artery and to reduce computation time. The developed segmentation algorithm enforces two priors in a global optimization manner: the spatial consistency between the adjacent 2D slices and the anatomical region order between the femoral artery lumen and outer wall surfaces. The formulated combinatorial optimization problem for segmentation is solved globally and exactly by means of convex relaxation using a coupled continuous max-flow (CCMF) model, which is a dual formulation to the convex relaxed optimization problem. In addition, the CCMF model directly derives an efficient duality-based algorithm based on the modern multiplier augmented optimization scheme, which has been implemented on a GPU for fast computation. The computed segmentations from the developed algorithm were compared to manual delineations from experts using 20 black-blood MR images. The developed algorithm yielded both high accuracy (Dice similarity coefficients ≥ 87% for both the lumen and outer wall surfaces) and high reproducibility (intra-class correlation coefficient of 0.95 for generating vessel wall area), while outperforming the state-of-the-art method in terms of computational time by a factor of ≈ 20. PMID:26387053

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

    Science.gov (United States)

    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

  11. ELTs Adaptive Optics for Multi-Objects 3D Spectroscopy Key Parameters and Design Rules

    CERN Document Server

    Neichel, B; Fusco, T; Gendron, E; Puech, M; Rousset, G; Hammer, F

    2006-01-01

    In the last few years, new Adaptive Optics [AO] techniques have emerged to answer new astronomical challenges: Ground-Layer AO [GLAO] and Multi-Conjugate AO [MCAO] to access a wider Field of View [FoV], Multi-Object AO [MOAO] for the simultaneous observation of several faint galaxies, eXtreme AO [XAO] for the detection of faint companions. In this paper, we focus our study to one of these applications : high red-shift galaxy observations using MOAO techniques in the framework of Extremely Large Telescopes [ELTs]. We present the high-level specifications of a dedicated instrument. We choose to describe the scientific requirements with the following criteria : 40% of Ensquared Energy [EE] in H band (1.65um) and in an aperture size from 25 to 150 mas. Considering these specifications we investigate different AO solutions thanks to Fourier based simulations. Sky Coverage [SC] is computed for Natural and Laser Guide Stars [NGS, LGS] systems. We show that specifications are met for NGS-based systems at the cost of ...

  12. 3D Wavelet Sub-Bands Mixing for Image De-noising and Segmentation of Brain Images

    OpenAIRE

    Joyjit Patra; Himadri Nath Moulick; Shreyosree Mallick; Arun Kanti Manna

    2016-01-01

    A critical issue in image restoration is the problem of noise removal while keeping the integrity of relevant image information. The method proposed in this paper is a fully automatic 3D block wise version of the Non Local (NL) Means filter with wavelet sub-bands mixing. The proposed a wavelet sub-bands mixing is based on a multi-resolution approach for improving the quality of image de-noising filter. Quantitative validation was carried out on synthetic datasets generated with the Brain W...

  13. HIFI-C: a robust and fast method for determining NMR couplings from adaptive 3D to 2D projections

    International Nuclear Information System (INIS)

    We describe a novel method for the robust, rapid, and reliable determination of J couplings in multi-dimensional NMR coupling data, including small couplings from larger proteins. The method, 'High-resolution Iterative Frequency Identification of Couplings' (HIFI-C) is an extension of the adaptive and intelligent data collection approach introduced earlier in HIFI-NMR. HIFI-C collects one or more optimally tilted two-dimensional (2D) planes of a 3D experiment, identifies peaks, and determines couplings with high resolution and precision. The HIFI-C approach, demonstrated here for the 3D quantitative J method, offers vital features that advance the goal of rapid and robust collection of NMR coupling data. (1) Tilted plane residual dipolar couplings (RDC) data are collected adaptively in order to offer an intelligent trade off between data collection time and accuracy. (2) Data from independent planes can provide a statistical measure of reliability for each measured coupling. (3) Fast data collection enables measurements in cases where sample stability is a limiting factor (for example in the presence of an orienting medium required for residual dipolar coupling measurements). (4) For samples that are stable, or in experiments involving relatively stronger couplings, robust data collection enables more reliable determinations of couplings in shorter time, particularly for larger biomolecules. As a proof of principle, we have applied the HIFI-C approach to the 3D quantitative J experiment to determine N-C' RDC values for three proteins ranging from 56 to 159 residues (including a homodimer with 111 residues in each subunit). A number of factors influence the robustness and speed of data collection. These factors include the size of the protein, the experimental set up, and the coupling being measured, among others. To exhibit a lower bound on robustness and the potential for time saving, the measurement of dipolar couplings for the N-C' vector represents a realistic

  14. 3D segmentation and quantification of magnetic resonance data: application to the osteonecrosis of the femoral head

    Science.gov (United States)

    Klifa, Catherine S.; Lynch, John A.; Zaim, Souhil; Genant, Harry K.

    1999-05-01

    The general objective of our study is the development of a clinically robust three-dimensional segmentation and quantification technique of Magnetic Resonance (MR) data, for the objective and quantitative evaluation of the osteonecrosis (ON) of the femoral head. This method will help evaluate the effects of joint preserving treatments for femoral head osteonecrosis from MR data. The disease is characterized by tissue changes (death of bone and marrow cells) within the weight-bearing portion of the femoral head. Due to the fuzzy appearance of lesion tissues and their different intensity patterns in various MR sequences, we proposed a semi-automatic multispectral segmentation of MR data introducing data constraints (anatomical and geometrical) and using a classical K-means unsupervised clustering algorithm. The method was applied on ON patient data. Results of volumetric measurements and configuration of various tissues obtained with the semi- automatic method were compared with quantitative results delineated by a trained radiologist.

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

    OpenAIRE

    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...

  16. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

    International Nuclear Information System (INIS)

    Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to

  17. Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

    Energy Technology Data Exchange (ETDEWEB)

    Park, Sang Hyun [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong, E-mail: yzgao@cs.unc.edu [Department of Computer Science, Department of Radiology, and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Shi, Yinghuan, E-mail: syh@nju.edu.cn [State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)

    2014-11-01

    Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correct the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to

  18. Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma

    Energy Technology Data Exchange (ETDEWEB)

    Ciller, Carlos, E-mail: carlos.cillerruiz@unil.ch [Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne (Switzerland); Ophthalmic Technology Group, ARTORG Center of the University of Bern, Bern (Switzerland); Centre d’Imagerie BioMédicale, University of Lausanne, Lausanne (Switzerland); De Zanet, Sandro I.; Rüegsegger, Michael B. [Ophthalmic Technology Group, ARTORG Center of the University of Bern, Bern (Switzerland); Department of Ophthalmology, Inselspital, Bern University Hospital, Bern (Switzerland); Pica, Alessia [Department of Radiation Oncology, Inselspital, Bern University Hospital, Bern (Switzerland); Sznitman, Raphael [Ophthalmic Technology Group, ARTORG Center of the University of Bern, Bern (Switzerland); Department of Ophthalmology, Inselspital, Bern University Hospital, Bern (Switzerland); Thiran, Jean-Philippe [Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne (Switzerland); Signal Processing Laboratory, École Polytechnique Fédérale de Lausanne, Lausanne (Switzerland); Maeder, Philippe [Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne (Switzerland); Munier, Francis L. [Unit of Pediatric Ocular Oncology, Jules Gonin Eye Hospital, Lausanne (Switzerland); Kowal, Jens H. [Ophthalmic Technology Group, ARTORG Center of the University of Bern, Bern (Switzerland); Department of Ophthalmology, Inselspital, Bern University Hospital, Bern (Switzerland); and others

    2015-07-15

    Purpose: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. Methods and Materials: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. Results: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. Conclusion: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

  19. Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma

    International Nuclear Information System (INIS)

    Purpose: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. Methods and Materials: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. Results: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. Conclusion: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor

  20. 手腕骨三维图像分割方法%A 3D Segmentation Technique for Carpal Bone Images

    Institute of Scientific and Technical Information of China (English)

    李晶; 赵海燕

    2013-01-01

    Targeted at kinematic analysis of the carpal bones and design of fracture fixation for corresponding surgeries, this paper proposes a 3D (Three-Dimensional) technique for segmentation of the carpal bone images on the basis of the spatial position, which contributes to independent investigation of each segmented carpal bone on kinematic features and load-carrying capabilities under different circumstances. As a new segmentation technique in diagnosis and treatment of carpal bone diseases, it can divide the carpal bone images into eight segments that are available separately for review, conifguration, analysis and measurement.%为了对手腕骨进行运动学分析并对骨折手术固定辅助设计,本文提出一种对手腕骨的三维分割方法,即采用基于空间位置的方法将手腕骨独立分开,以便独立研究各部分在不同情况下的运动与受力。该方法将手腕8块腕骨分割开来,并能独立显示控制测量。为手腕骨疾病的诊断治疗提供,新的技术方法。

  1. Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation

    Directory of Open Access Journals (Sweden)

    Richard eBeare

    2016-03-01

    Full Text Available Measuring the distribution of brain tissue types (tissue classification in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation, which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF, hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T2-weighted images of preterm infants (born ≤30 weeks’ gestation acquired at 30 weeks’ corrected gestational age (n= 5, coronal T2-weighted images of preterm infants acquired at 40 weeks’ corrected gestational age (n= 5 and axial T2-weighted images of preterm infants acquired at 40 weeks’ corrected gestational age (n= 5. The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR group, consisted of T2-weighted images of preterm infants (born <30 weeks’ gestation acquired shortly after birth (n= 12, preterm infants acquired at term-equivalent age (n= 12, and healthy term-born infants (born ≥38 weeks’ gestation acquired within the first nine days of life (n= 12. For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for

  2. Automating measurement of subtle changes in articular cartilage from MRI of the knee by combining 3D image registration and segmentation

    Science.gov (United States)

    Lynch, John A.; Zaim, Souhil; Zhao, Jenny; Peterfy, Charles G.; Genant, Harry K.

    2001-07-01

    In osteoarthritis, articular cartilage loses integrity and becomes thinned. This usually occurs at sites which bear weight during normal use. Measurement of such loss from MRI scans, requires precise and reproducible techniques, which can overcome the difficulties of patient repositioning within the scanner. In this study, we combine a previously described technique for segmentation of cartilage from MRI of the knee, with a technique for 3D image registration that matches localized regions of interest at followup and baseline. Two patients, who had recently undergone meniscal surgery, and developed lesions during the 12 month followup period were examined. Image registration matched regions of interest (ROI) between baseline and followup, and changes within the cartilage lesions were estimate to be about a 16% reduction in cartilage volume within each ROI. This was more than 5 times the reproducibility of the measurement, but only represented a change of between 1 and 2% in total femoral cartilage volume. Changes in total cartilage volume may be insensitive for quantifying changes in cartilage morphology. A combined used of automated image segmentation, with 3D image registration could be a useful tool for the precise and sensitive measurement of localized changes in cartilage from MRI of the knee.

  3. 三维脑血管图像分割%Segmentation of 3D image of cerebral vessel

    Institute of Scientific and Technical Information of China (English)

    窦菲菲; 王成

    2009-01-01

    在外科手术和放射治疗中,对于脑血管的量化和可视化的要求越来越高,因此对于脑血管的自动(或半自动)的准确提取就显得尤为重要.对于近年来应用于脑血管分割的统计学分割法、形变模型法、多尺度法、基于先验知识法等分割方法进行了综述,将现有的脑血管分割技术分成如下3类:基于像素灰度的分割技术,基于血管管状结构的分割技术和基于先验知识的分割技术.%During surgery and radiation therapy,demands for higher quality of quantification and visualization of cerebral vessels need to be met.Hence,automatic (or semi-automatic) extractions of accurate cerebral vessel information seem particularly important.This paper reviews the cerebral vessel segmentation methods used in recent years,including statistics-based segmentation,deformable model,multi-scale method,prior knowledgebased method,and so on.The methods are divided into the following three categories:voxel intensity based approach,vascular tubular structure based approach,and prior knowledge-based approach.

  4. Generalization of Hindi OCR Using Adaptive Segmentation and Font Files

    Science.gov (United States)

    Agrawal, Mudit; Ma, Huanfeng; Doermann, David

    In this chapter, we describe an adaptive Indic OCR system implemented as part of a rapidly retargetable language tool effort and extend work found in [20, 2]. The system includes script identification, character segmentation, training sample creation, and character recognition. For script identification, Hindi words are identified in bilingual or multilingual document images using features of the Devanagari script and support vector machine (SVM). Identified words are then segmented into individual characters, using a font-model-based intelligent character segmentation and recognition system. Using characteristics of structurally similar TrueType fonts, our system automatically builds a model to be used for the segmentation and recognition of the new script, independent of glyph composition. The key is a reliance on known font attributes. In our recognition system three feature extraction methods are used to demonstrate the importance of appropriate features for classification. The methods are tested on both Latin and non-Latin scripts. Results show that the character-level recognition accuracy exceeds 92% for non-Latin and 96% for Latin text on degraded documents. This work is a step toward the recognition of scripts of low-density languages which typically do not warrant the development of commercial OCR, yet often have complete TrueType font descriptions.

  5. Segmentation of branching vascular structures using adaptive subdivision surface fitting

    Science.gov (United States)

    Kitslaar, Pieter H.; van't Klooster, Ronald; Staring, Marius; Lelieveldt, Boudewijn P. F.; van der Geest, Rob J.

    2015-03-01

    This paper describes a novel method for segmentation and modeling of branching vessel structures in medical images using adaptive subdivision surfaces fitting. The method starts with a rough initial skeleton model of the vessel structure. A coarse triangular control mesh consisting of hexagonal rings and dedicated bifurcation elements is constructed from this skeleton. Special attention is paid to ensure a topological sound control mesh is created around the bifurcation areas. Then, a smooth tubular surface is obtained from this coarse mesh using a standard subdivision scheme. This subdivision surface is iteratively fitted to the image. During the fitting, the target update locations of the subdivision surface are obtained using a scanline search along the surface normals, finding the maximum gradient magnitude (of the imaging data). In addition to this surface fitting framework, we propose an adaptive mesh refinement scheme. In this step the coarse control mesh topology is updated based on the current segmentation result, enabling adaptation to varying vessel lumen diameters. This enhances the robustness and flexibility of the method and reduces the amount of prior knowledge needed to create the initial skeletal model. The method was applied to publicly available CTA data from the Carotid Bifurcation Algorithm Evaluation Framework resulting in an average dice index of 89.2% with the ground truth. Application of the method to the complex vascular structure of a coronary artery tree in CTA and to MRI images were performed to show the versatility and flexibility of the proposed framework.

  6. Evaluation of a prototype 3D ultrasound system for multimodality imaging of cervical nodes for adaptive radiation therapy

    Science.gov (United States)

    Fraser, Danielle; Fava, Palma; Cury, Fabio; Vuong, Te; Falco, Tony; Verhaegen, Frank

    2007-03-01

    Sonography has good topographic accuracy for superficial lymph node assessment in patients with head and neck cancers. It is therefore an ideal non-invasive tool for precise inter-fraction volumetric analysis of enlarged cervical nodes. In addition, when registered with computed tomography (CT) images, ultrasound information may improve target volume delineation and facilitate image-guided adaptive radiation therapy. A feasibility study was developed to evaluate the use of a prototype ultrasound system capable of three dimensional visualization and multi-modality image fusion for cervical node geometry. A ceiling-mounted optical tracking camera recorded the position and orientation of a transducer in order to synchronize the transducer's position with respect to the room's coordinate system. Tracking systems were installed in both the CT-simulator and radiation therapy treatment rooms. Serial images were collected at the time of treatment planning and at subsequent treatment fractions. Volume reconstruction was performed by generating surfaces around contours. The quality of the spatial reconstruction and semi-automatic segmentation was highly dependent on the system's ability to track the transducer throughout each scan procedure. The ultrasound information provided enhanced soft tissue contrast and facilitated node delineation. Manual segmentation was the preferred method to contour structures due to their sonographic topography.

  7. Rate Adaptive Selective Segment Assignment for Reliable Wireless Video Transmission

    Directory of Open Access Journals (Sweden)

    Sajid Nazir

    2012-01-01

    Full Text Available A reliable video communication system is proposed based on data partitioning feature of H.264/AVC, used to create a layered stream, and LT codes for erasure protection. The proposed scheme termed rate adaptive selective segment assignment (RASSA is an adaptive low-complexity solution to varying channel conditions. The comparison of the results of the proposed scheme is also provided for slice-partitioned H.264/AVC data. Simulation results show competitiveness of the proposed scheme compared to optimized unequal and equal error protection solutions. The simulation results also demonstrate that a high visual quality video transmission can be maintained despite the adverse effect of varying channel conditions and the number of decoding failures can be reduced.

  8. A fully automatic, threshold-based segmentation method for the estimation of the Metabolic Tumor Volume from PET images: validation on 3D printed anthropomorphic oncological lesions

    Science.gov (United States)

    Gallivanone, F.; Interlenghi, M.; Canervari, C.; Castiglioni, I.

    2016-01-01

    18F-Fluorodeoxyglucose (18F-FDG) Positron Emission Tomography (PET) is a standard functional diagnostic technique to in vivo image cancer. Different quantitative paramters can be extracted from PET images and used as in vivo cancer biomarkers. Between PET biomarkers Metabolic Tumor Volume (MTV) has gained an important role in particular considering the development of patient-personalized radiotherapy treatment for non-homogeneous dose delivery. Different imaging processing methods have been developed to define MTV. The different proposed PET segmentation strategies were validated in ideal condition (e.g. in spherical objects with uniform radioactivity concentration), while the majority of cancer lesions doesn't fulfill these requirements. In this context, this work has a twofold objective: 1) to implement and optimize a fully automatic, threshold-based segmentation method for the estimation of MTV, feasible in clinical practice 2) to develop a strategy to obtain anthropomorphic phantoms, including non-spherical and non-uniform objects, miming realistic oncological patient conditions. The developed PET segmentation algorithm combines an automatic threshold-based algorithm for the definition of MTV and a k-means clustering algorithm for the estimation of the background. The method is based on parameters always available in clinical studies and was calibrated using NEMA IQ Phantom. Validation of the method was performed both in ideal (e.g. in spherical objects with uniform radioactivity concentration) and non-ideal (e.g. in non-spherical objects with a non-uniform radioactivity concentration) conditions. The strategy to obtain a phantom with synthetic realistic lesions (e.g. with irregular shape and a non-homogeneous uptake) consisted into the combined use of standard anthropomorphic phantoms commercially and irregular molds generated using 3D printer technology and filled with a radioactive chromatic alginate. The proposed segmentation algorithm was feasible in a

  9. Comparison of 3D Adaptive Remeshing Strategies for Finite Element Simulations of Electromagnetic Heating of Gold Nanoparticles

    Directory of Open Access Journals (Sweden)

    Fadhil Mezghani

    2015-01-01

    Full Text Available The optical properties of metallic nanoparticles are well known, but the study of their thermal behavior is in its infancy. However the local heating of surrounding medium, induced by illuminated nanostructures, opens the way to new sensors and devices. Consequently the accurate calculation of the electromagnetically induced heating of nanostructures is of interest. The proposed multiphysics problem cannot be directly solved with the classical refinement method of Comsol Multiphysics and a 3D adaptive remeshing process based on an a posteriori error estimator is used. In this paper the efficiency of three remeshing strategies for solving the multiphysics problem is compared. The first strategy uses independent remeshing for each physical quantity to reach a given accuracy. The second strategy only controls the accuracy on temperature. The third strategy uses a linear combination of the two normalized targets (the electric field intensity and the temperature. The analysis of the performance of each strategy is based on the convergence of the remeshing process in terms of number of elements. The efficiency of each strategy is also characterized by the number of computation iterations, the number of elements, the CPU time, and the RAM required to achieve a given target accuracy.

  10. Adaptive segmentation of wavelet transform coefficients for video compression

    Science.gov (United States)

    Wasilewski, Piotr

    2000-04-01

    This paper presents video compression algorithm suitable for inexpensive real-time hardware implementation. This algorithm utilizes Discrete Wavelet Transform (DWT) with the new Adaptive Spatial Segmentation Algorithm (ASSA). The algorithm was designed to obtain better or similar decompressed video quality in compare to H.263 recommendation and MPEG standard using lower computational effort, especially at high compression rates. The algorithm was optimized for hardware implementation in low-cost Field Programmable Gate Array (FPGA) devices. The luminance and chrominance components of every frame are encoded with 3-level Wavelet Transform with biorthogonal filters bank. The low frequency subimage is encoded with an ADPCM algorithm. For the high frequency subimages the new Adaptive Spatial Segmentation Algorithm is applied. It divides images into rectangular blocks that may overlap each other. The width and height of the blocks are set independently. There are two kinds of blocks: Low Variance Blocks (LVB) and High Variance Blocks (HVB). The positions of the blocks and the values of the WT coefficients belonging to the HVB are encoded with the modified zero-tree algorithms. LVB are encoded with the mean value. Obtained results show that presented algorithm gives similar or better quality of decompressed images in compare to H.263, even up to 5 dB in PSNR measure.

  11. Sensitivity and reproducibility of a new fast 3D segmentation technique for clinical MR-based brain volumetry in multiple sclerosis

    Energy Technology Data Exchange (ETDEWEB)

    Lukas, Carsten; Bellenberg, Barbara; Schimrigk, Sebastian K.; Przuntek, Horst [Ruhr University, Department of Neurology, St. Josef Hospital, Bochum (Germany); Hahn, Horst K.; Rexilius, Jan; Peitgen, Heinz-Otto [MeVis, Center for Medical Diagnostic Systems and Visualization, Bremen (Germany); Schmid, Gebhard; Koester, Odo [Ruhr University, Department of Radiology and Nuclear Medicine, St. Josef Hospital, Bochum (Germany)

    2004-11-01

    Fast, reliable and easy-to-use methods to quantify brain atrophy are of increasing importance in clinical studies on neuro-degenerative diseases. Here, ILAB 4, a new volumetry software that uses a fast semi-automated 3D segmentation of thin-slice T1-weighted 3D MR images based on a modified watershed transform and an automatic histogram analysis was evaluated. It provides the cerebral volumes: whole brain, white matter, gray matter and intracranial cavity. Inter- and intra-rater reliability and scan-rescan reproducibility were excellent in measuring whole brain volumes (coefficients of variation below 0.5%) of volunteers and patients. However, gray and white matter volumes were more susceptible to image quality. High accuracy of the absolute volume results ({+-}5 ml) were shown by phantom and preparation measurements. Analysis times were 6 min for processing of 128 slices. The proposed technique is reliable and highly suitable for quantitative studies of brain atrophy, e.g., in multiple sclerosis. (orig.)

  12. Sensitivity and reproducibility of a new fast 3D segmentation technique for clinical MR-based brain volumetry in multiple sclerosis.

    Science.gov (United States)

    Lukas, Carsten; Hahn, Horst K; Bellenberg, Barbara; Rexilius, Jan; Schmid, Gebhard; Schimrigk, Sebastian K; Przuntek, Horst; Köster, Odo; Peitgen, Heinz-Otto

    2004-11-01

    Fast, reliable and easy-to-use methods to quantify brain atrophy are of increasing importance in clinical studies on neuro-degenerative diseases. Here, ILAB 4, a new volumetry software that uses a fast semi-automated 3D segmentation of thin-slice T1-weighted 3D MR images based on a modified watershed transform and an automatic histogram analysis was evaluated. It provides the cerebral volumes: whole brain, white matter, gray matter and intracranial cavity. Inter- and intra-rater reliability and scan-rescan reproducibility were excellent in measuring whole brain volumes (coefficients of variation below 0.5%) of volunteers and patients. However, gray and white matter volumes were more susceptible to image quality. High accuracy of the absolute volume results (+/-5 ml) were shown by phantom and preparation measurements. Analysis times were 6 min for processing of 128 slices. The proposed technique is reliable and highly suitable for quantitative studies of brain atrophy, e.g., in multiple sclerosis. PMID:15536555

  13. Automatic speech signal segmentation based on the innovation adaptive filter

    Directory of Open Access Journals (Sweden)

    Makowski Ryszard

    2014-06-01

    Full Text Available Speech segmentation is an essential stage in designing automatic speech recognition systems and one can find several algorithms proposed in the literature. It is a difficult problem, as speech is immensely variable. The aim of the authors’ studies was to design an algorithm that could be employed at the stage of automatic speech recognition. This would make it possible to avoid some problems related to speech signal parametrization. Posing the problem in such a way requires the algorithm to be capable of working in real time. The only such algorithm was proposed by Tyagi et al., (2006, and it is a modified version of Brandt’s algorithm. The article presents a new algorithm for unsupervised automatic speech signal segmentation. It performs segmentation without access to information about the phonetic content of the utterances, relying exclusively on second-order statistics of a speech signal. The starting point for the proposed method is time-varying Schur coefficients of an innovation adaptive filter. The Schur algorithm is known to be fast, precise, stable and capable of rapidly tracking changes in second order signal statistics. A transfer from one phoneme to another in the speech signal always indicates a change in signal statistics caused by vocal track changes. In order to allow for the properties of human hearing, detection of inter-phoneme boundaries is performed based on statistics defined on the mel spectrum determined from the reflection coefficients. The paper presents the structure of the algorithm, defines its properties, lists parameter values, describes detection efficiency results, and compares them with those for another algorithm. The obtained segmentation results, are satisfactory.

  14. 机载激光扫描数据分割的三维数学形态学模型%Airborne LIDAR data segmentation based on 3D mathematical morphology

    Institute of Scientific and Technical Information of China (English)

    吴杭彬; 李楠; 刘春; 施蓓琦; 杨璇

    2011-01-01

    机载激光扫描点云的三维数字图像表达模型将二维形态学运算推广至三维,给出基于三维数字图像的膨胀和腐蚀运算方法.针对点云三维数字图像,提出基于三维数学形态学和聚类分析的分割方法.将点云三维数字图像进行膨胀和聚类分析,依据聚类结果得到点云的分割结果.讨论了本方法两个参数与点云分辨率、地物间隔之间的关系.选用两套实例数据进行实验,并将第一套数据计算结果与Mean Shift算法、渐进三角网加密算法进行比较,从分割评价因子、精度、计算效率等方面分析本文方法与其他两种方法的优劣,最后分析了本文方法的稳定性.%A 3D digital image model is proposed to represent the LIDAR data. The mathematical morphology is extended to 3D and then, dilation and erosion operators are re-defined. A method combining 3D mathematical morphology with clustering analysis is developed . Sequential dilation operations and clustering analysis are introduced into the 3D point cloud to achieve the pixel-level results of point cloud. The relationships between the two parameters and data property, resolution of point cloud and the minimum distance between objects, is discussed. Two case data are used to demonstrate the feasibility of the proposed method. The result for the first dataset is compared with those from the two other methods, Mean Shift algorithm and adaptive TIN filter method. The advantages and disadvantages are summarized using segmentation evaluation factors, segmentation accuracy, and computation efficiency. Meanwhile the stabilization of proposed method is also analyzed.

  15. Integration of 3D scale-based pseudo-enhancement correction and partial volume image segmentation for improving electronic colon cleansing in CT colonograpy.

    Science.gov (United States)

    Zhang, Hao; Li, Lihong; Zhu, Hongbin; Han, Hao; Song, Bowen; Liang, Zhengrong

    2014-01-01

    Orally administered tagging agents are usually used in CT colonography (CTC) to differentiate residual bowel content from native colonic structures. However, the high-density contrast agents tend to introduce pseudo-enhancement (PE) effect on neighboring soft tissues and elevate their observed CT attenuation value toward that of the tagged materials (TMs), which may result in an excessive electronic colon cleansing (ECC) since the pseudo-enhanced soft tissues are incorrectly identified as TMs. To address this issue, we integrated a 3D scale-based PE correction into our previous ECC pipeline based on the maximum a posteriori expectation-maximization partial volume (PV) segmentation. The newly proposed ECC scheme takes into account both the PE and PV effects that commonly appear in CTC images. We evaluated the new scheme on 40 patient CTC scans, both qualitatively through display of segmentation results, and quantitatively through radiologists' blind scoring (human observer) and computer-aided detection (CAD) of colon polyps (computer observer). Performance of the presented algorithm has shown consistent improvements over our previous ECC pipeline, especially for the detection of small polyps submerged in the contrast agents. The CAD results of polyp detection showed that 4 more submerged polyps were detected for our new ECC scheme over the previous one.

  16. Atlas Based Automatic Liver 3D CT Image Segmentation%基于图谱的肝脏CT三维自动分割研究

    Institute of Scientific and Technical Information of China (English)

    刘伟; 贾富仓; 胡庆茂; 王俊

    2011-01-01

    目的 在肝脏外科手术或肝脏病理研究中,计算肝脏体积是重要步骤.由于肝脏外形复杂、临近组织灰度值与之接近等特点,肝脏的自动医学图像分割仍是医学图像处理中的难点之一.方法 本文采用图谱结合3D非刚性配准的方法,同时加入肝脏区域搜索算法,实现了鲁棒性较高的肝脏自动分割程序.首先,利用20套训练图像创建图谱,然后程序自动搜索肝脏区域,最后将图谱与待分割CT图像依次进行仿射配准和B样条配准.配准以后的图谱肝脏轮廓即可表示为目标肝脏分割轮廓,进而计算出肝脏体积.结果 评估结果显示,上述方法在肝脏体积误差方面表现出色,达到77分,但在局部(主要在肝脏尖端)出现较大的误差.结论 该方法分割临床肝脏CT图像具有可行性.%Objective Liver segmentation is an important step for the planning and navigation in liver surgery. Accurate, fast and robust automatic segmentation methods for clinical routine data are urgently needed. Because of the liver- s characteristics, such as the complexity of the external form, the similarity between the intensities of the liver and the tissues around it, automatic segmentation of the liver is one of the difficulties in medical image processing. Methods In this paper, 3D non-rigid registration from a refined atlas to liver CT images is used for segmentation. Firstly, twenty sets of training images are utilized to create an atlas. Then the liver initial region is searched and located automatically. After that threshold filtering is used to enhance the robustness of segmentation. Finally, this atlas is non-rigidly registered to the liver in CT images with affine and B-spline in succession. The registered segmentation of liver- s atlas represented the segmentation of the target liver, and then the liver volume was calculated. Results The evaluation show that the proposed method works well in liver volume error, with the 77 score

  17. Real-Time Adaptive Foreground/Background Segmentation

    Science.gov (United States)

    Butler, Darren E.; Bove, V. Michael; Sridharan, Sridha

    2005-12-01

    The automatic analysis of digital video scenes often requires the segmentation of moving objects from a static background. Historically, algorithms developed for this purpose have been restricted to small frame sizes, low frame rates, or offline processing. The simplest approach involves subtracting the current frame from the known background. However, as the background is rarely known beforehand, the key is how to learn and model it. This paper proposes a new algorithm that represents each pixel in the frame by a group of clusters. The clusters are sorted in order of the likelihood that they model the background and are adapted to deal with background and lighting variations. Incoming pixels are matched against the corresponding cluster group and are classified according to whether the matching cluster is considered part of the background. The algorithm has been qualitatively and quantitatively evaluated against three other well-known techniques. It demonstrated equal or better segmentation and proved capable of processing [InlineEquation not available: see fulltext.] PAL video at full frame rate using only 35%-40% of a [InlineEquation not available: see fulltext.] GHz Pentium 4 computer.

  18. Cerebral Arteries Extraction using Level Set Segmentation and Adaptive Tracing for CT Angiography

    International Nuclear Information System (INIS)

    We propose an approach for extracting cerebral arteries from partial Computed Tomography Angiography (CTA). The challenges of extracting cerebral arteries from CTA come from the fact that arteries are usually surrounded by bones and veins in the lower portion of a CTA volume. There exists strong intensity-value overlap between vessels and surrounding objects. Besides, it is inappropriate to assume the 2D cross sections of arteries are circle or ellipse, especially for abnormal vessels. The navigation of the arteries could change suddenly in the 3D space. In this paper, a method based on level set segmentation is proposed to target this challenging problem. For the lower portion of a CTA volume, we use geodesic active contour method to detect cross section of arteries in the 2D space. The medial axis of the artery is obtained by adaptively tracking along its navigation path. This is done by finding the minimal cross section from cutting the arteries under different angles in the 3D spherical space. This method is highly automated, with minimum user input of providing only the starting point and initial navigation direction of the arteries of interests

  19. Evaluation of left atrial function by multidetector computed tomography before left atrial radiofrequency-catheter ablation: Comparison of a manual and automated 3D volume segmentation method

    Energy Technology Data Exchange (ETDEWEB)

    Wolf, Florian, E-mail: florian.wolf@meduniwien.ac.a [Department of Radiology, Medical University of Vienna, Vienna (Austria); Ourednicek, Petr [Philips Medical Systems, Prague (Czech Republic); Loewe, Christian [Department of Radiology, Medical University of Vienna, Vienna (Austria); Richter, Bernhard; Goessinger, Heinz David; Gwechenberger, Marianne [Department of Cardiology, Medical University of Vienna, Vienna (Austria); Plank, Christina; Schernthaner, Ruediger Egbert; Toepker, Michael; Lammer, Johannes [Department of Radiology, Medical University of Vienna, Vienna (Austria); Feuchtner, Gudrun M. [Department of Radiology, Innsbruck Medical University, Innsbruck (Austria); Institute of Diagnostic Radiology, University Hospital Zurich (Switzerland)

    2010-08-15

    Introduction: The purpose of this study was to compare a manual and automated 3D volume segmentation tool for evaluation of left atrial (LA) function by 64-slice multidetector-CT (MDCT). Methods and materials: In 33 patients with paroxysmal atrial fibrillation a MDCT scan was performed before radiofrequency-catheter ablation. Atrial function (minimal volume (LAmin), maximal volume (LAmax), stroke volume (SV), ejection fraction (EF)) was evaluated by two readers using a manual and an automatic tool and measurement time was evaluated. Results: Automated LA volume segmentation failed in one patient due to low LA enhancement (103HU). Mean LAmax, LAmin, SV and EF were 127.7 ml, 93 ml, 34.7 ml, 27.1% by the automated, and 122.7 ml, 89.9 ml, 32.8 ml, 26.3% by the manual method with no significant difference (p > 0.05) and high Pearsons correlation coefficients (r = 0.94, r = 0.94, r = 0.82 and r = 0.85, p < 0.0001), respectively. The automated method was significantly faster (p < 0.001). Interobserver variability was low for both methods with Pearson's correlation coefficients between 0.98 and 0.99 (p < 0.0001). Conclusions: Evaluation of LA volume and function with 64-slice MDCT is feasible with a very low interobserver variability. The automatic method is as accurate as the manual method but significantly less time consuming permitting a routine use in clinical practice before RF-catheter ablation.

  20. Optimized adaptation algorithm for HEVC/H.265 dynamic adaptive streaming over HTTP using variable segment duration

    Science.gov (United States)

    Irondi, Iheanyi; Wang, Qi; Grecos, Christos

    2016-04-01

    Adaptive video streaming using HTTP has become popular in recent years for commercial video delivery. The recent MPEG-DASH standard allows interoperability and adaptability between servers and clients from different vendors. The delivery of the MPD (Media Presentation Description) files in DASH and the DASH client behaviours are beyond the scope of the DASH standard. However, the different adaptation algorithms employed by the clients do affect the overall performance of the system and users' QoE (Quality of Experience), hence the need for research in this field. Moreover, standard DASH delivery is based on fixed segments of the video. However, there is no standard segment duration for DASH where various fixed segment durations have been employed by different commercial solutions and researchers with their own individual merits. Most recently, the use of variable segment duration in DASH has emerged but only a few preliminary studies without practical implementation exist. In addition, such a technique requires a DASH client to be aware of segment duration variations, and this requirement and the corresponding implications on the DASH system design have not been investigated. This paper proposes a segment-duration-aware bandwidth estimation and next-segment selection adaptation strategy for DASH. Firstly, an MPD file extension scheme to support variable segment duration is proposed and implemented in a realistic hardware testbed. The scheme is tested on a DASH client, and the tests and analysis have led to an insight on the time to download next segment and the buffer behaviour when fetching and switching between segments of different playback durations. Issues like sustained buffering when switching between segments of different durations and slow response to changing network conditions are highlighted and investigated. An enhanced adaptation algorithm is then proposed to accurately estimate the bandwidth and precisely determine the time to download the next

  1. Adaptive Image Restoration and Segmentation Method Using Different Neighborhood Sizes

    Directory of Open Access Journals (Sweden)

    Chengcheng Li

    2003-04-01

    Full Text Available The image restoration methods based on the Bayesian's framework and Markov random fields (MRF have been widely used in the image-processing field. The basic idea of all these methods is to use calculus of variation and mathematical statistics to average or estimate a pixel value by the values of its neighbors. After applying this averaging process to the whole image a number of times, the noisy pixels, which are abnormal values, are filtered out. Based on the Tea-trade model, which states that the closer the neighbor, more contribution it makes, almost all of these methods use only the nearest four neighbors for calculation. In our previous research [1, 2], we extended the research on CLRS (image restoration and segmentation by using competitive learning algorithm to enlarge the neighborhood size. The results showed that the longer neighborhood range could improve or worsen the restoration results. We also found that the autocorrelation coefficient was an important factor to determine the proper neighborhood size. We then further realized that the computational complexity increased dramatically along with the enlargement of the neighborhood size. This paper is to further the previous research and to discuss the tradeoff between the computational complexity and the restoration improvement by using longer neighborhood range. We used a couple of methods to construct the synthetic images with the exact correlation coefficients we want and to determine the corresponding neighborhood size. We constructed an image with a range of correlation coefficients by blending some synthetic images. Then an adaptive method to find the correlation coefficients of this image was constructed. We restored the image by applying different neighborhood CLRS algorithm to different parts of the image according to its correlation coefficient. Finally, we applied this adaptive method to some real-world images to get improved restoration results than by using single

  2. Energy-consistent small-core pseudopotentials for 3d-transition metals adapted to quantum Monte Carlo calculations

    NARCIS (Netherlands)

    Burkatzki, M.; Filippi, Claudia; Dolg, M.

    2008-01-01

    We extend our recently published set of energy-consistent scalar-relativistic Hartree–Fock pseudopotentials by the 3d-transition metal elements, scandium through zinc. The pseudopotentials do not exhibit a singularity at the nucleus and are therefore suitable for quantum Monte Carlo (QMC) calculatio

  3. Alternative Fuzzy Cluster Segmentation of Remote Sensing Images Based on Adaptive Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Jing; TANG Jilong; LIU Jibin; REN Chunying; LIU Xiangnan; FENG Jiang

    2009-01-01

    Remote sensing image segmentation is the basis of image understanding and analysis. However, the precision and the speed of segmentation can not meet the need of image analysis, due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm (AGA) and Alternative Fuzzy C-Means (AFCM). Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased, and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means (FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM.

  4. An adaptive grid method for computing the high speed 3D viscous flow about a re-entry vehicle

    Science.gov (United States)

    Bockelie, Michael J.; Smith, Robert E.

    1992-01-01

    An algebraic solution adaptive grid generation method that allows adapting the grid in all three coordinate directions is presented. Techniques are described that maintain the integrity of the original vehicle definition for grid point movement on the vehicle surface and that avoid grid cross over in the boundary layer portion of the grid lying next to the vehicle surface. The adaptive method is tested by computing the Mach 6 hypersonic three dimensional viscous flow about a proposed Martian entry vehicle.

  5. Length-adaptive graph search for automatic segmentation of pathological features in optical coherence tomography images

    Science.gov (United States)

    Keller, Brenton; Cunefare, David; Grewal, Dilraj S.; Mahmoud, Tamer H.; Izatt, Joseph A.; Farsiu, Sina

    2016-07-01

    We introduce a metric in graph search and demonstrate its application for segmenting retinal optical coherence tomography (OCT) images of macular pathology. Our proposed "adjusted mean arc length" (AMAL) metric is an adaptation of the lowest mean arc length search technique for automated OCT segmentation. We compare this method to Dijkstra's shortest path algorithm, which we utilized previously in our popular graph theory and dynamic programming segmentation technique. As an illustrative example, we show that AMAL-based length-adaptive segmentation outperforms the shortest path in delineating the retina/vitreous boundary of patients with full-thickness macular holes when compared with expert manual grading.

  6. Adaptive automatic segmentation of Leishmaniasis parasite in Indirect Immunofluorescence images.

    Science.gov (United States)

    Ouertani, F; Amiri, H; Bettaib, J; Yazidi, R; Ben Salah, A

    2014-01-01

    This paper describes the first steps for the automation of the serum titration process. In fact, this process requires an Indirect Immunofluorescence (IIF) diagnosis automation. We deal with the initial phase that represents the fluorescence images segmentation. Our approach consists of three principle stages: (1) a color based segmentation which aims at extracting the fluorescent foreground based on k-means clustering, (2) the segmentation of the fluorescent clustered image, and (3) a region-based feature segmentation, intended to remove the fluorescent noisy regions and to locate fluorescent parasites. We evaluated the proposed method on 40 IIF images. Experimental results show that such a method provides reliable and robust automatic segmentation of fluorescent Promastigote parasite. PMID:25571049

  7. 3D Image Modelling and Specific Treatments in Orthodontics Domain

    Directory of Open Access Journals (Sweden)

    Dionysis Goularas

    2007-01-01

    Full Text Available In this article, we present a 3D specific dental plaster treatment system for orthodontics. From computer tomography scanner images, we propose first a 3D image modelling and reconstruction method of the Mandible and Maxillary based on an adaptive triangulation allowing management of contours meant for the complex topologies. Secondly, we present two specific treatment methods directly achieved on obtained 3D model allowing the automatic correction for the setting in occlusion of the Mandible and the Maxillary, and the teeth segmentation allowing more specific dental examinations. Finally, these specific treatments are presented via a client/server application with the aim of allowing a telediagnosis and treatment.

  8. Online Event Segmentation in Active Perception using Adaptive Strong Anticipation

    CERN Document Server

    Nery, Bruno

    2010-01-01

    Most cognitive architectures rely on discrete representation, both in space (e.g., objects) and in time (e.g., events). However, a robot interaction with the world is inherently continuous, both in space and in time. The segmentation of the stream of perceptual inputs a robot receives into discrete and meaningful events poses as a challenge in bridging the gap between internal cognitive representations, and the external world. Event Segmentation Theory, recently proposed in the context of cognitive systems research, sustains that humans segment time into events based on matching perceptual input with predictions. In this work we propose a framework for online event segmentation, targeting robots endowed with active perception. Moreover, sensory processing systems have an intrinsic latency, resulting from many factors such as sampling rate, and computational processing, and which is seldom accounted for. This framework is founded on the theory of dynamical systems synchronization, where the system considered i...

  9. 3D adaptive finite element method for a phase field model for the moving contact line problems

    KAUST Repository

    Shi, Yi

    2013-08-01

    In this paper, we propose an adaptive finite element method for simulating the moving contact line problems in three dimensions. The model that we used is the coupled Cahn-Hilliard Navier-Stokes equations with the generalized Navier boundary condition(GNBC) proposed in [18]. In our algorithm, to improve the efficiency of the simulation, we use the residual type adaptive finite element algorithm. It is well known that the phase variable decays much faster away from the interface than the velocity variables. There- fore we use an adaptive strategy that will take into account of such difference. Numerical experiments show that our algorithm is both efficient and reliable. © 2013 American Institute of Mathematical Sciences.

  10. Adapting Binary Information Retrieval Evaluation Metrics for Segment-based Retrieval Tasks

    OpenAIRE

    Aly, Robin; Eskevich, Maria; Ordelman, Roeland; Jones, Gareth J.F.

    2013-01-01

    This report describes metrics for the evaluation of the effectiveness of segment-based retrieval based on existing binary information retrieval metrics. This metrics are described in the context of a task for the hyperlinking of video segments. This evaluation approach re-uses existing evaluation measures from the standard Cranfield evaluation paradigm. Our adaptation approach can in principle be used with any kind of effectiveness measure that uses binary relevance, and for other segment-bae...

  11. Segmentation et modélisation des structures vasculaires cérébrales en imagerie médicale 3D

    OpenAIRE

    Dufour, Alice

    2013-01-01

    Angiographie images are useful data for several tasks, e.g., diagnosis, pathology follow-up or surgery planning. However, due to low SNR (noise,artifacts), and complex semantic content (sparseness), angiographie image analysis is a time consurning and error prone task. These consideration have motivated the development of numerous vesse! filtering, segmentation, or modeling techinques.This thesis is organized around two research areas : the segmentation anù the moùeling. Segmentation of cereb...

  12. Cross-axis adaptation improves 3D vestibulo-ocular reflex alignment during chronic stimulation via a head-mounted multichannel vestibular prosthesis.

    Science.gov (United States)

    Dai, Chenkai; Fridman, Gene Y; Chiang, Bryce; Davidovics, Natan S; Melvin, Thuy-Anh; Cullen, Kathleen E; Della Santina, Charles C

    2011-05-01

    By sensing three-dimensional (3D) head rotation and electrically stimulating the three ampullary branches of a vestibular nerve to encode head angular velocity, a multichannel vestibular prosthesis (MVP) can restore vestibular sensation to individuals disabled by loss of vestibular hair cell function. However, current spread to afferent fibers innervating non-targeted canals and otolith end organs can distort the vestibular nerve activation pattern, causing misalignment between the perceived and actual axis of head rotation. We hypothesized that over time, central neural mechanisms can adapt to correct this misalignment. To test this, we rendered five chinchillas vestibular deficient via bilateral gentamicin treatment and unilaterally implanted them with a head-mounted MVP. Comparison of 3D angular vestibulo-ocular reflex (aVOR) responses during 2 Hz, 50°/s peak horizontal sinusoidal head rotations in darkness on the first, third, and seventh days of continual MVP use revealed that eye responses about the intended axis remained stable (at about 70% of the normal gain) while misalignment improved significantly by the end of 1 week of prosthetic stimulation. A comparable time course of improvement was also observed for head rotations about the other two semicircular canal axes and at every stimulus frequency examined (0.2-5 Hz). In addition, the extent of disconjugacy between the two eyes progressively improved during the same time window. These results indicate that the central nervous system rapidly adapts to multichannel prosthetic vestibular stimulation to markedly improve 3D aVOR alignment within the first week after activation. Similar adaptive improvements are likely to occur in other species, including humans.

  13. Adaptive RT in rectal cancer: superior to 3D-CRT? A simple question, a complex answer

    Energy Technology Data Exchange (ETDEWEB)

    Haustermans, K.; Roels, S.; Verstraete, J.; Depuydt, T. [Leuvens Kanker Inst., Dept. of Radiotherapy, Univ. Hospital Gasthuisberg, Leuven (Belgium); Slagmolen, P. [ESAT/Radiology, Medical Image Computing, Univ. Hospital Gasthuisberg, ESAT, Leuven (Belgium)

    2007-12-15

    Although the introduction of modern treatment techniques such as Total Mesorectal Excision (TME) and combined preoperative chemoradiation has strongly reduced local recurrence rates, there is still room for improvement in treatment in high-risk patients (T3-T4, lymph node positive). In these selected patients, progress may be achieved with higher preoperative doses and by integrating novel chemotherapeutic and molecular targeted agents. Better treatment techniques such as adaptive radiotherapy may ultimately lead to less local recurrences and more sphincter and even organ preservation. But before adaptive radiation can be introduced into clinical routine several steps have to be taken going from target definition over target localisation and positioning to re-planning and cumulative dosimetry. (orig.)

  14. Goal-Oriented Self-Adaptive hp Finite Element Simulation of 3D DC Borehole Resistivity Simulations

    KAUST Repository

    Calo, Victor M.

    2011-05-14

    In this paper we present a goal-oriented self-adaptive hp Finite Element Method (hp-FEM) with shared data structures and a parallel multi-frontal direct solver. The algorithm automatically generates (without any user interaction) a sequence of meshes delivering exponential convergence of a prescribed quantity of interest with respect to the number of degrees of freedom. The sequence of meshes is generated from a given initial mesh, by performing h (breaking elements into smaller elements), p (adjusting polynomial orders of approximation) or hp (both) refinements on the finite elements. The new parallel implementation utilizes a computational mesh shared between multiple processors. All computational algorithms, including automatic hp goal-oriented adaptivity and the solver work fully in parallel. We describe the parallel self-adaptive hp-FEM algorithm with shared computational domain, as well as its efficiency measurements. We apply the methodology described to the three-dimensional simulation of the borehole resistivity measurement of direct current through casing in the presence of invasion.

  15. Simultaneous 3D segmentation of three bone compartments on high resolution knee MR images from osteoarthritis initiative (OAI) using graph cuts

    Science.gov (United States)

    Shim, Hackjoon; Kwoh, C. Kent; Yun, Il Dong; Lee, Sang Uk; Bae, Kyongtae

    2009-02-01

    Osteoarthritis (OA) is associated with degradation of cartilage and related changes in the underlying bone. Quantitative measurement of those changes from MR images is an important biomarker to study the progression of OA and it requires a reliable segmentation of knee bone and cartilage. As the most popular method, manual segmentation of knee joint structures by boundary delineation is highly laborious and subject to user-variation. To overcome these difficulties, we have developed a semi-automated method for segmentation of knee bones, which consisted of two steps: placement of seeds and computation of segmentation. In the first step, seeds were placed by the user on a number of slices and then were propagated automatically to neighboring images. The seed placement could be performed on any of sagittal, coronal, and axial planes. The second step, computation of segmentation, was based on a graph-cuts algorithm where the optimal segmentation is the one that minimizes a cost function, which integrated the seeds specified by the user and both the regional and boundary properties of the regions to be segmented. The algorithm also allows simultaneous segmentation of three compartments of the knee bone (femur, tibia, patella). Our method was tested on the knee MR images of six subjects from the osteoarthritis initiative (OAI). The segmentation processing time (mean+/-SD) was (22+/-4)min, which is much shorter than that by the manual boundary delineation method (typically several hours). With this improved efficiency, our segmentation method will facilitate the quantitative morphologic analysis of changes in knee bones associated with osteoarthritis.

  16. An efficient Video Segmentation Algorithm with Real time Adaptive Threshold Technique

    Directory of Open Access Journals (Sweden)

    Yasira Beevi C P

    2009-12-01

    Full Text Available Automatic video segmentation plays an important role in real-time MPEG-4 encoding systems. This paper presents a video segmentation algorithm for MPEG-4 camera system with change detection, background registration techniques and real time adaptive thresholdtechniques. This algorithm can give satisfying segmentation results with low computation load. Besides, it has shadow cancellation mode, which can deal with light changing effect and shadow effect. Furthermore, this algorithm also implemented real time adaptive threshold techniques by which the parameters can be decided automatically.

  17. An $h$-Adaptive Operator Splitting Method for Two-Phase Flow in 3D Heterogeneous Porous Media

    KAUST Repository

    Chueh, Chih-Che

    2013-01-01

    The simulation of multiphase flow in porous media is a ubiquitous problem in a wide variety of fields, such as fuel cell modeling, oil reservoir simulation, magma dynamics, and tumor modeling. However, it is computationally expensive. This paper presents an interconnected set of algorithms which we show can accelerate computations by more than two orders of magnitude compared to traditional techniques, yet retains the high accuracy necessary for practical applications. Specifically, we base our approach on a new adaptive operator splitting technique driven by an a posteriori criterion to separate the flow from the transport equations, adaptive meshing to reduce the size of the discretized problem, efficient block preconditioned solver techniques for fast solution of the discrete equations, and a recently developed artificial diffusion strategy to stabilize the numerical solution of the transport equation. We demonstrate the accuracy and efficiency of our approach using numerical experiments in one, two, and three dimensions using a program that is made available as part of a large open source library. © 2013 Society for Industrial and Applied Mathematics.

  18. An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration

    Institute of Scientific and Technical Information of China (English)

    李国宏; 施鹏飞

    2004-01-01

    This paper presents a methodology for off-line handwritten Chinese character recognition based on mergence of consecutive segments of adaptive duration. The handwritten Chinese character string is partitioned into a sequence of consecutive segments, which are combined to implement dissimilarity evaluation within a sliding window whose durations are determined adaptively by the integration of shapes and context of evaluations. The average stroke width is estimated for the handwritten Chinese character string, and a set of candidate character segmentation boundaries is found by using the integration of pixel and stroke features. The final decisions on segmentation and recognition are made under minimal arithmetical mean dissimilarities. Experiments proved that the proposed approach of adaptive duration outperforms the method of fixed duration, and is very effective for the recognition of overlapped, broken, touched, loosely configured Chinese characters.

  19. An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration

    Institute of Scientific and Technical Information of China (English)

    李国宏; 施鹏飞

    2004-01-01

    This paper presents a methodology for off-line handwritten Chinese character recognition based on mergence of consecutive segments of adaptive duration. The handwritten Chinese character string is partitioned into a sequence of consecutive segments,which are combined to implement dissimilarity evaluation within a sliding window whose durations are determined adaptively by the integration of shapes and context of evaluations. The average stroke width is estimated for the handwritten Chinese character string,and a set of candidate character segmentation boundaries is found by using the integration of pixel and stroke features. The final decisions on segmentation and recognition are made under minimal arithmetical mean dissimilarities. Experiments proved that the proposed approach of adaptive duration outperforms the method of fixed duration,and is very effective for the recognition of overlapped,broken,touched,loosely configured Chinese characters.

  20. A Bintree Energy Approach for Colour Image Segmentation Using Adaptive Channel Selection

    Institute of Scientific and Technical Information of China (English)

    TU Sheng-xian; ZHANG Su; CHEN Ya-zhu; XIAO Chang-yan; ZHANG Lei

    2008-01-01

    A new hierarchical approach called bintree energy segmentation was presented for color image seg-mentation. The image features are extracted by adaptive clustering on multi-channel data at each level and used as the criteria to dynamically select the best chromatic channel, where the segmentation is carried out. In this approach, an extended direct energy computation method based on the Chan-Vese model was proposed to segment the selected channel, and the segmentation outputs are then fused with other channels into new images,from which a new channel with better features is selected for the second round segmentation. This procedure is repeated until the preset condition is met. Finally, a binary segmentation tree is formed, in which each leaf represents a class of objects with a distinctive color. To facilitate the data organization, image background is employed in segmentation and channels fusion. The bintree energy segmentation exploits color information involved in all channels data and tries to optimize the global segmentation result by choosing the "best" chan-nel for segmentation at each level. The experiments show that the method is effective in speed, accuracy and flexibility.

  1. Adaptation, Commissioning, and Evaluation of a 3D Treatment Planning System for High-Resolution Small-Animal Irradiation.

    Science.gov (United States)

    Jeong, Jeho; Chen, Qing; Febo, Robert; Yang, Jie; Pham, Hai; Xiong, Jian-Ping; Zanzonico, Pat B; Deasy, Joseph O; Humm, John L; Mageras, Gig S

    2016-06-01

    Although spatially precise systems are now available for small-animal irradiations, there are currently limited software tools available for treatment planning for such irradiations. We report on the adaptation, commissioning, and evaluation of a 3-dimensional treatment planning system for use with a small-animal irradiation system. The 225-kV X-ray beam of the X-RAD 225Cx microirradiator (Precision X-Ray) was commissioned using both ion-chamber and radiochromic film for 10 different collimators ranging in field size from 1 mm in diameter to 40 × 40 mm(2) A clinical 3-dimensional treatment planning system (Metropolis) developed at our institution was adapted to small-animal irradiation by making it compatible with the dimensions of mice and rats, modeling the microirradiator beam orientations and collimators, and incorporating the measured beam data for dose calculation. Dose calculations in Metropolis were verified by comparison with measurements in phantoms. Treatment plans for irradiation of a tumor-bearing mouse were generated with both the Metropolis and the vendor-supplied software. The calculated beam-on times and the plan evaluation tools were compared. The dose rate at the central axis ranges from 74 to 365 cGy/min depending on the collimator size. Doses calculated with Metropolis agreed with phantom measurements within 3% for all collimators. The beam-on times calculated by Metropolis and the vendor-supplied software agreed within 1% at the isocenter. The modified 3-dimensional treatment planning system provides better visualization of the relationship between the X-ray beams and the small-animal anatomy as well as more complete dosimetric information on target tissues and organs at risk. It thereby enhances the potential of image-guided microirradiator systems for evaluation of dose-response relationships and for preclinical experimentation generally. PMID:25948321

  2. Adaptive Cell Segmentation and Tracking for Volumetric Confocal Microscopy Images of a Developing Plant Meristem

    Institute of Scientific and Technical Information of China (English)

    Min Liu; Anirban Chakraborty; Damanpreet Singh; Ram Kishor Yadav; Gopi Meenakshisundaram; G. Venugopala Reddy; Amit Roy-Chowdhury

    2011-01-01

    Automated segmentation and tracking of cells in actively developing tissues can provide high-throughput and quantitative spatiotemporal measurements of a range of cell behaviors; cell expansion and cell-division kinetics leading to a better understanding of the underlying dynamics of morphogenesis.Here,we have studied the problem of constructing cell lineages in time-lapse volumetric image stacks obtained using Confocal Laser Scanning Microscopy (CLSM).The novel contribution of the work lies in its ability to segment and track cells in densely packed tissue,the shoot apical meristem (SAM),through the use of a close-loop,adaptive segmentation,and tracking approach.The tracking output acts as an indicator of the quality of segmentation and,in turn,the segmentation can be improved to obtain better tracking results.We construct an optimization function that minimizes the segmentation error,which is,in turn,estimated from the tracking results.This adaptive approach significantly improves both tracking and segmentation when compared to an open loop framework in which segmentation and tracking modules operate separately.

  3. Multi-Class Simultaneous Adaptive Segmentation and Quality Control of Point Cloud Data

    Directory of Open Access Journals (Sweden)

    Ayman Habib

    2016-01-01

    Full Text Available 3D modeling of a given site is an important activity for a wide range of applications including urban planning, as-built mapping of industrial sites, heritage documentation, military simulation, and outdoor/indoor analysis of airflow. Point clouds, which could be either derived from passive or active imaging systems, are an important source for 3D modeling. Such point clouds need to undergo a sequence of data processing steps to derive the necessary information for the 3D modeling process. Segmentation is usually the first step in the data processing chain. This paper presents a region-growing multi-class simultaneous segmentation procedure, where planar, pole-like, and rough regions are identified while considering the internal characteristics (i.e., local point density/spacing and noise level of the point cloud in question. The segmentation starts with point cloud organization into a kd-tree data structure and characterization process to estimate the local point density/spacing. Then, proceeding from randomly-distributed seed points, a set of seed regions is derived through distance-based region growing, which is followed by modeling of such seed regions into planar and pole-like features. Starting from optimally-selected seed regions, planar and pole-like features are then segmented. The paper also introduces a list of hypothesized artifacts/problems that might take place during the region-growing process. Finally, a quality control process is devised to detect, quantify, and mitigate instances of partially/fully misclassified planar and pole-like features. Experimental results from airborne and terrestrial laser scanning as well as image-based point clouds are presented to illustrate the performance of the proposed segmentation and quality control framework.

  4. Improved Gaussian Mixture Models for Adaptive Foreground Segmentation

    DEFF Research Database (Denmark)

    Katsarakis, Nikolaos; Pnevmatikakis, Aristodemos; Tan, Zheng-Hua;

    2016-01-01

    elements to the baseline algorithm: The learning rate can change across space and time, while the Gaussian distributions can be merged together if they become similar due to their adaptation process. We quantify the importance of our enhancements and the effect of parameter tuning using an annotated...

  5. Development 3D model of adaptation of the Azerbaijan coastal zone at the various levels of Caspian Sea

    Science.gov (United States)

    Mammadov, Ramiz

    2013-04-01

    coastal areas at hydraulic engineering projects the sea level should be considered as multistage process, what we have considered by development of adaptation of a coastal zone The exact three-dimensional map of a coastal zone has been created. For different scenario sea levels, or example, -30.0; -29.0; -28.0; -27.0; -26.0; -25.0 and -24.0 exact coastal lines have been certain. Further maps of a vegetative cover, ground, social and economic and ecological conditions have been developed for different level and respective alterations are certain. More vulnerable coastal zone, flooded area and socio-economic damage were estimated.

  6. Adaptive Segmentation Method for 2-D Barcode Image Base on Mathematic Morphological

    Directory of Open Access Journals (Sweden)

    Jianhua Li

    2013-10-01

    Full Text Available Segmentation is a key process of 2-D barcode identification. In this study we propose a fast adaptive segmentation method that is based on morphological method which is suitable for kinds of 2-D barcode images with different scale, angle and sort. The algorithm is based on mathematical morphology, the basic idea of the algorithm is to use Multi-scale open reconstruction of mathematical morphology to transform the image continuously, then choose whether to terminate by the results of the adjacent image transformation and finally get the final segmentation results by further processing of the images obtain from termination.The proposed approach is applied in experiments on 2-D barcodes with complicated background. The results indicated that the proposed method is very effective in adaptively 2-D barcode image segmentation.

  7. Automatic Spatially-Adaptive Balancing of Energy Terms for Image Segmentation

    CERN Document Server

    Rao, Josna; Abugharbieh, Rafeef

    2009-01-01

    Image segmentation techniques are predominately based on parameter-laden optimization. The objective function typically involves weights for balancing competing image fidelity and segmentation regularization cost terms. Setting these weights suitably has been a painstaking, empirical process. Even if such ideal weights are found for a novel image, most current approaches fix the weight across the whole image domain, ignoring the spatially-varying properties of object shape and image appearance. We propose a novel technique that autonomously balances these terms in a spatially-adaptive manner through the incorporation of image reliability in a graph-based segmentation framework. We validate on synthetic data achieving a reduction in mean error of 47% (p-value << 0.05) when compared to the best fixed parameter segmentation. We also present results on medical images (including segmentations of the corpus callosum and brain tissue in MRI data) and on natural images.

  8. Emphysema quantification on low-dose CT using percentage of low-attenuation volume and size distribution of low-attenuation lung regions: Effects of adaptive iterative dose reduction using 3D processing

    Energy Technology Data Exchange (ETDEWEB)

    Nishio, Mizuho, E-mail: nmizuho@med.kobe-u.ac.jp [Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017 (Japan); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017 (Japan); Matsumoto, Sumiaki, E-mail: sumatsu@med.kobe-u.ac.jp [Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017 (Japan); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017 (Japan); Seki, Shinichiro, E-mail: sshin@med.kobe-u.ac.jp [Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017 (Japan); Koyama, Hisanobu, E-mail: hkoyama@med.kobe-u.ac.jp [Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017 (Japan); Ohno, Yoshiharu, E-mail: yosirad@kobe-u.ac.jp [Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017 (Japan); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017 (Japan); Fujisawa, Yasuko, E-mail: yasuko1.fujisawa@toshiba.co.jp [Toshiba Medical Systems Corporation, 1385 Shimoishigami, Otawara, Tochigi 324-8550 (Japan); Sugihara, Naoki, E-mail: naoki.sugihara@toshiba.co.jp [Toshiba Medical Systems Corporation, 1385 Shimoishigami, Otawara, Tochigi 324-8550 (Japan); and others

    2014-12-15

    Highlights: • Emphysema quantification (LAV% and D) was affected by image noise on low-dose CT. • For LAV% and D, AIDR 3D improved agreement of quantification on low-dose CT. • AIDR 3D has the potential to quantify emphysema accurately on low-dose CT. - Abstract: Purpose: To evaluate the effects of adaptive iterative dose reduction using 3D processing (AIDR 3D) for quantification of two measures of emphysema: percentage of low-attenuation volume (LAV%) and size distribution of low-attenuation lung regions. Method and materials: : Fifty-two patients who underwent standard-dose (SDCT) and low-dose CT (LDCT) were included. SDCT without AIDR 3D, LDCT without AIDR 3D, and LDCT with AIDR 3D were used for emphysema quantification. First, LAV% was computed at 10 thresholds from −990 to −900 HU. Next, at the same thresholds, linear regression on a log–log plot was used to compute the power law exponent (D) for the cumulative frequency-size distribution of low-attenuation lung regions. Bland–Altman analysis was used to assess whether AIDR 3D improved agreement between LDCT and SDCT for emphysema quantification of LAV% and D. Results: The mean relative differences in LAV% between LDCT without AIDR 3D and SDCT were 3.73%–88.18% and between LDCT with AIDR 3D and SDCT were −6.61% to 0.406%. The mean relative differences in D between LDCT without AIDR 3D and SDCT were 8.22%–19.11% and between LDCT with AIDR 3D and SDCT were 1.82%–4.79%. AIDR 3D improved agreement between LDCT and SDCT at thresholds from −930 to −990 HU for LAV% and at all thresholds for D. Conclusion: AIDR 3D improved the consistency between LDCT and SDCT for emphysema quantification of LAV% and D.

  9. A novel adaptive biogeochemical model, and its 3-D application for a decadal hindcast simulation of the biogeochemistry of the southern North Sea

    Science.gov (United States)

    Kerimoglu, Onur; Hofmeister, Richard; Wirtz, Kai

    2016-04-01

    Adaptation and acclimation processes are often ignored in ecosystem-scale model implementations, despite the long-standing recognition of their importance. Here we present a novel adaptive phytoplankton growth model where acclimation of the community to the changes in external resource ratios is accounted for, using optimality principles and dynamic physiological traits. We show that the model can reproduce the internal stoichiometries obtained at marginal supply ratios in chemostat experiments. The model is applied in a decadal hindcast simulation of the southern North Sea, where it is coupled to a 2-D benthic model and a 3-D hydrodynamic model in an approximately 1.5km horizontal resolution at the German Bight coast. The model is shown to have good skill in capturing the steep, coastal gradients in the German Bight, suggested by the match between the estimated and observed dissolved nutrient and chlorophyll concentrations. We then analyze the differential sensitivity of the coastal and off-shore zones to major drivers of the system, such as riverine nutrient loads. We demonstrate that the relevance of phytoplankton acclimation varies across coastal gradients and can become particularly significant in terms of summer nutrient depletion.

  10. Pulmonary airways tree segmentation from CT examinations using adaptive volume of interest

    Science.gov (United States)

    Park, Sang Cheol; Kim, Won Pil; Zheng, Bin; Leader, Joseph K.; Pu, Jiantao; Tan, Jun; Gur, David

    2009-02-01

    Airways tree segmentation is an important step in quantitatively assessing the severity of and changes in several lung diseases such as chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis. It can also be used in guiding bronchoscopy. The purpose of this study is to develop an automated scheme for segmenting the airways tree structure depicted on chest CT examinations. After lung volume segmentation, the scheme defines the first cylinder-like volume of interest (VOI) using a series of images depicting the trachea. The scheme then iteratively defines and adds subsequent VOIs using a region growing algorithm combined with adaptively determined thresholds in order to trace possible sections of airways located inside the combined VOI in question. The airway tree segmentation process is automatically terminated after the scheme assesses all defined VOIs in the iteratively assembled VOI list. In this preliminary study, ten CT examinations with 1.25mm section thickness and two different CT image reconstruction kernels ("bone" and "standard") were selected and used to test the proposed airways tree segmentation scheme. The experiment results showed that (1) adopting this approach affectively prevented the scheme from infiltrating into the parenchyma, (2) the proposed method reasonably accurately segmented the airways trees with lower false positive identification rate as compared with other previously reported schemes that are based on 2-D image segmentation and data analyses, and (3) the proposed adaptive, iterative threshold selection method for the region growing step in each identified VOI enables the scheme to segment the airways trees reliably to the 4th generation in this limited dataset with successful segmentation up to the 5th generation in a fraction of the airways tree branches.

  11. SU-E-J-123: Assessing Segmentation Accuracy of Internal Volumes and Sub-Volumes in 4D PET/CT of Lung Tumors Using a Novel 3D Printed Phantom

    Energy Technology Data Exchange (ETDEWEB)

    Soultan, D [University of California-San Diego, San Diego State University, La Jolla, CA (United States); Murphy, J; James, C; Hoh, C; Moiseenko, V; Cervino, L [University of California, San Diego, La Jolla, CA (United States); Gill, B [British Columbia Cancer Agency, Windsor, ON (Canada)

    2015-06-15

    Purpose: To assess the accuracy of internal target volume (ITV) segmentation of lung tumors for treatment planning of simultaneous integrated boost (SIB) radiotherapy as seen in 4D PET/CT images, using a novel 3D-printed phantom. Methods: The insert mimics high PET tracer uptake in the core and 50% uptake in the periphery, by using a porous design at the periphery. A lung phantom with the insert was placed on a programmable moving platform. Seven breathing waveforms of ideal and patient-specific respiratory motion patterns were fed to the platform, and 4D PET/CT scans were acquired of each of them. CT images were binned into 10 phases, and PET images were binned into 5 phases following the clinical protocol. Two scenarios were investigated for segmentation: a gate 30–70 window, and no gating. The radiation oncologist contoured the outer ITV of the porous insert with on CT images, while the internal void volume with 100% uptake was contoured on PET images for being indistinguishable from the outer volume in CT images. Segmented ITVs were compared to the expected volumes based on known target size and motion. Results: 3 ideal breathing patterns, 2 regular-breathing patient waveforms, and 2 irregular-breathing patient waveforms were used for this study. 18F-FDG was used as the PET tracer. The segmented ITVs from CT closely matched the expected motion for both no gating and gate 30–70 window, with disagreement of contoured ITV with respect to the expected volume not exceeding 13%. PET contours were seen to overestimate volumes in all the cases, up to more than 40%. Conclusion: 4DPET images of a novel 3D printed phantom designed to mimic different uptake values were obtained. 4DPET contours overestimated ITV volumes in all cases, while 4DCT contours matched expected ITV volume values. Investigation of the cause and effects of the discrepancies is undergoing.

  12. SU-E-J-123: Assessing Segmentation Accuracy of Internal Volumes and Sub-Volumes in 4D PET/CT of Lung Tumors Using a Novel 3D Printed Phantom

    International Nuclear Information System (INIS)

    Purpose: To assess the accuracy of internal target volume (ITV) segmentation of lung tumors for treatment planning of simultaneous integrated boost (SIB) radiotherapy as seen in 4D PET/CT images, using a novel 3D-printed phantom. Methods: The insert mimics high PET tracer uptake in the core and 50% uptake in the periphery, by using a porous design at the periphery. A lung phantom with the insert was placed on a programmable moving platform. Seven breathing waveforms of ideal and patient-specific respiratory motion patterns were fed to the platform, and 4D PET/CT scans were acquired of each of them. CT images were binned into 10 phases, and PET images were binned into 5 phases following the clinical protocol. Two scenarios were investigated for segmentation: a gate 30–70 window, and no gating. The radiation oncologist contoured the outer ITV of the porous insert with on CT images, while the internal void volume with 100% uptake was contoured on PET images for being indistinguishable from the outer volume in CT images. Segmented ITVs were compared to the expected volumes based on known target size and motion. Results: 3 ideal breathing patterns, 2 regular-breathing patient waveforms, and 2 irregular-breathing patient waveforms were used for this study. 18F-FDG was used as the PET tracer. The segmented ITVs from CT closely matched the expected motion for both no gating and gate 30–70 window, with disagreement of contoured ITV with respect to the expected volume not exceeding 13%. PET contours were seen to overestimate volumes in all the cases, up to more than 40%. Conclusion: 4DPET images of a novel 3D printed phantom designed to mimic different uptake values were obtained. 4DPET contours overestimated ITV volumes in all cases, while 4DCT contours matched expected ITV volume values. Investigation of the cause and effects of the discrepancies is undergoing

  13. Clinical application of contrast enhanced MRI 3D-Space-iso sequence in the entire segment spinal nerve roots imaging%增强3D-Space-iso序列在全段脊神经根成像中的临床应用

    Institute of Scientific and Technical Information of China (English)

    段圣武; 李一辉; 刘珺; 胡李男; 李亚; 黄文博

    2015-01-01

    目的:探讨3.0 T磁共振增强3D-Space-iso序列在全段脊神经根的显示及相应脊神经根病变的诊断价值。材料与方法搜集脊神经根病变患者15例,正常志愿者3例,进行常规MRI序列扫描,冠状位非增强及增强3D-Space-iso序列,后两者均用3D最大信号强度投影做重建后处理,观察各序列显示脊神经根形态、大小及长度、走行与病变的关系。结果增强3D-Space-iso显示脊神经根、神经节及节后纤维较非增强3D-Space-iso及常规序列有更高的清晰度,能更清晰显示脊神经根病变及病变对脊神经根的压迫及侵犯程度。15例患者中腰椎间盘突出10例,肿瘤性病变3例,神经根鞘囊肿2例。结论增强3D-Space-iso序列对显示脊神经根解剖结构、以及与病变的解剖关系具有更大的优势,为临床诊治脊神经根病变提供明确的诊断依据。%Objective:To investigate the display technique and application value of 3.0 T magnetic resonance contrast enhanced 3D-Space-iso sequence in the entire segment spinal nerve roots lesions.Materials and Methods: Fifteen cases of patients with spinal nerve roots lesions and 3 cases of healthy volunteers were included. MRI conventional sequence, coronary 3D-Space-iso sequences (contrast enhanced and non-contrast enhanced) were performed in all cases. The source coronal images of 3D-Space-iso were further reconstructed using maxium intensity projection(MIP) technique. All displayed nerve roots were morphologically analyzed and the relation with lesions was evaluated.Results:Contrast enhanced 3D-Space-iso sequence has the best visualization than the other two sequences of spinal nerve roots spinal ganlfion, postganglionic neuroifbers and the degree of invasion and compression by the lesions. Among the 15 cases, there were 10 cases of disk herniation, 3 cases of tumor and 2 case of nerve root cysts.Conclusion:Contrast enhanced 3D-Space-iso sequence shows more advantages

  14. Adaptive-optics SLO imaging combined with widefield OCT and SLO enables precise 3D localization of fluorescent cells in the mouse retina.

    Science.gov (United States)

    Zawadzki, Robert J; Zhang, Pengfei; Zam, Azhar; Miller, Eric B; Goswami, Mayank; Wang, Xinlei; Jonnal, Ravi S; Lee, Sang-Hyuck; Kim, Dae Yu; Flannery, John G; Werner, John S; Burns, Marie E; Pugh, Edward N

    2015-06-01

    Adaptive optics scanning laser ophthalmoscopy (AO-SLO) has recently been used to achieve exquisite subcellular resolution imaging of the mouse retina. Wavefront sensing-based AO typically restricts the field of view to a few degrees of visual angle. As a consequence the relationship between AO-SLO data and larger scale retinal structures and cellular patterns can be difficult to assess. The retinal vasculature affords a large-scale 3D map on which cells and structures can be located during in vivo imaging. Phase-variance OCT (pv-OCT) can efficiently image the vasculature with near-infrared light in a label-free manner, allowing 3D vascular reconstruction with high precision. We combined widefield pv-OCT and SLO imaging with AO-SLO reflection and fluorescence imaging to localize two types of fluorescent cells within the retinal layers: GFP-expressing microglia, the resident macrophages of the retina, and GFP-expressing cone photoreceptor cells. We describe in detail a reflective afocal AO-SLO retinal imaging system designed for high resolution retinal imaging in mice. The optical performance of this instrument is compared to other state-of-the-art AO-based mouse retinal imaging systems. The spatial and temporal resolution of the new AO instrumentation was characterized with angiography of retinal capillaries, including blood-flow velocity analysis. Depth-resolved AO-SLO fluorescent images of microglia and cone photoreceptors are visualized in parallel with 469 nm and 663 nm reflectance images of the microvasculature and other structures. Additional applications of the new instrumentation are discussed.

  15. An Adaptive Frame Skipping and VOP Interpolation Algorithm for Video Object Segmentation

    Institute of Scientific and Technical Information of China (English)

    YANGGaobo; ZHANGZhaoyang

    2004-01-01

    Video object segmentation is a key step for the successful use of MPEG-4. However, most of the current available segmentation algorithms are still far away from real-time performance. In order to improve the processing speed, an adaptive frame skipping and VOP interpolation algorithm is proposed in this paper. It adaptively determines the number of skipped frames based on the rigidity and motion complexity of video object. To interpolate the VOPs for skipped frames, a hi-directional projection scheme is adopted. Its principle is to perform a classification of those regions obtained by spatial segmentation for every frame in the sequence. It is valid for both rigid object and non-rigid object and can get good localization of object boundaries. Experimental results show that the proposed approach can improve the processing speed greatly while maintaining visually pleasant results.

  16. Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

    Directory of Open Access Journals (Sweden)

    Hui Liu

    2015-01-01

    Full Text Available The key problem of computer-aided diagnosis (CAD of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO pulmonary nodules than other typical algorithms.

  17. Perceptual adaptation to segmental and syllabic reductions in continuous spoken Dutch

    NARCIS (Netherlands)

    Poellmann, K.; Bosker, H.R.; McQueen, J.M.; Mitterer, H.A.

    2014-01-01

    This study investigates if and how listeners adapt to reductions in casual continuous speech. In a perceptual-learning variant of the visual-world paradigm, two groups of Dutch participants were exposed to either segmental (/b/ -> [upsilon] or syllabic (ver- -> [f:]) reductions in spoken Dutch

  18. Mobile 3 D Laser Scanning System in Shield Tunnel Segment Ovality Detection%移动式三维激光扫描系统在盾构隧道管片椭圆度检测中的应用

    Institute of Scientific and Technical Information of China (English)

    张华

    2015-01-01

    Several common methods of metro shield tunnel segment ovality detection are compared and basic princi -ples and internal and external workflow of Ovality detection based on mobile 3 D laser scanning system are analyzed by taking GRP5000 for example.The actual project shows that the ovality detection method based on mobile 3D laser scan-ning system has advantages in metro shield tunnel segment ovality detection .%介绍对比了几种常用的地铁盾构隧道管片椭圆度检测方法,并在此基础上以GRP5000系统为例分析了基于移动式三维激光扫描系统的椭圆度检测的基本原理及内外业工作流程。通过实际项目检验,表明基于移动式三维激光扫描系统的地铁盾构隧道管片椭圆度检测方法具有优势。

  19. Segmentation des tumeurs en imagerie médicale TEP basée sur la marche aléatoire 3D

    OpenAIRE

    Onoma, Dago Pacôme; Ruan, Su; Gardin, Isabelle; Monnehan, Georges Alain; Modzelewski, Romain; Vera, Pierre

    2012-01-01

    Cet article présente une méthode de segmentation automatique basée sur la Marche Aléatoire (MA). Face à certains problèmes de l'algorithme original telles que la dépendance vis-à-vis du choix de l'hyperparamètre \\beta, ainsi que la probabilité d'un marcheur d'aller vers un label, fonction exclusivement du gradient d'intensité des niveaux de gris, nous proposons une approche permettant de résoudre ces problèmes. Elle consiste à rendre l'hyperparamètre \\beta adaptatif et à intégrer la densité d...

  20. Single-Crystal to Single-Crystal Phase Transition and Segmented Thermochromic Luminescence in a Dynamic 3D Interpenetrated Ag(I) Coordination Network.

    Science.gov (United States)

    Yan, Zhi-Hao; Li, Xiao-Yu; Liu, Li-Wei; Yu, Si-Qi; Wang, Xing-Po; Sun, Di

    2016-02-01

    A new 3D Ag(I)-based coordination network, [Ag2(pz)(bdc)·H2O]n (1; pz = pyrazine and H2bdc = benzene-1,3-dicarboxylic acid), was constructed by one-pot assembly and structurally established by single-crystal X-ray diffraction at different temperatures. Upon cooling from 298 to 93 K, 1 undergo an interesting single-crystal to single-crystal phase transition from orthorhombic Ibca (Z = 16) to Pccn (Z = 32) at around 148 K. Both phases show a rare 2-fold-interpenetrated 4-connected lvt network but incorporate different [Ag2(COO)2] dimeric secondary building units. It is worth mentioning that complex 1 shows red- and blue-shifted luminescences in the 290-170 and 140-80 K temperature ranges, respectively. The variable-temperature single-crystal X-ray crystallographic studies suggest that the argentophilic interactions and rigidity of the structure dominated the luminescence chromism trends at the respective temperature ranges. Upon being mechanically ground, 1 exhibits a slight mechanoluminescence red shift from 589 to 604 nm at 298 K. PMID:26828950

  1. An adaptive spatial clustering method for automatic brain MR image segmentation

    Institute of Scientific and Technical Information of China (English)

    Jingdan Zhang; Daoqing Dai

    2009-01-01

    In this paper, an adaptive spatial clustering method is presented for automatic brain MR image segmentation, which is based on a competitive learning algorithm-self-organizing map (SOM). We use a pattern recognition approach in terms of feature generation and classifier design. Firstly, a multi-dimensional feature vector is constructed using local spatial information. Then, an adaptive spatial growing hierarchical SOM (ASGHSOM) is proposed as the classifier, which is an extension of SOM, fusing multi-scale segmentation with the competitive learning clustering algorithm to overcome the problem of overlapping grey-scale intensities on boundary regions. Furthermore, an adaptive spatial distance is integrated with ASGHSOM, in which local spatial information is considered in the cluster-ing process to reduce the noise effect and the classification ambiguity. Our proposed method is validated by extensive experiments using both simulated and real MR data with varying noise level, and is compared with the state-of-the-art algorithms.

  2. 3D Animation Essentials

    CERN Document Server

    Beane, Andy

    2012-01-01

    The essential fundamentals of 3D animation for aspiring 3D artists 3D is everywhere--video games, movie and television special effects, mobile devices, etc. Many aspiring artists and animators have grown up with 3D and computers, and naturally gravitate to this field as their area of interest. Bringing a blend of studio and classroom experience to offer you thorough coverage of the 3D animation industry, this must-have book shows you what it takes to create compelling and realistic 3D imagery. Serves as the first step to understanding the language of 3D and computer graphics (CG)Covers 3D anim

  3. 3D video

    CERN Document Server

    Lucas, Laurent; Loscos, Céline

    2013-01-01

    While 3D vision has existed for many years, the use of 3D cameras and video-based modeling by the film industry has induced an explosion of interest for 3D acquisition technology, 3D content and 3D displays. As such, 3D video has become one of the new technology trends of this century.The chapters in this book cover a large spectrum of areas connected to 3D video, which are presented both theoretically and technologically, while taking into account both physiological and perceptual aspects. Stepping away from traditional 3D vision, the authors, all currently involved in these areas, provide th

  4. Co-adaptability solution to conflict events in construction projects by segmented hierarchical algorithm

    Institute of Scientific and Technical Information of China (English)

    HOU XueLiang; LU Mei

    2008-01-01

    In order to seek the co-adaptability solution to conflict events in construction en-gineering projects,a new method referred to as segmented hierarchical algorithm is proposed in this paper by means of comparing co-adaptability evolution process of conflict events to the stackelberg model.By this new algorithm,local solutions to the first-order transformation of co-adaptability for conflict events can be ob-tained,based upon which,a global solution to the second-order transformation of co-adaptability for conflict events can also be decided by judging satisfaction de-gree of local solutions.The research results show that this algorithm can be used not only for obtaining co-adaptability solution to conflict events efficiently,but also for other general decision-making problems with multi-layers and multi-subsidi-aries in project management field.

  5. Co-adaptability solution to conflict events in construction projects by segmented hierarchical algorithm

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In order to seek the co-adaptability solution to conflict events in construction engineering projects, a new method referred to as segmented hierarchical algorithm is proposed in this paper by means of comparing co-adaptability evolution process of conflict events to the stackelberg model. By this new algorithm, local solutions to the first-order transformation of co-adaptability for conflict events can be obtained, based upon which, a global solution to the second-order transformation of co-adaptability for conflict events can also be decided by judging satisfaction degree of local solutions. The research results show that this algorithm can be used not only for obtaining co-adaptability solution to conflict events efficiently, but also for other general decision-making problems with multi-layers and multi-subsidi-aries in project management field.

  6. Dosimetric Evaluation of Automatic Segmentation for Adaptive IMRT for Head-and-Neck Cancer

    International Nuclear Information System (INIS)

    Purpose: Adaptive planning to accommodate anatomic changes during treatment requires repeat segmentation. This study uses dosimetric endpoints to assess automatically deformed contours. Methods and Materials: Sixteen patients with head-and-neck cancer had adaptive plans because of anatomic change during radiotherapy. Contours from the initial planning computed tomography (CT) were deformed to the mid-treatment CT using an intensity-based free-form registration algorithm then compared with the manually drawn contours for the same CT using the Dice similarity coefficient and an overlap index. The automatic contours were used to create new adaptive plans. The original and automatic adaptive plans were compared based on dosimetric outcomes of the manual contours and on plan conformality. Results: Volumes from the manual and automatic segmentation were similar; only the gross tumor volume (GTV) was significantly different. Automatic plans achieved lower mean coverage for the GTV: V95: 98.6 ± 1.9% vs. 89.9 ± 10.1% (p = 0.004) and clinical target volume: V95: 98.4 ± 0.8% vs. 89.8 ± 6.2% (p 3 of the spinal cord 39.9 ± 3.7 Gy vs. 42.8 ± 5.4 Gy (p = 0.034), but no difference for the remaining structures. Conclusions: Automatic segmentation is not robust enough to substitute for physician-drawn volumes, particularly for the GTV. However, it generates normal structure contours of sufficient accuracy when assessed by dosimetric end points.

  7. Beowulf 3D: a case study

    Science.gov (United States)

    Engle, Rob

    2008-02-01

    This paper discusses the creative and technical challenges encountered during the production of "Beowulf 3D," director Robert Zemeckis' adaptation of the Old English epic poem and the first film to be simultaneously released in IMAX 3D and digital 3D formats.

  8. Sealing Clay Text Segmentation Based on Radon-Like Features and Adaptive Enhancement Filters

    Directory of Open Access Journals (Sweden)

    Xia Zheng

    2015-01-01

    Full Text Available Text extraction is a key issue in sealing clay research. The traditional method based on rubbings increases the risk of sealing clay damage and is unfavorable to sealing clay protection. Therefore, using digital image of sealing clay, a new method for text segmentation based on Radon-like features and adaptive enhancement filters is proposed in this paper. First, adaptive enhancement LM filter bank is used to get the maximum energy image; second, the edge image of the maximum energy image is calculated; finally, Radon-like feature images are generated by combining maximum energy image and its edge image. The average image of Radon-like feature images is segmented by the image thresholding method. Compared with 2D Otsu, GA, and FastFCM, the experiment result shows that this method can perform better in terms of accuracy and completeness of the text.

  9. Impossible expectations: fMRI adaptation in the lateral occipital complex (LOC) is modulated by the statistical regularities of 3D structural information.

    Science.gov (United States)

    Freud, Erez; Ganel, Tzvi; Avidan, Galia

    2015-11-15

    fMRI adaptation (fMRIa), the attenuation of fMRI signal which follows repeated presentation of a stimulus, is a well-documented phenomenon. Yet, the underlying neural mechanisms supporting this effect are not fully understood. Recently, short-term perceptual expectations, induced by specific experimental settings, were shown to play an important modulating role in fMRIa. Here we examined the role of long-term expectations, based on 3D structural statistical regularities, in the modulation of fMRIa. To this end, human participants underwent fMRI scanning while performing a same-different task on pairs of possible (regular, expected) objects and spatially impossible (irregular, unexpected) objects. We hypothesized that given the spatial irregularity of impossible objects in relation to real-world visual experience, the visual system would always generate a prediction which is biased to the possible version of the objects. Consistently, fMRIa effects in the lateral occipital cortex (LOC) were found for possible, but not for impossible objects. Additionally, in alternating trials the order of stimulus presentation modulated LOC activity. That is, reduced activation was observed in trials in which the impossible version of the object served as the prime object (i.e. first object) and was followed by the possible version compared to the reverse order. These results were also supported by the behavioral advantage observed for trials that were primed by possible objects. Together, these findings strongly emphasize the importance of perceptual expectations in object representation and provide novel evidence for the role of real-world statistical regularities in eliciting fMRIa.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Liu, Jianfei; Dubra, Alfredo; Tam, Johnny

    2016-03-01

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

  12. Automatic segmentation of canine retinal OCT using adaptive gradient enhancement and region growing

    Science.gov (United States)

    He, Yufan; Sun, Yankui; Chen, Min; Zheng, Yuanjie; Liu, Hui; Leon, Cecilia; Beltran, William; Gee, James C.

    2016-03-01

    In recent years, several studies have shown that the canine retina model offers important insight for our understanding of human retinal diseases. Several therapies developed to treat blindness in such models have already moved onto human clinical trials, with more currently under development [1]. Optical coherence tomography (OCT) offers a high resolution imaging modality for performing in-vivo analysis of the retinal layers. However, existing algorithms for automatically segmenting and analyzing such data have been mostly focused on the human retina. As a result, canine retinal images are often still being analyzed using manual segmentations, which is a slow and laborious task. In this work, we propose a method for automatically segmenting 5 boundaries in canine retinal OCT. The algorithm employs the position relationships between different boundaries to adaptively enhance the gradient map. A region growing algorithm is then used on the enhanced gradient maps to find the five boundaries separately. The automatic segmentation was compared against manual segmentations showing an average absolute error of 5.82 +/- 4.02 microns.

  13. EUROPEANA AND 3D

    Directory of Open Access Journals (Sweden)

    D. Pletinckx

    2012-09-01

    Full Text Available The current 3D hype creates a lot of interest in 3D. People go to 3D movies, but are we ready to use 3D in our homes, in our offices, in our communication? Are we ready to deliver real 3D to a general public and use interactive 3D in a meaningful way to enjoy, learn, communicate? The CARARE project is realising this for the moment in the domain of monuments and archaeology, so that real 3D of archaeological sites and European monuments will be available to the general public by 2012. There are several aspects to this endeavour. First of all is the technical aspect of flawlessly delivering 3D content over all platforms and operating systems, without installing software. We have currently a working solution in PDF, but HTML5 will probably be the future. Secondly, there is still little knowledge on how to create 3D learning objects, 3D tourist information or 3D scholarly communication. We are still in a prototype phase when it comes to integrate 3D objects in physical or virtual museums. Nevertheless, Europeana has a tremendous potential as a multi-facetted virtual museum. Finally, 3D has a large potential to act as a hub of information, linking to related 2D imagery, texts, video, sound. We describe how to create such rich, explorable 3D objects that can be used intuitively by the generic Europeana user and what metadata is needed to support the semantic linking.

  14. Solid works 3D

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Cheol Yeong

    2004-02-15

    This book explains modeling of solid works 3D and application of 3D CAD/CAM. The contents of this book are outline of modeling such as CAD and 2D and 3D, solid works composition, method of sketch, writing measurement fixing, selecting projection, choosing condition of restriction, practice of sketch, making parts, reforming parts, modeling 3D, revising 3D modeling, using pattern function, modeling necessaries, assembling, floor plan, 3D modeling method, practice floor plans for industrial engineer data aided manufacturing, processing of CAD/CAM interface.

  15. Solid works 3D

    International Nuclear Information System (INIS)

    This book explains modeling of solid works 3D and application of 3D CAD/CAM. The contents of this book are outline of modeling such as CAD and 2D and 3D, solid works composition, method of sketch, writing measurement fixing, selecting projection, choosing condition of restriction, practice of sketch, making parts, reforming parts, modeling 3D, revising 3D modeling, using pattern function, modeling necessaries, assembling, floor plan, 3D modeling method, practice floor plans for industrial engineer data aided manufacturing, processing of CAD/CAM interface.

  16. 3D Integration for Wireless Multimedia

    Science.gov (United States)

    Kimmich, Georg

    The convergence of mobile phone, internet, mapping, gaming and office automation tools with high quality video and still imaging capture capability is becoming a strong market trend for portable devices. High-density video encode and decode, 3D graphics for gaming, increased application-software complexity and ultra-high-bandwidth 4G modem technologies are driving the CPU performance and memory bandwidth requirements close to the PC segment. These portable multimedia devices are battery operated, which requires the deployment of new low-power-optimized silicon process technologies and ultra-low-power design techniques at system, architecture and device level. Mobile devices also need to comply with stringent silicon-area and package-volume constraints. As for all consumer devices, low production cost and fast time-to-volume production is key for success. This chapter shows how 3D architectures can bring a possible breakthrough to meet the conflicting power, performance and area constraints. Multiple 3D die-stacking partitioning strategies are described and analyzed on their potential to improve the overall system power, performance and cost for specific application scenarios. Requirements and maturity of the basic process-technology bricks including through-silicon via (TSV) and die-to-die attachment techniques are reviewed. Finally, we highlight new challenges which will arise with 3D stacking and an outlook on how they may be addressed: Higher power density will require thermal design considerations, new EDA tools will need to be developed to cope with the integration of heterogeneous technologies and to guarantee signal and power integrity across the die stack. The silicon/wafer test strategies have to be adapted to handle high-density IO arrays, ultra-thin wafers and provide built-in self-test of attached memories. New standards and business models have to be developed to allow cost-efficient assembly and testing of devices from different silicon and technology

  17. An adaptive segment method for smoothing lidar signal based on noise estimation

    Science.gov (United States)

    Wang, Yuzhao; Luo, Pingping

    2014-10-01

    An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.

  18. 3d-3d correspondence revisited

    Science.gov (United States)

    Chung, Hee-Joong; Dimofte, Tudor; Gukov, Sergei; Sułkowski, Piotr

    2016-04-01

    In fivebrane compactifications on 3-manifolds, we point out the importance of all flat connections in the proper definition of the effective 3d {N}=2 theory. The Lagrangians of some theories with the desired properties can be constructed with the help of homological knot invariants that categorify colored Jones polynomials. Higgsing the full 3d theories constructed this way recovers theories found previously by Dimofte-Gaiotto-Gukov. We also consider the cutting and gluing of 3-manifolds along smooth boundaries and the role played by all flat connections in this operation.

  19. A hybrid and adaptive segmentation method using color and texture information

    Science.gov (United States)

    Meurie, C.; Ruichek, Y.; Cohen, A.; Marais, J.

    2010-01-01

    This paper presents a new image segmentation method based on the combination of texture and color informations. The method first computes the morphological color and texture gradients. The color gradient is analyzed taking into account the different color spaces. The texture gradient is computed using the luminance component of the HSL color space. The texture gradient procedure is achieved using a morphological filter and a granulometric and local energy analysis. To overcome the limitations of a linear/barycentric combination, the two morphological gradients are then mixed using a gradient component fusion strategy (to fuse the three components of the color gradient and the unique component of the texture gradient) and an adaptive technique to choose the weighting coefficients. The segmentation process is finally performed by applying the watershed technique using different type of germ images. The segmentation method is evaluated in different object classification applications using the k-means algorithm. The obtained results are compared with other known segmentation methods. The evaluation analysis shows that the proposed method gives better results, especially with hard image acquisition conditions.

  20. IZDELAVA TISKALNIKA 3D

    OpenAIRE

    Brdnik, Lovro

    2015-01-01

    Diplomsko delo analizira trenutno stanje 3D tiskalnikov na trgu. Prikazan je razvoj in principi delovanja 3D tiskalnikov. Predstavljeni so tipi 3D tiskalnikov, njihove prednosti in slabosti. Podrobneje je predstavljena zgradba in delovanje koračnih motorjev. Opravljene so meritve koračnih motorjev. Opisana je programska oprema za rokovanje s 3D tiskalniki in komponente, ki jih potrebujemo za izdelavo. Diploma se oklepa vprašanja, ali je izdelava 3D tiskalnika bolj ekonomična kot pa naložba v ...

  1. Fast segmentation of 3D-ICT images by symmetric region growing method%利用对称区域生长算法实现三维ICT图像的快速分割

    Institute of Scientific and Technical Information of China (English)

    魏英; 田宝玉; 孙晶晶; 夏云野

    2011-01-01

    Image segmentation has been widely applied in the industrial computed tomography testing(ICT). Along with the ICT scanning mode developing from two-dimension to three-dimension, the computed tomography image analy sis has been changed from two-dimension image to three-dimension image . The traditional image segmentation methods have not kept up with the development yet. A symmetric region growing fast segmentation method is proposed The pa rameters used in the algorithm are computed automatically according to the ICT images. And the choice of the initial seed points doesn't affect the final results. Because this method processes the 3D images and combination the regions slice by slice, the cost of the memory is reduced greatly. The experimental results prove that this method has higher accuracy and computation efficiency than traditional segmentation algorithms.%图像分割作为一种基础的分析手段在工业计算机断层(Industrial Computed Tomography,ICT)检侧中有着广泛的应用.随着CT扫描方式从二维断层扫描向三维立体扫描的发展,对于CT图像的分析也由二维图像处理发展为三维序列图像处理,所以传统的图像分割手段已经不能很好地适应这种需求了.以目前在计算机视觉领域广泛应用的对称区域生长算法为基础,结合CT图像的特点对参数进行了自动选取,提出了适用于CT图像分析的对称区域生长分割算法.该方法不依赖于初始种子点的选择,对所有断层图像进行逐层处理和逐层合并,有效地降低了内存消耗.试验结果表明,该方法不仅分割精度高,而且计算效率也高于传统的分割算法.

  2. An efficient fully unsupervised video object segmentation scheme using an adaptive neural-network classifier architecture.

    Science.gov (United States)

    Doulamis, A; Doulamis, N; Ntalianis, K; Kollias, S

    2003-01-01

    In this paper, an unsupervised video object (VO) segmentation and tracking algorithm is proposed based on an adaptable neural-network architecture. The proposed scheme comprises: 1) a VO tracking module and 2) an initial VO estimation module. Object tracking is handled as a classification problem and implemented through an adaptive network classifier, which provides better results compared to conventional motion-based tracking algorithms. Network adaptation is accomplished through an efficient and cost effective weight updating algorithm, providing a minimum degradation of the previous network knowledge and taking into account the current content conditions. A retraining set is constructed and used for this purpose based on initial VO estimation results. Two different scenarios are investigated. The first concerns extraction of human entities in video conferencing applications, while the second exploits depth information to identify generic VOs in stereoscopic video sequences. Human face/ body detection based on Gaussian distributions is accomplished in the first scenario, while segmentation fusion is obtained using color and depth information in the second scenario. A decision mechanism is also incorporated to detect time instances for weight updating. Experimental results and comparisons indicate the good performance of the proposed scheme even in sequences with complicated content (object bending, occlusion).

  3. YouDash3D: exploring stereoscopic 3D gaming for 3D movie theaters

    Science.gov (United States)

    Schild, Jonas; Seele, Sven; Masuch, Maic

    2012-03-01

    Along with the success of the digitally revived stereoscopic cinema, events beyond 3D movies become attractive for movie theater operators, i.e. interactive 3D games. In this paper, we present a case that explores possible challenges and solutions for interactive 3D games to be played by a movie theater audience. We analyze the setting and showcase current issues related to lighting and interaction. Our second focus is to provide gameplay mechanics that make special use of stereoscopy, especially depth-based game design. Based on these results, we present YouDash3D, a game prototype that explores public stereoscopic gameplay in a reduced kiosk setup. It features live 3D HD video stream of a professional stereo camera rig rendered in a real-time game scene. We use the effect to place the stereoscopic effigies of players into the digital game. The game showcases how stereoscopic vision can provide for a novel depth-based game mechanic. Projected trigger zones and distributed clusters of the audience video allow for easy adaptation to larger audiences and 3D movie theater gaming.

  4. 3D and Education

    Science.gov (United States)

    Meulien Ohlmann, Odile

    2013-02-01

    Today the industry offers a chain of 3D products. Learning to "read" and to "create in 3D" becomes an issue of education of primary importance. 25 years professional experience in France, the United States and Germany, Odile Meulien set up a personal method of initiation to 3D creation that entails the spatial/temporal experience of the holographic visual. She will present some different tools and techniques used for this learning, their advantages and disadvantages, programs and issues of educational policies, constraints and expectations related to the development of new techniques for 3D imaging. Although the creation of display holograms is very much reduced compared to the creation of the 90ies, the holographic concept is spreading in all scientific, social, and artistic activities of our present time. She will also raise many questions: What means 3D? Is it communication? Is it perception? How the seeing and none seeing is interferes? What else has to be taken in consideration to communicate in 3D? How to handle the non visible relations of moving objects with subjects? Does this transform our model of exchange with others? What kind of interaction this has with our everyday life? Then come more practical questions: How to learn creating 3D visualization, to learn 3D grammar, 3D language, 3D thinking? What for? At what level? In which matter? for whom?

  5. Dimensional accuracy of 3D printed vertebra

    Science.gov (United States)

    Ogden, Kent; Ordway, Nathaniel; Diallo, Dalanda; Tillapaugh-Fay, Gwen; Aslan, Can

    2014-03-01

    3D printer applications in the biomedical sciences and medical imaging are expanding and will have an increasing impact on the practice of medicine. Orthopedic and reconstructive surgery has been an obvious area for development of 3D printer applications as the segmentation of bony anatomy to generate printable models is relatively straightforward. There are important issues that should be addressed when using 3D printed models for applications that may affect patient care; in particular the dimensional accuracy of the printed parts needs to be high to avoid poor decisions being made prior to surgery or therapeutic procedures. In this work, the dimensional accuracy of 3D printed vertebral bodies derived from CT data for a cadaver spine is compared with direct measurements on the ex-vivo vertebra and with measurements made on the 3D rendered vertebra using commercial 3D image processing software. The vertebra was printed on a consumer grade 3D printer using an additive print process using PLA (polylactic acid) filament. Measurements were made for 15 different anatomic features of the vertebral body, including vertebral body height, endplate width and depth, pedicle height and width, and spinal canal width and depth, among others. It is shown that for the segmentation and printing process used, the results of measurements made on the 3D printed vertebral body are substantially the same as those produced by direct measurement on the vertebra and measurements made on the 3D rendered vertebra.

  6. Novel 3D media technologies

    CERN Document Server

    Dagiuklas, Tasos

    2015-01-01

    This book describes recent innovations in 3D media and technologies, with coverage of 3D media capturing, processing, encoding, and adaptation, networking aspects for 3D Media, and quality of user experience (QoE). The contributions are based on the results of the FP7 European Project ROMEO, which focuses on new methods for the compression and delivery of 3D multi-view video and spatial audio, as well as the optimization of networking and compression jointly across the future Internet. The delivery of 3D media to individual users remains a highly challenging problem due to the large amount of data involved, diverse network characteristics and user terminal requirements, as well as the user’s context such as their preferences and location. As the number of visual views increases, current systems will struggle to meet the demanding requirements in terms of delivery of consistent video quality to fixed and mobile users. ROMEO will present hybrid networking solutions that combine the DVB-T2 and DVB-NGH broadcas...

  7. 3D future internet media

    CERN Document Server

    Dagiuklas, Tasos

    2014-01-01

    This book describes recent innovations in 3D media and technologies, with coverage of 3D media capturing, processing, encoding, and adaptation, networking aspects for 3D Media, and quality of user experience (QoE). The main contributions are based on the results of the FP7 European Projects ROMEO, which focus on new methods for the compression and delivery of 3D multi-view video and spatial audio, as well as the optimization of networking and compression jointly across the Future Internet (www.ict-romeo.eu). The delivery of 3D media to individual users remains a highly challenging problem due to the large amount of data involved, diverse network characteristics and user terminal requirements, as well as the user’s context such as their preferences and location. As the number of visual views increases, current systems will struggle to meet the demanding requirements in terms of delivery of constant video quality to both fixed and mobile users. ROMEO will design and develop hybrid-networking solutions that co...

  8. 3D virtuel udstilling

    DEFF Research Database (Denmark)

    Tournay, Bruno; Rüdiger, Bjarne

    2006-01-01

    3d digital model af Arkitektskolens gård med virtuel udstilling af afgangsprojekter fra afgangen sommer 2006. 10 s.......3d digital model af Arkitektskolens gård med virtuel udstilling af afgangsprojekter fra afgangen sommer 2006. 10 s....

  9. Robust semi-automatic segmentation of single- and multichannel MRI volumes through adaptable class-specific representation

    Science.gov (United States)

    Nielsen, Casper F.; Passmore, Peter J.

    2002-05-01

    Segmentation of MRI volumes is complicated by noise, inhomogeneity and partial volume artefacts. Fully or semi-automatic methods often require time consuming or unintuitive initialization. Adaptable Class-Specific Representation (ACSR) is a semi-automatic segmentation framework implemented by the Path Growing Algorithm (PGA), which reduces artefacts near segment boundaries. The user visually defines the desired segment classes through the selection of class templates and the following segmentation process is fully automatic. Good results have previously been achieved with color cryo section segmentation and ACSR has been developed further for the MRI modality. In this paper we present two optimizations for robust ACSR segmentation of MRI volumes. Automatic template creation based on an initial segmentation step using Learning Vector Quantization is applied for higher robustness to noise. Inhomogeneity correction is added as a pre-processing step, comparing the EQ and N3 algorithms. Results based on simulated T1-weighed and multispectral (T1 and T2) MRI data from the BrainWeb database and real data from the Internet Brain Segmentation Repository are presented. We show that ACSR segmentation compares favorably to previously published results on the same volumes and discuss the pros and cons of using quantitative ground truth evaluation compared to qualitative visual assessment.

  10. 立体视频对象分割及其三维重建算法研究%Research for stereo video object segmentation and 3 D reconstruction

    Institute of Scientific and Technical Information of China (English)

    高韬

    2011-01-01

    为更加有效分析立体视频对象,提出了一种基于离散冗余小波变换的立体视频对象分割算法.采用离散冗余小波变换提取特征点结合DT网格技术的视差估计方法,获得了可靠的视差场,再利用视差信息对立体视频中静止对象进行分割.对于立体视频序列中的运动对象,采用离散冗余小波提取运动区域的方法进行分割.实验结果表明,本算法对有重叠的多视频对象具有较好的分割效果,可同时分割静止物体和运动物体,具有较好的精确性和鲁棒性.对于分割出的立体视频对象,结合深度信息对其进行三维重建,得到较好的三维效果.%For more effective analysis of stereo video object, this paper proposed a discrete redundant wavelet transforms based stereo video object segmentation method. First, the method obtained the disparity map by discrete redundant wavelet transforms and used the disparity map to do video object segmentation. For the moving objects in the stereo video sequence,used the discrete redundant wavelet transforms to extract the motion region. Experimental results show that the method can not only segment the overlapping objects, but also can segment the stationary objects and moving objects at the same time with better accuracy and robustness. According to depth map, represented the visible scene surface with a para-metrically deformable,spatially adaptive, wireframe model.

  11. Blender 3D cookbook

    CERN Document Server

    Valenza, Enrico

    2015-01-01

    This book is aimed at the professionals that already have good 3D CGI experience with commercial packages and have now decided to try the open source Blender and want to experiment with something more complex than the average tutorials on the web. However, it's also aimed at the intermediate Blender users who simply want to go some steps further.It's taken for granted that you already know how to move inside the Blender interface, that you already have 3D modeling knowledge, and also that of basic 3D modeling and rendering concepts, for example, edge-loops, n-gons, or samples. In any case, it'

  12. Auto-adaptative Robot-aided Therapy based in 3D Virtual Tasks controlled by a Supervised and Dynamic Neuro-Fuzzy System

    Directory of Open Access Journals (Sweden)

    Luis Daniel Lledó

    2015-03-01

    Full Text Available This paper presents an application formed by a classification method based on the architecture of ART neural network (Adaptive Resonance Theory and the Fuzzy Set Theory to classify physiological reactions in order to automatically and dynamically adapt a robot-assisted rehabilitation therapy to the patient needs, using a three-dimensional task in a virtual reality system. Firstly, the mathematical and structural model of the neuro-fuzzy classification method is described together with the signal and training data acquisition. Then, the virtual designed task with physics behavior and its development procedure are explained. Finally, the general architecture of the experimentation for the auto-adaptive therapy is presented using the classification method with the virtual reality exercise.

  13. 3D meshes of carbon nanotubes guide functional reconnection of segregated spinal explants.

    Science.gov (United States)

    Usmani, Sadaf; Aurand, Emily Rose; Medelin, Manuela; Fabbro, Alessandra; Scaini, Denis; Laishram, Jummi; Rosselli, Federica B; Ansuini, Alessio; Zoccolan, Davide; Scarselli, Manuela; De Crescenzi, Maurizio; Bosi, Susanna; Prato, Maurizio; Ballerini, Laura

    2016-07-01

    In modern neuroscience, significant progress in developing structural scaffolds integrated with the brain is provided by the increasing use of nanomaterials. We show that a multiwalled carbon nanotube self-standing framework, consisting of a three-dimensional (3D) mesh of interconnected, conductive, pure carbon nanotubes, can guide the formation of neural webs in vitro where the spontaneous regrowth of neurite bundles is molded into a dense random net. This morphology of the fiber regrowth shaped by the 3D structure supports the successful reconnection of segregated spinal cord segments. We further observed in vivo the adaptability of these 3D devices in a healthy physiological environment. Our study shows that 3D artificial scaffolds may drive local rewiring in vitro and hold great potential for the development of future in vivo interfaces. PMID:27453939

  14. Radiochromic 3D Detectors

    Science.gov (United States)

    Oldham, Mark

    2015-01-01

    Radiochromic materials exhibit a colour change when exposed to ionising radiation. Radiochromic film has been used for clinical dosimetry for many years and increasingly so recently, as films of higher sensitivities have become available. The two principle advantages of radiochromic dosimetry include greater tissue equivalence (radiologically) and the lack of requirement for development of the colour change. In a radiochromic material, the colour change arises direct from ionising interactions affecting dye molecules, without requiring any latent chemical, optical or thermal development, with important implications for increased accuracy and convenience. It is only relatively recently however, that 3D radiochromic dosimetry has become possible. In this article we review recent developments and the current state-of-the-art of 3D radiochromic dosimetry, and the potential for a more comprehensive solution for the verification of complex radiation therapy treatments, and 3D dose measurement in general.

  15. 3D Projection Installations

    DEFF Research Database (Denmark)

    Halskov, Kim; Johansen, Stine Liv; Bach Mikkelsen, Michelle

    2014-01-01

    Three-dimensional projection installations are particular kinds of augmented spaces in which a digital 3-D model is projected onto a physical three-dimensional object, thereby fusing the digital content and the physical object. Based on interaction design research and media studies, this article...... contributes to the understanding of the distinctive characteristics of such a new medium, and identifies three strategies for designing 3-D projection installations: establishing space; interplay between the digital and the physical; and transformation of materiality. The principal empirical case, From...... Fingerplan to Loop City, is a 3-D projection installation presenting the history and future of city planning for the Copenhagen area in Denmark. The installation was presented as part of the 12th Architecture Biennale in Venice in 2010....

  16. Herramientas SIG 3D

    Directory of Open Access Journals (Sweden)

    Francisco R. Feito Higueruela

    2010-04-01

    Full Text Available Applications of Geographical Information Systems on several Archeology fields have been increasing during the last years. Recent avances in these technologies make possible to work with more realistic 3D models. In this paper we introduce a new paradigm for this system, the GIS Thetrahedron, in which we define the fundamental elements of GIS, in order to provide a better understanding of their capabilities. At the same time the basic 3D characteristics of some comercial and open source software are described, as well as the application to some samples on archeological researchs

  17. TOWARDS: 3D INTERNET

    OpenAIRE

    Ms. Swapnali R. Ghadge

    2013-01-01

    In today’s ever-shifting media landscape, it can be a complex task to find effective ways to reach your desired audience. As traditional media such as television continue to lose audience share, one venue in particular stands out for its ability to attract highly motivated audiences and for its tremendous growth potential the 3D Internet. The concept of '3D Internet' has recently come into the spotlight in the R&D arena, catching the attention of many people, and leading to a lot o...

  18. Bootstrapping 3D fermions

    Science.gov (United States)

    Iliesiu, Luca; Kos, Filip; Poland, David; Pufu, Silviu S.; Simmons-Duffin, David; Yacoby, Ran

    2016-03-01

    We study the conformal bootstrap for a 4-point function of fermions in 3D. We first introduce an embedding formalism for 3D spinors and compute the conformal blocks appearing in fermion 4-point functions. Using these results, we find general bounds on the dimensions of operators appearing in the ψ × ψ OPE, and also on the central charge C T . We observe features in our bounds that coincide with scaling dimensions in the GrossNeveu models at large N . We also speculate that other features could coincide with a fermionic CFT containing no relevant scalar operators.

  19. Interaktiv 3D design

    DEFF Research Database (Denmark)

    Villaume, René Domine; Ørstrup, Finn Rude

    2002-01-01

    Projektet undersøger potentialet for interaktiv 3D design via Internettet. Arkitekt Jørn Utzons projekt til Espansiva blev udviklet som et byggesystem med det mål, at kunne skabe mangfoldige planmuligheder og mangfoldige facade- og rumudformninger. Systemets bygningskomponenter er digitaliseret som...... 3D elementer og gjort tilgængelige. Via Internettet er det nu muligt at sammenstille og afprøve en uendelig  række bygningstyper som  systemet blev tænkt og udviklet til....

  20. Evaluation of Methods for Coregistration and Fusion of Rpas-Based 3d Point Clouds and Thermal Infrared Images

    Science.gov (United States)

    Hoegner, L.; Tuttas, S.; Xu, Y.; Eder, K.; Stilla, U.

    2016-06-01

    This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR) images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i) coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii) coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii) coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv) coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v) coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

  1. Tangible 3D Modelling

    DEFF Research Database (Denmark)

    Hejlesen, Aske K.; Ovesen, Nis

    2012-01-01

    This paper presents an experimental approach to teaching 3D modelling techniques in an Industrial Design programme. The approach includes the use of tangible free form models as tools for improving the overall learning. The paper is based on lecturer and student experiences obtained through facil...

  2. 3D Harmonic Echocardiography:

    NARCIS (Netherlands)

    M.M. Voormolen

    2007-01-01

    textabstractThree dimensional (3D) echocardiography has recently developed from an experimental technique in the ’90 towards an imaging modality for the daily clinical practice. This dissertation describes the considerations, implementation, validation and clinical application of a unique

  3. Adaptive stress response in segmental progeria resembles long-lived dwarfism and calorie restriction in mice.

    Directory of Open Access Journals (Sweden)

    Marieke van de Ven

    2006-12-01

    Full Text Available How congenital defects causing genome instability can result in the pleiotropic symptoms reminiscent of aging but in a segmental and accelerated fashion remains largely unknown. Most segmental progerias are associated with accelerated fibroblast senescence, suggesting that cellular senescence is a likely contributing mechanism. Contrary to expectations, neither accelerated senescence nor acute oxidative stress hypersensitivity was detected in primary fibroblast or erythroblast cultures from multiple progeroid mouse models for defects in the nucleotide excision DNA repair pathway, which share premature aging features including postnatal growth retardation, cerebellar ataxia, and death before weaning. Instead, we report a prominent phenotypic overlap with long-lived dwarfism and calorie restriction during postnatal development (2 wk of age, including reduced size, reduced body temperature, hypoglycemia, and perturbation of the growth hormone/insulin-like growth factor 1 neuroendocrine axis. These symptoms were also present at 2 wk of age in a novel progeroid nucleotide excision repair-deficient mouse model (XPD(G602D/R722W/XPA(-/- that survived weaning with high penetrance. However, despite persistent cachectic dwarfism, blood glucose and serum insulin-like growth factor 1 levels returned to normal by 10 wk, with hypoglycemia reappearing near premature death at 5 mo of age. These data strongly suggest changes in energy metabolism as part of an adaptive response during the stressful period of postnatal growth. Interestingly, a similar perturbation of the postnatal growth axis was not detected in another progeroid mouse model, the double-strand DNA break repair deficient Ku80(-/- mouse. Specific (but not all types of genome instability may thus engage a conserved response to stress that evolved to cope with environmental pressures such as food shortage.

  4. Image segmentation for uranium isotopic analysis by SIMS: Combined adaptive thresholding and marker controlled watershed approach

    Energy Technology Data Exchange (ETDEWEB)

    Willingham, David G.; Naes, Benjamin E.; Heasler, Patrick G.; Zimmer, Mindy M.; Barrett, Christopher A.; Addleman, Raymond S.

    2016-05-31

    A novel approach to particle identification and particle isotope ratio determination has been developed for nuclear safeguard applications. This particle search approach combines an adaptive thresholding algorithm and marker-controlled watershed segmentation (MCWS) transform, which improves the secondary ion mass spectrometry (SIMS) isotopic analysis of uranium containing particle populations for nuclear safeguards applications. The Niblack assisted MCWS approach (a.k.a. SEEKER) developed for this work has improved the identification of isotopically unique uranium particles under conditions that have historically presented significant challenges for SIMS image data processing techniques. Particles obtained from five NIST uranium certified reference materials (CRM U129A, U015, U150, U500 and U850) were successfully identified in regions of SIMS image data 1) where a high variability in image intensity existed, 2) where particles were touching or were in close proximity to one another and/or 3) where the magnitude of ion signal for a given region was count limited. Analysis of the isotopic distributions of uranium containing particles identified by SEEKER showed four distinct, accurately identified 235U enrichment distributions, corresponding to the NIST certified 235U/238U isotope ratios for CRM U129A/U015 (not statistically differentiated), U150, U500 and U850. Additionally, comparison of the minor uranium isotope (234U, 235U and 236U) atom percent values verified that, even in the absence of high precision isotope ratio measurements, SEEKER could be used to segment isotopically unique uranium particles from SIMS image data. Although demonstrated specifically for SIMS analysis of uranium containing particles for nuclear safeguards, SEEKER has application in addressing a broad set of image processing challenges.

  5. Improving Adaptive Learning Rate of BP Neural Network for the Modelling of 3D Woven Composites Using the Golden Section Law

    Institute of Scientific and Technical Information of China (English)

    易洪雷; 丁辛

    2001-01-01

    Focused on various BP algorithms with variable learning rate based on network system error gradient, a modified learning strategy for training non-linear network models is developed with both the incremental and the decremental factors of network learning rate being adjusted adaptively and dynamically. The golden section law is put forward to build a relationship between the network training parameters, and a series of data from an existing model is used to train and test the network parameters. By means of the evaluation of network performance in respect to convergent speed and predicting precision, the effectiveness of the proposed learning strategy can be illustrated.

  6. Adaptive stress response in segmental progeria resembles long-lived dwarfism and calorie restriction in mice

    NARCIS (Netherlands)

    H.W.M. van de Ven (Marieke); J.-O. Andressoo (Jaan-Olle); V.B. Holcomb (Valerie); M.M. von Lindern (Marieke); W.M.C. Jong (W. M C); C.I. de Zeeuw (Chris); Y. Suh (Yousin); P. Hasty (Paul); J.H.J. Hoeijmakers (Jan); G.T.J. van der Horst (Gijsbertus); J.R. Mitchell (James)

    2006-01-01

    textabstractHow congenital defects causing genome instability can result in the pleiotropic symptoms reminiscent of aging but in a segmental and accelerated fashion remains largely unknown. Most segmental progerias are associated with accelerated fibroblast senescence, suggesting that cellular senes

  7. Automated Adaptive Brightness in Wireless Capsule Endoscopy Using Image Segmentation and Sigmoid Function.

    Science.gov (United States)

    Shrestha, Ravi; Mohammed, Shahed K; Hasan, Md Mehedi; Zhang, Xuechao; Wahid, Khan A

    2016-08-01

    Wireless capsule endoscopy (WCE) plays an important role in the diagnosis of gastrointestinal (GI) diseases by capturing images of human small intestine. Accurate diagnosis of endoscopic images depends heavily on the quality of captured images. Along with image and frame rate, brightness of the image is an important parameter that influences the image quality which leads to the design of an efficient illumination system. Such design involves the choice and placement of proper light source and its ability to illuminate GI surface with proper brightness. Light emitting diodes (LEDs) are normally used as sources where modulated pulses are used to control LED's brightness. In practice, instances like under- and over-illumination are very common in WCE, where the former provides dark images and the later provides bright images with high power consumption. In this paper, we propose a low-power and efficient illumination system that is based on an automated brightness algorithm. The scheme is adaptive in nature, i.e., the brightness level is controlled automatically in real-time while the images are being captured. The captured images are segmented into four equal regions and the brightness level of each region is calculated. Then an adaptive sigmoid function is used to find the optimized brightness level and accordingly a new value of duty cycle of the modulated pulse is generated to capture future images. The algorithm is fully implemented in a capsule prototype and tested with endoscopic images. Commercial capsules like Pillcam and Mirocam were also used in the experiment. The results show that the proposed algorithm works well in controlling the brightness level accordingly to the environmental condition, and as a result, good quality images are captured with an average of 40% brightness level that saves power consumption of the capsule. PMID:27333609

  8. Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer

    NARCIS (Netherlands)

    L. Bondar (Luiza); M.S. Hoogeman (Mischa); W. Schillemans; B.J.M. Heijmen (Ben)

    2013-01-01

    textabstractFor online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and

  9. An Adaptive Sensor Data Segments Selection Method for Wearable Health Care Services.

    Science.gov (United States)

    Chen, Shih-Yeh; Lai, Chin-Feng; Hwang, Ren-Hung; Lai, Ying-Hsun; Wang, Ming-Shi

    2015-12-01

    As cloud computing and wearable devices technologies mature, relevant services have grown more and more popular in recent years. The healthcare field is one of the popular services for this technology that adopts wearable devices to sense signals of negative physiological events, and to notify users. The development and implementation of long-term healthcare monitoring that can prevent or quickly respond to the occurrence of disease and accidents present an interesting challenge for computing power and energy limits. This study proposed an adaptive sensor data segments selection method for wearable health care services, and considered the sensing frequency of the various signals from human body, as well as the data transmission among the devices. The healthcare service regulates the sensing frequency of devices by considering the overall cloud computing environment and the sensing variations of wearable health care services. The experimental results show that the proposed service can effectively transmit the sensing data and prolong the overall lifetime of health care services. PMID:26490152

  10. Segmentation by Fusion of Self-Adaptive SFCM Cluster in Multi-Color Space Components

    Directory of Open Access Journals (Sweden)

    Kun Chen

    2012-04-01

    Full Text Available This paper proposes a new, simple, and efficient segmentation approach that could find diverseapplications in pattern recognition as well as in computer vision, particularly in color imagesegmentation. First, we choose the best segmentation components among six different colorspaces. Then, Histogram and SFCM techniques are applied for initialization of segmentation.Finally, we fuse the segmentation results and merge similar regions. Extensive experiments havebeen taken on Berkeley image database by using the proposed algorithm. The results show that,compared with some classical segmentation algorithms, such as Mean-Shift, FCR and CTM, etc,our method could yield reasonably good or better image partitioning, which illustrates practicalvalue of the method.

  11. FUN3D Manual: 12.5

    Science.gov (United States)

    Biedron, Robert T.; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, William L.; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; Rumsey, Christopher L.; Thomas, James L.; Wood, William A.

    2014-01-01

    This manual describes the installation and execution of FUN3D version 12.5, including optional dependent packages. FUN3D is a suite of computational uid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables ecient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  12. FUN3D Manual: 13.0

    Science.gov (United States)

    Biedron, Robert T.; Carlson, Jan-Renee; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, Bill; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; Rumsey, Christopher L.; Thomas, James L.; Wood, William A.

    2016-01-01

    This manual describes the installation and execution of FUN3D version 13.0, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  13. FUN3D Manual: 12.9

    Science.gov (United States)

    Biedron, Robert T.; Carlson, Jan-Renee; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, Bil; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; Rumsey, Christopher L.; Thomas, James L.; Wood, William A.

    2016-01-01

    This manual describes the installation and execution of FUN3D version 12.9, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixed-element unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  14. FUN3D Manual: 12.4

    Science.gov (United States)

    Biedron, Robert T.; Derlaga, Joseph M.; Gnoffo, Peter A.; Hammond, Dana P.; Jones, William T.; Kleb, Bil; Lee-Rausch, Elizabeth M.; Nielsen, Eric J.; Park, Michael A.; Rumsey, Christopher L.; Thomas, James L.; Wood, William A.

    2014-01-01

    This manual describes the installation and execution of FUN3D version 12.4, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixedelement unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

  15. 3-D Human Modeling and Animation

    CERN Document Server

    Ratner, Peter

    2012-01-01

    3-D Human Modeling and Animation Third Edition All the tools and techniques you need to bring human figures to 3-D life Thanks to today's remarkable technology, artists can create and animate realistic, three-dimensional human figures that were not possible just a few years ago. This easy-to-follow book guides you through all the necessary steps to adapt your own artistic skill in figure drawing, painting, and sculpture to this exciting digital canvas. 3-D Human Modeling and Animation, Third Edition starts you off with simple modeling, then prepares you for more advanced techniques for crea

  16. 3D adaptive mesh refinement simulations of the gas cloud G2 born within the disks of young stars in the Galactic Center

    CERN Document Server

    Schartmann, M; Burkert, A; Gillessen, S; Genzel, R; Pfuhl, O; Eisenhauer, F; Plewa, P M; Ott, T; George, E M; Habibi, M

    2015-01-01

    The dusty, ionized gas cloud G2 is currently passing the massive black hole in the Galactic Center at a distance of roughly 2400 Schwarzschild radii. We explore the possibility of a starting point of the cloud within the disks of young stars. We make use of the large amount of new observations in order to put constraints on G2's origin. Interpreting the observations as a diffuse cloud of gas, we employ three-dimensional hydrodynamical adaptive mesh refinement (AMR) simulations with the PLUTO code and do a detailed comparison with observational data. The simulations presented in this work update our previously obtained results in multiple ways: (1) high resolution three-dimensional hydrodynamical AMR simulations are used, (2) the cloud follows the updated orbit based on the Brackett-$\\gamma$ data, (3) a detailed comparison to the observed high-quality position-velocity diagrams and the evolution of the total Brackett-$\\gamma$ luminosity is done. We concentrate on two unsolved problems of the diffuse cloud scen...

  17. Viability of 3 D Woven Carbon Cloth and Advanced Carbon-Carbon Ribs for Adaptive Deployable Entry Placement Technology (ADEPT) for Future NASA Missions

    Science.gov (United States)

    Venkatapathy, Ethiraj; Arnold, James O.; Peterson, K. H.; Blosser, M. L.

    2013-01-01

    This paper describes aerothermodynamic and thermal structural testing that demonstrate the viability of three dimensional woven carbon cloth and advanced carbon-carbon (ACC) ribs for use in the Adaptive Deployable Entry Placement Technology (ADEPT). ADEPT is an umbrella-like entry system that is folded for stowage in the launch vehicle's shroud and deployed prior to reaching the atmeopheric interface. A key feature of the ADEPT concept is a lower ballistic coefficient for delivery of a given payload than seen with conventional, rigid body entry systems. The benefits that accrue from the lower ballistic coefficient incllude factor-of-ten reductions of deceleration forces and entry heating. The former enables consideration of new classes of scientific instruments for solar system exploration while the latter enables the design of a more efficient thermal protection system. The carbon cloth base lined for ADEPT has a dual use in that it serves as the thermal protection system and as the "skin" that transfers aerdynamic deceleration loads to its umbrella-like substructure. Arcjet testing described in this paper was conducted for some of the higher heating conditions for a future Venus mission using the ADEPT concept, thereby showing that the carbon cloth can perform in a relevant entry environment. Recently completed the thermal structural testing of the cloth attached to a representative ACC rib design is also described. Finally, this paper describes a preliminary engineering level code, based on the arcjet data, that can be used to estimate cloth thickness for future ADEPT missions and to predict carbon cloth performance in future arcjet tests.

  18. An aerial 3D printing test mission

    Science.gov (United States)

    Hirsch, Michael; McGuire, Thomas; Parsons, Michael; Leake, Skye; Straub, Jeremy

    2016-05-01

    This paper provides an overview of an aerial 3D printing technology, its development and its testing. This technology is potentially useful in its own right. In addition, this work advances the development of a related in-space 3D printing technology. A series of aerial 3D printing test missions, used to test the aerial printing technology, are discussed. Through completing these test missions, the design for an in-space 3D printer may be advanced. The current design for the in-space 3D printer involves focusing thermal energy to heat an extrusion head and allow for the extrusion of molten print material. Plastics can be used as well as composites including metal, allowing for the extrusion of conductive material. A variety of experiments will be used to test this initial 3D printer design. High altitude balloons will be used to test the effects of microgravity on 3D printing, as well as parabolic flight tests. Zero pressure balloons can be used to test the effect of long 3D printing missions subjected to low temperatures. Vacuum chambers will be used to test 3D printing in a vacuum environment. The results will be used to adapt a current prototype of an in-space 3D printer. Then, a small scale prototype can be sent into low-Earth orbit as a 3-U cube satellite. With the ability to 3D print in space demonstrated, future missions can launch production hardware through which the sustainability and durability of structures in space will be greatly improved.

  19. Massive 3D Supergravity

    CERN Document Server

    Andringa, Roel; de Roo, Mees; Hohm, Olaf; Sezgin, Ergin; Townsend, Paul K

    2009-01-01

    We construct the N=1 three-dimensional supergravity theory with cosmological, Einstein-Hilbert, Lorentz Chern-Simons, and general curvature squared terms. We determine the general supersymmetric configuration, and find a family of supersymmetric adS vacua with the supersymmetric Minkowski vacuum as a limiting case. Linearizing about the Minkowski vacuum, we find three classes of unitary theories; one is the supersymmetric extension of the recently discovered `massive 3D gravity'. Another is a `new topologically massive supergravity' (with no Einstein-Hilbert term) that propagates a single (2,3/2) helicity supermultiplet.

  20. Massive 3D supergravity

    Energy Technology Data Exchange (ETDEWEB)

    Andringa, Roel; Bergshoeff, Eric A; De Roo, Mees; Hohm, Olaf [Centre for Theoretical Physics, University of Groningen, Nijenborgh 4, 9747 AG Groningen (Netherlands); Sezgin, Ergin [George and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, Texas A and M University, College Station, TX 77843 (United States); Townsend, Paul K, E-mail: E.A.Bergshoeff@rug.n, E-mail: O.Hohm@rug.n, E-mail: sezgin@tamu.ed, E-mail: P.K.Townsend@damtp.cam.ac.u [Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge, CB3 0WA (United Kingdom)

    2010-01-21

    We construct the N=1 three-dimensional supergravity theory with cosmological, Einstein-Hilbert, Lorentz Chern-Simons, and general curvature squared terms. We determine the general supersymmetric configuration, and find a family of supersymmetric adS vacua with the supersymmetric Minkowski vacuum as a limiting case. Linearizing about the Minkowski vacuum, we find three classes of unitary theories; one is the supersymmetric extension of the recently discovered 'massive 3D gravity'. Another is a 'new topologically massive supergravity' (with no Einstein-Hilbert term) that propagates a single (2,3/2) helicity supermultiplet.

  1. 3D Digital Modelling

    DEFF Research Database (Denmark)

    Hundebøl, Jesper

    ABSTRACT: Lack of productivity in construction is a well known issue. Despite the fact that causes hereof are multiple, the introduction of information technology is a frequently observed response to almost any challenge. ICT in construction is a thoroughly researched matter, however, the current...... important to appreciate the analysis. Before turning to the presentation of preliminary findings and a discussion of 3D digital modelling, it begins, however, with an outline of industry specific ICT strategic issues. Paper type. Multi-site field study...

  2. Visualization of liver in 3-D

    Science.gov (United States)

    Chen, Chin-Tu; Chou, Jin-Shin; Giger, Maryellen L.; Kahn, Charles E., Jr.; Bae, Kyongtae T.; Lin, Wei-Chung

    1991-05-01

    Visualization of the liver in three dimensions (3-D) can improve the accuracy of volumetric estimation and also aid in surgical planning. We have developed a method for 3-D visualization of the liver using x-ray computed tomography (CT) or magnetic resonance (MR) images. This method includes four major components: (1) segmentation algorithms for extracting liver data from tomographic images; (2) interpolation techniques for both shape and intensity; (3) schemes for volume rendering and display, and (4) routines for electronic surgery and image analysis. This method has been applied to cases from a living-donor liver transplant project and appears to be useful for surgical planning.

  3. TOWARDS: 3D INTERNET

    Directory of Open Access Journals (Sweden)

    Ms. Swapnali R. Ghadge

    2013-08-01

    Full Text Available In today’s ever-shifting media landscape, it can be a complex task to find effective ways to reach your desired audience. As traditional media such as television continue to lose audience share, one venue in particular stands out for its ability to attract highly motivated audiences and for its tremendous growth potential the 3D Internet. The concept of '3D Internet' has recently come into the spotlight in the R&D arena, catching the attention of many people, and leading to a lot of discussions. Basically, one can look into this matter from a few different perspectives: visualization and representation of information, and creation and transportation of information, among others. All of them still constitute research challenges, as no products or services are yet available or foreseen for the near future. Nevertheless, one can try to envisage the directions that can be taken towards achieving this goal. People who take part in virtual worlds stay online longer with a heightened level of interest. To take advantage of that interest, diverse businesses and organizations have claimed an early stake in this fast-growing market. They include technology leaders such as IBM, Microsoft, and Cisco, companies such as BMW, Toyota, Circuit City, Coca Cola, and Calvin Klein, and scores of universities, including Harvard, Stanford and Penn State.

  4. 一种基于在线模型匹配与更新的人脸三维表情运动跟踪算法%3D Facial Expressional Motion Tracking Algorithm Based on Online Model Adaptation and Updating

    Institute of Scientific and Technical Information of China (English)

    於俊; 汪增福

    2011-01-01

    提出一种基于在线模型匹配与更新的人脸三维表情运动跟踪算法.利用自适应的统计观测模型建立在线模型,自适应的状态转移模型结合改进的粒子滤波同时进行确定性搜索和随机化搜索,并且融合目标的多种测量信息减少光照和个体相关性的影响.利用所提出的算法既可以得到全局刚体运动参数,又可以得到局部柔性表情参数.实验证明了该算法的有效性.%A 3D facial expressional motion tracking algorithm based on online model adaptation and updating is proposed.It constructs the online model using an adaptive statistic observation model.With the combination of adaptive state transition model and improved particle filter, statistic search and determinate search are proposed simultaneously.Multi- measurements are infused to decrease lighting influence and person dependence.With the proposed algorithm, the global rigid motion parameters and local non rigid expressional parameters are obtained.Experiment result confirms the effectiveness of the proposed algorithm.

  5. Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C-Means Clustering.

    Science.gov (United States)

    Elazab, Ahmed; Wang, Changmiao; Jia, Fucang; Wu, Jianhuang; Li, Guanglin; Hu, Qingmao

    2015-01-01

    An adaptively regularized kernel-based fuzzy C-means clustering framework is proposed for segmentation of brain magnetic resonance images. The framework can be in the form of three algorithms for the local average grayscale being replaced by the grayscale of the average filter, median filter, and devised weighted images, respectively. The algorithms employ the heterogeneity of grayscales in the neighborhood and exploit this measure for local contextual information and replace the standard Euclidean distance with Gaussian radial basis kernel functions. The main advantages are adaptiveness to local context, enhanced robustness to preserve image details, independence of clustering parameters, and decreased computational costs. The algorithms have been validated against both synthetic and clinical magnetic resonance images with different types and levels of noises and compared with 6 recent soft clustering algorithms. Experimental results show that the proposed algorithms are superior in preserving image details and segmentation accuracy while maintaining a low computational complexity.

  6. Self-adapting segmentation for brain tissue%自适应脑组织影像分割

    Institute of Scientific and Technical Information of China (English)

    贾迪; 杨金柱; 张一飞; 赵大哲; 于戈

    2012-01-01

    A method for 2D and 3D brain tissue segmentation was presented.First,the noise of spinal fluid affecting the segmentation accuracy was eliminated using an improved C-V model.Then,the ventricle extraction and skull stripping were performed by C-V model and regions merging with tags.Finally,the white matter and grey matter were extracted through covered background method and the brain tissue was segmented.Simulation data was used for theoretical analysis,and the results were verified by real data.The accuracy,universality and practicality were validated by experiment results.%提出一种支持二维及三维MR脑影像的脑组织分割方法。首先采用改进的C-V模型去除脑脊液对灰质分割准确性的干扰。其次通过采用结合C-V模型的带标记区域增长算法,去除脑壳并提取脑室。最后结合覆盖背景的方法提取灰质及白质,从而实现了脑组织的自动分割。对该算法进行了仿真与实验验证,结果表明,该算法具备良好的准确性、通用性与实用性。

  7. Adaptive local multi-atlas segmentation: application to the heart and the caudate nucleus.

    NARCIS (Netherlands)

    Rikxoort, E.M. van; Isgum, I.; Arzhaeva, Y.; Staring, M.; Klein, S.; Viergever, M.A.; Pluim, J.P.; Ginneken, B. van

    2010-01-01

    Atlas-based segmentation is a powerful generic technique for automatic delineation of structures in volumetric images. Several studies have shown that multi-atlas segmentation methods outperform schemes that use only a single atlas, but running multiple registrations on volumetric data is time-consu

  8. Shaping 3-D boxes

    DEFF Research Database (Denmark)

    Stenholt, Rasmus; Madsen, Claus B.

    2011-01-01

    Enabling users to shape 3-D boxes in immersive virtual environments is a non-trivial problem. In this paper, a new family of techniques for creating rectangular boxes of arbitrary position, orientation, and size is presented and evaluated. These new techniques are based solely on position data......, making them different from typical, existing box shaping techniques. The basis of the proposed techniques is a new algorithm for constructing a full box from just three of its corners. The evaluation of the new techniques compares their precision and completion times in a 9 degree-of-freedom (Do......F) docking experiment against an existing technique, which requires the user to perform the rotation and scaling of the box explicitly. The precision of the users' box construction is evaluated by a novel error metric measuring the difference between two boxes. The results of the experiment strongly indicate...

  9. Optree: a learning-based adaptive watershed algorithm for neuron segmentation.

    Science.gov (United States)

    Uzunbaş, Mustafa Gökhan; Chen, Chao; Metaxas, Dimitris

    2014-01-01

    We present a new algorithm for automatic and interactive segmentation of neuron structures from electron microscopy (EM) images. Our method selects a collection of nodes from the watershed mergng tree as the proposed segmentation. This is achieved by building a onditional random field (CRF) whose underlying graph is the merging tree. The maximum a posteriori (MAP) prediction of the CRF is the output segmentation. Our algorithm outperforms state-of-the-art methods. Both the inference and the training are very efficient as the graph is tree-structured. Furthermore, we develop an interactive segmentation framework which selects uncertain regions for a user to proofread. The uncertainty is measured by the marginals of the graphical model. Based on user corrections, our framework modifies the merging tree and thus improves the segmentation globally. PMID:25333106

  10. Adaptive segmentation of nuclei in H&S stained tendon microscopy

    Science.gov (United States)

    Chuang, Bo-I.; Wu, Po-Ting; Hsu, Jian-Han; Jou, I.-Ming; Su, Fong-Chin; Sun, Yung-Nien

    2015-12-01

    Tendiopathy is a popular clinical issue in recent years. In most cases like trigger finger or tennis elbow, the pathology change can be observed under H and E stained tendon microscopy. However, the qualitative analysis is too subjective and thus the results heavily depend on the observers. We develop an automatic segmentation procedure which segments and counts the nuclei in H and E stained tendon microscopy fast and precisely. This procedure first determines the complexity of images and then segments the nuclei from the image. For the complex images, the proposed method adopts sampling-based thresholding to segment the nuclei. While for the simple images, the Laplacian-based thresholding is employed to re-segment the nuclei more accurately. In the experiments, the proposed method is compared with the experts outlined results. The nuclei number of proposed method is closed to the experts counted, and the processing time of proposed method is much faster than the experts'.

  11. Fusion of multisensor passive and active 3D imagery

    Science.gov (United States)

    Fay, David A.; Verly, Jacques G.; Braun, Michael I.; Frost, Carl E.; Racamato, Joseph P.; Waxman, Allen M.

    2001-08-01

    We have extended our previous capabilities for fusion of multiple passive imaging sensors to now include 3D imagery obtained from a prototype flash ladar. Real-time fusion of low-light visible + uncooled LWIR + 3D LADAR, and SWIR + LWIR + 3D LADAR is demonstrated. Fused visualization is achieved by opponent-color neural networks for passive image fusion, which is then textured upon segmented object surfaces derived from the 3D data. An interactive viewer, coded in Java3D, is used to examine the 3D fused scene in stereo. Interactive designation, learning, recognition and search for targets, based on fused passive + 3D signatures, is achieved using Fuzzy ARTMAP neural networks with a Java-coded GUI. A client-server web-based architecture enables remote users to interact with fused 3D imagery via a wireless palmtop computer.

  12. A New 3D Model-Based Tracking Technique for Robust Camera Pose Estimation

    Directory of Open Access Journals (Sweden)

    Fakhreddine Ababsa

    2012-04-01

    Full Text Available In this paper we present a new robust camera pose estimation approach based on 3D lines features. The proposed method is well adapted for mobile augmented reality applications We used an Extended Kalman Filter (EKF to incrementally update the camera pose in real-time. The principal contributions of our method include first, the expansion of the RANSAC scheme in order to achieve a robust matching algorithm that associates 2D edges from the image with the 3D line segments from the input model. And second, a new powerful framework for camera pose estimation using only 2D-3D straight-lines within an EKF. Experimental results on real image sequences are presented to evaluate the performances and the feasibility of the proposed approach in indoor and outdoor environments.

  13. 3D Maps Representation Using GNG

    Directory of Open Access Journals (Sweden)

    Vicente Morell

    2014-01-01

    Full Text Available Current RGB-D sensors provide a big amount of valuable information for mobile robotics tasks like 3D map reconstruction, but the storage and processing of the incremental data provided by the different sensors through time quickly become unmanageable. In this work, we focus on 3D maps representation and propose the use of the Growing Neural Gas (GNG network as a model to represent 3D input data. GNG method is able to represent the input data with a desired amount of neurons or resolution while preserving the topology of the input space. Experiments show how GNG method yields a better input space adaptation than other state-of-the-art 3D map representation methods.

  14. Simultaneous Whole-Brain Segmentation and White Matter Lesion Detection Using Contrast-Adaptive Probabilistic Models

    DEFF Research Database (Denmark)

    Puonti, Oula; Van Leemput, Koen

    2016-01-01

    In this paper we propose a new generative model for simultaneous brain parcellation and white matter lesion segmentation from multi-contrast magnetic resonance images. The method combines an existing whole-brain segmentation technique with a novel spatial lesion model based on a convolutional...... restricted Boltzmann machine. Unlike current state-of-the-art lesion detection techniques based on discriminative modeling, the proposed method is not tuned to one specific scanner or imaging protocol, and simultaneously segments dozens of neuroanatomical structures. Experiments on a public benchmark dataset...

  15. 3D printing for dummies

    CERN Document Server

    Hausman, Kalani Kirk

    2014-01-01

    Get started printing out 3D objects quickly and inexpensively! 3D printing is no longer just a figment of your imagination. This remarkable technology is coming to the masses with the growing availability of 3D printers. 3D printers create 3-dimensional layered models and they allow users to create prototypes that use multiple materials and colors.  This friendly-but-straightforward guide examines each type of 3D printing technology available today and gives artists, entrepreneurs, engineers, and hobbyists insight into the amazing things 3D printing has to offer. You'll discover methods for

  16. Cyto-3D-print to attach mitotic cells.

    Science.gov (United States)

    Castroagudin, Michelle R; Zhai, Yujia; Li, Zhi; Marnell, Michael G; Glavy, Joseph S

    2016-08-01

    The Cyto-3D-print is an adapter that adds cytospin capability to a standard centrifuge. Like standard cytospinning, Cyto-3D-print increases the surface attachment of mitotic cells while giving a higher degree of adaptability to other slide chambers than available commercial devices. The use of Cyto-3D-print is cost effective, safe, and applicable to many slide designs. It is durable enough for repeated use and made of biodegradable materials for environment-friendly disposal.

  17. Martian terrain - 3D

    Science.gov (United States)

    1997-01-01

    This area of terrain near the Sagan Memorial Station was taken on Sol 3 by the Imager for Mars Pathfinder (IMP). 3D glasses are necessary to identify surface detail.The IMP is a stereo imaging system with color capability provided by 24 selectable filters -- twelve filters per 'eye.' It stands 1.8 meters above the Martian surface, and has a resolution of two millimeters at a range of two meters.Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. The Jet Propulsion Laboratory, Pasadena, CA, developed and manages the Mars Pathfinder mission for NASA's Office of Space Science, Washington, D.C. JPL is an operating division of the California Institute of Technology (Caltech). The Imager for Mars Pathfinder (IMP) was developed by the University of Arizona Lunar and Planetary Laboratory under contract to JPL. Peter Smith is the Principal Investigator.Click below to see the left and right views individually. [figure removed for brevity, see original site] Left [figure removed for brevity, see original site] Right

  18. 3D monitor

    OpenAIRE

    Szkandera, Jan

    2009-01-01

    Tato bakalářská práce se zabývá návrhem a realizací systému, který umožní obraz scény zobrazovaný na ploše vnímat prostorově. Prostorové vnímání 2D obrazové informace je umožněno jednak stereopromítáním a jednak tím, že se obraz mění v závislosti na poloze pozorovatele. Tato práce se zabývá hlavně druhým z těchto problémů. This Bachelor's thesis goal is to design and realize system, which allows user to perceive 2D visual information as three-dimensional. 3D visual preception of 2D image i...

  19. Comparative analysis of different adaptive filters for tracking lower segments of a human body using inertial motion sensors

    International Nuclear Information System (INIS)

    For all segments and tests, a modified Kalman filter and a quasi-static sensor fusion algorithm were equally accurate (precision and accuracy ∼2–3°) compared to normalized least mean squares filtering, recursive least-squares filtering and standard Kalman filtering. The aims were to: (1) compare adaptive filtering techniques used for sensor fusion and (2) evaluate the precision and accuracy for a chosen adaptive filter. Motion sensors (based on inertial measurement units) are limited by accumulative integration errors arising from sensor bias. This drift can partly be handled with adaptive filtering techniques. To advance the measurement technique in this area, a new modified Kalman filter is developed. Differences in accuracy were observed during different tests especially drift in the internal/external rotation angle. This drift can be minimized if the sensors include magnetometers. (paper)

  20. 3D image analysis of abdominal aortic aneurysm

    Science.gov (United States)

    Subasic, Marko; Loncaric, Sven; Sorantin, Erich

    2002-05-01

    This paper presents a method for 3-D segmentation of abdominal aortic aneurysm from computed tomography angiography images. The proposed method is automatic and requires minimal user assistance. Segmentation is performed in two steps. First inner and then outer aortic border is segmented. Those two steps are different due to different image conditions on two aortic borders. Outputs of these two segmentations give a complete 3-D model of abdominal aorta. Such a 3-D model is used in measurements of aneurysm area. The deformable model is implemented using the level-set algorithm due to its ability to describe complex shapes in natural manner which frequently occur in pathology. In segmentation of outer aortic boundary we introduced some knowledge based preprocessing to enhance and reconstruct low contrast aortic boundary. The method has been implemented in IDL and C languages. Experiments have been performed using real patient CTA images and have shown good results.

  1. 3D game environments create professional 3D game worlds

    CERN Document Server

    Ahearn, Luke

    2008-01-01

    The ultimate resource to help you create triple-A quality art for a variety of game worlds; 3D Game Environments offers detailed tutorials on creating 3D models, applying 2D art to 3D models, and clear concise advice on issues of efficiency and optimization for a 3D game engine. Using Photoshop and 3ds Max as his primary tools, Luke Ahearn explains how to create realistic textures from photo source and uses a variety of techniques to portray dynamic and believable game worlds.From a modern city to a steamy jungle, learn about the planning and technological considerations for 3D modelin

  2. X3D: Extensible 3D Graphics Standard

    OpenAIRE

    Daly, Leonard; Brutzman, Don

    2007-01-01

    The article of record as published may be located at http://dx.doi.org/10.1109/MSP.2007.905889 Extensible 3D (X3D) is the open standard for Web-delivered three-dimensional (3D) graphics. It specifies a declarative geometry definition language, a run-time engine, and an application program interface (API) that provide an interactive, animated, real-time environment for 3D graphics. The X3D specification documents are freely available, the standard can be used without paying any royalties,...

  3. 3D Printing an Octohedron

    OpenAIRE

    Aboufadel, Edward F.

    2014-01-01

    The purpose of this short paper is to describe a project to manufacture a regular octohedron on a 3D printer. We assume that the reader is familiar with the basics of 3D printing. In the project, we use fundamental ideas to calculate the vertices and faces of an octohedron. Then, we utilize the OPENSCAD program to create a virtual 3D model and an STereoLithography (.stl) file that can be used by a 3D printer.

  4. Salient Local 3D Features for 3D Shape Retrieval

    CERN Document Server

    Godil, Afzal

    2011-01-01

    In this paper we describe a new formulation for the 3D salient local features based on the voxel grid inspired by the Scale Invariant Feature Transform (SIFT). We use it to identify the salient keypoints (invariant points) on a 3D voxelized model and calculate invariant 3D local feature descriptors at these keypoints. We then use the bag of words approach on the 3D local features to represent the 3D models for shape retrieval. The advantages of the method are that it can be applied to rigid as well as to articulated and deformable 3D models. Finally, this approach is applied for 3D Shape Retrieval on the McGill articulated shape benchmark and then the retrieval results are presented and compared to other methods.

  5. Lifting Object Detection Datasets into 3D.

    Science.gov (United States)

    Carreira, Joao; Vicente, Sara; Agapito, Lourdes; Batista, Jorge

    2016-07-01

    While data has certainly taken the center stage in computer vision in recent years, it can still be difficult to obtain in certain scenarios. In particular, acquiring ground truth 3D shapes of objects pictured in 2D images remains a challenging feat and this has hampered progress in recognition-based object reconstruction from a single image. Here we propose to bypass previous solutions such as 3D scanning or manual design, that scale poorly, and instead populate object category detection datasets semi-automatically with dense, per-object 3D reconstructions, bootstrapped from:(i) class labels, (ii) ground truth figure-ground segmentations and (iii) a small set of keypoint annotations. Our proposed algorithm first estimates camera viewpoint using rigid structure-from-motion and then reconstructs object shapes by optimizing over visual hull proposals guided by loose within-class shape similarity assumptions. The visual hull sampling process attempts to intersect an object's projection cone with the cones of minimal subsets of other similar objects among those pictured from certain vantage points. We show that our method is able to produce convincing per-object 3D reconstructions and to accurately estimate cameras viewpoints on one of the most challenging existing object-category detection datasets, PASCAL VOC. We hope that our results will re-stimulate interest on joint object recognition and 3D reconstruction from a single image. PMID:27295458

  6. 3D modelling and recognition

    OpenAIRE

    Rodrigues, Marcos; Robinson, Alan; Alboul, Lyuba; Brink, Willie

    2006-01-01

    3D face recognition is an open field. In this paper we present a method for 3D facial recognition based on Principal Components Analysis. The method uses a relatively large number of facial measurements and ratios and yields reliable recognition. We also highlight our approach to sensor development for fast 3D model acquisition and automatic facial feature extraction.

  7. An Improved Character Segmentation Algorithm Based on Local Adaptive Thresholding Technique for Chinese NvShu Documents

    Directory of Open Access Journals (Sweden)

    Yangguang Sun

    2014-06-01

    Full Text Available For the structural characteristics of Chinese NvShu character, by combining the basic idea in LLT local threshold algorithm and introducing the maximal between-class variance algorithm into local windows, an improved character segmentation algorithm based on local adaptive thresholding technique for Chinese NvShu documents was presented in this paper. Because of designing the corresponding correction parameters for the threshold and using secondary search mechanism, our proposed method could not only automatically obtain local threshold, but also avoid the loss of the character image information and improve the accuracy of the character image segmentation. Experimental results demonstrated its capability to reduce the effect of background noise, especially for Chinese NvShu character images with uneven illumination and low contrast

  8. SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Gupta, V; Wang, Y; Romero, A; Heijmen, B; Hoogeman, M [Erasmus MC Cancer Institute, Rotterdam (Netherlands); Myronenko, A; Jordan, P [Accuray Incorporated, Sunnyvale, United States. (United States)

    2014-06-01

    Purpose: Various studies have demonstrated that online adaptive radiotherapy by real-time re-optimization of the treatment plan can improve organs-at-risk (OARs) sparing in the abdominal region. Its clinical implementation, however, requires fast and accurate auto-segmentation of OARs in CT scans acquired just before each treatment fraction. Autosegmentation is particularly challenging in the abdominal region due to the frequently observed large deformations. We present a clinical validation of a new auto-segmentation method that uses fully automated non-rigid registration for propagating abdominal OAR contours from planning to daily treatment CT scans. Methods: OARs were manually contoured by an expert panel to obtain ground truth contours for repeat CT scans (3 per patient) of 10 patients. For the non-rigid alignment, we used a new non-rigid registration method that estimates the deformation field by optimizing local normalized correlation coefficient with smoothness regularization. This field was used to propagate planning contours to repeat CTs. To quantify the performance of the auto-segmentation, we compared the propagated and ground truth contours using two widely used metrics- Dice coefficient (Dc) and Hausdorff distance (Hd). The proposed method was benchmarked against translation and rigid alignment based auto-segmentation. Results: For all organs, the auto-segmentation performed better than the baseline (translation) with an average processing time of 15 s per fraction CT. The overall improvements ranged from 2% (heart) to 32% (pancreas) in Dc, and 27% (heart) to 62% (spinal cord) in Hd. For liver, kidneys, gall bladder, stomach, spinal cord and heart, Dc above 0.85 was achieved. Duodenum and pancreas were the most challenging organs with both showing relatively larger spreads and medians of 0.79 and 2.1 mm for Dc and Hd, respectively. Conclusion: Based on the achieved accuracy and computational time we conclude that the investigated auto-segmentation

  9. 3D Image Synthesis for B—Reps Objects

    Institute of Scientific and Technical Information of China (English)

    黄正东; 彭群生; 等

    1991-01-01

    This paper presents a new algorithm for generating 3D images of B-reps objects with trimmed surface boundaries.The 3D image is a discrete voxel-map representation within a Cubic Frame Buffer (CFB).The definition of 3D images for curve,surface and solid object are introduced which imply the connectivity and fidelity requirements.Adaptive Forward Differencing matrix (AFD-matrix) for 1D-3D manifolds in 3D space is developed.By setting rules to update the AFD-matrix,the forward difference direction and stepwise can be adjusted.Finally,an efficient algorithm is presented based on the AFD-matrix concept for converting the object in 3D space to 3D image in 3D discrete space.

  10. 3D Viewer Platform of Cloud Clustering Management System: Google Map 3D

    Science.gov (United States)

    Choi, Sung-Ja; Lee, Gang-Soo

    The new management system of framework for cloud envrionemnt is needed by the platfrom of convergence according to computing environments of changes. A ISV and small business model is hard to adapt management system of platform which is offered from super business. This article suggest the clustering management system of cloud computing envirionments for ISV and a man of enterprise in small business model. It applies the 3D viewer adapt from map3D & earth of google. It is called 3DV_CCMS as expand the CCMS[1].

  11. Comparisons of adaptive TIN modelling filtering method and threshold segmentation filtering method of LiDAR point cloud

    International Nuclear Information System (INIS)

    Point cloud filtering is the basic and key step in LiDAR data processing. Adaptive Triangle Irregular Network Modelling (ATINM) algorithm and Threshold Segmentation on Elevation Statistics (TSES) algorithm are among the mature algorithms. However, few researches concentrate on the parameter selections of ATINM and the iteration condition of TSES, which can greatly affect the filtering results. First the paper presents these two key problems under two different terrain environments. For a flat area, small height parameter and angle parameter perform well and for areas with complex feature changes, large height parameter and angle parameter perform well. One-time segmentation is enough for flat areas, and repeated segmentations are essential for complex areas. Then the paper makes comparisons and analyses of the results by these two methods. ATINM has a larger I error in both two data sets as it sometimes removes excessive points. TSES has a larger II error in both two data sets as it ignores topological relations between points. ATINM performs well even with a large region and a dramatic topology while TSES is more suitable for small region with flat topology. Different parameters and iterations can cause relative large filtering differences

  12. 3D-skannaukseen perehtyminen

    OpenAIRE

    Santaluoto, Olli

    2012-01-01

    Tässä insinöörityössä tarkastellaan erilaisia 3D-skannaustekniikoita ja menetelmiä. Työssä myös kerrotaan esimerkkien avulla eri 3D-skannaustekniikoiden käyttökohteista. 3D-skannaus on Suomessa vielä melko harvinaista, siksi eri tekniikat ja käyttömahdollisuudet ovat monille tuntemattomia. 3D-skanneri on laite, jolla tutkitaan reaalimaailman esineitä tai ympäristöä keräämällä dataa kohteen muodoista. 3D-skannerit ovat hyvin paljon vastaavia tavallisen kameran kanssa. Kuten kameroilla, 3D...

  13. Cerebrovascular Segmentation Based on Region Growing and Local Adaptive C-V Model%基于区域增长与局部自适应C-V模型的脑血管分割

    Institute of Scientific and Technical Information of China (English)

    解立志; 周明全; 田沄; 武仲科; 王醒策

    2013-01-01

      提出了一种针对TOF MRA(time-of-flight magnetic resonance angiography)磁共振图像的双重分割脑血管提取方法。首先结合高斯滤波,采用二维OTSU算法,结合MIP(maximum intensity projection)图像获得三维血管种子点,定义全局与局部信息相结合的区域增长规则,通过区域增长算法对血管进行粗分割;然后,采用 Catt 扩散模型对体数据场进行各向异性滤波,提出了局部自适应C-V模型,将初步分割结果作为自适应活动轮廓模型的初始轮廓线进行二次分割。实验结果表明,该算法不仅能够有效分割脑血管粗大分支,而且还能精确提取脑血管的细小结构。%This paper presents an effective approach to extract cerebrovascular tree from time-of-flight (TOF) magnetic resonance angiography (MRA) images. The approach consists of two segmentation stages. In the first stage, Gaussian filtering is implemented for the 3D volumetric field. By virtue of the maximum intensity projection (MIP) image segmented by the two dimensional OTSU algorithm, 3D vessel seeds are obtained. The region growing rule is defined by combining the global information with the local information, and then the rough segmentation is implemented by the region growing algorithm. In second stage, the original volume data is filtered by an anisotropic filtering based on Catt diffusion. A local adaptive C-V model is proposed, and the initial contour of the model is set by employing the first segmented vessels. Then the accurate segmentation is realized by the contour evolution. Experimental results show that the proposed algorithm is not only able to effectively segment the thick vessel, but also able to accurately extract the thinner vessels with weak boundaries.

  14. 3D Printing Functional Nanocomposites

    OpenAIRE

    Leong, Yew Juan

    2016-01-01

    3D printing presents the ability of rapid prototyping and rapid manufacturing. Techniques such as stereolithography (SLA) and fused deposition molding (FDM) have been developed and utilized since the inception of 3D printing. In such techniques, polymers represent the most commonly used material for 3D printing due to material properties such as thermo plasticity as well as its ability to be polymerized from monomers. Polymer nanocomposites are polymers with nanomaterials composited into the ...

  15. An Adaptive Online HDP-HMM for Segmentation and Classification of Sequential Data

    OpenAIRE

    Bargi, Ava; Da Xu, Richard Yi; Piccardi, Massimo

    2015-01-01

    In the recent years, the desire and need to understand sequential data has been increasing, with particular interest in sequential contexts such as patient monitoring, understanding daily activities, video surveillance, stock market and the like. Along with the constant flow of data, it is critical to classify and segment the observations on-the-fly, without being limited to a rigid number of classes. In addition, the model needs to be capable of updating its parameters to comply with possibl...

  16. 3D Elevation Program—Virtual USA in 3D

    Science.gov (United States)

    Lukas, Vicki; Stoker, J.M.

    2016-01-01

    The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) uses a laser system called ‘lidar’ (light detection and ranging) to create a virtual reality map of the Nation that is very accurate. 3D maps have many uses with new uses being discovered all the time.  

  17. 3D IBFV : Hardware-Accelerated 3D Flow Visualization

    NARCIS (Netherlands)

    Telea, Alexandru; Wijk, Jarke J. van

    2003-01-01

    We present a hardware-accelerated method for visualizing 3D flow fields. The method is based on insertion, advection, and decay of dye. To this aim, we extend the texture-based IBFV technique for 2D flow visualization in two main directions. First, we decompose the 3D flow visualization problem in a

  18. Interactive 3D multimedia content

    CERN Document Server

    Cellary, Wojciech

    2012-01-01

    The book describes recent research results in the areas of modelling, creation, management and presentation of interactive 3D multimedia content. The book describes the current state of the art in the field and identifies the most important research and design issues. Consecutive chapters address these issues. These are: database modelling of 3D content, security in 3D environments, describing interactivity of content, searching content, visualization of search results, modelling mixed reality content, and efficient creation of interactive 3D content. Each chapter is illustrated with example a

  19. 3D Bayesian contextual classifiers

    DEFF Research Database (Denmark)

    Larsen, Rasmus

    2000-01-01

    We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours.......We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours....

  20. 3-D printers for libraries

    CERN Document Server

    Griffey, Jason

    2014-01-01

    As the maker movement continues to grow and 3-D printers become more affordable, an expanding group of hobbyists is keen to explore this new technology. In the time-honored tradition of introducing new technologies, many libraries are considering purchasing a 3-D printer. Jason Griffey, an early enthusiast of 3-D printing, has researched the marketplace and seen several systems first hand at the Consumer Electronics Show. In this report he introduces readers to the 3-D printing marketplace, covering such topics asHow fused deposition modeling (FDM) printing workBasic terminology such as build

  1. 3D for Graphic Designers

    CERN Document Server

    Connell, Ellery

    2011-01-01

    Helping graphic designers expand their 2D skills into the 3D space The trend in graphic design is towards 3D, with the demand for motion graphics, animation, photorealism, and interactivity rapidly increasing. And with the meteoric rise of iPads, smartphones, and other interactive devices, the design landscape is changing faster than ever.2D digital artists who need a quick and efficient way to join this brave new world will want 3D for Graphic Designers. Readers get hands-on basic training in working in the 3D space, including product design, industrial design and visualization, modeling, ani

  2. Using 3D in Visualization

    DEFF Research Database (Denmark)

    Wood, Jo; Kirschenbauer, Sabine; Döllner, Jürgen;

    2005-01-01

    to display 3D imagery. The extra cartographic degree of freedom offered by using 3D is explored and offered as a motivation for employing 3D in visualization. The use of VR and the construction of virtual environments exploit navigational and behavioral realism, but become most usefil when combined...... with abstracted representations embedded in a 3D space. The interactions between development of geovisualization, the technology used to implement it and the theory surrounding cartographic representation are explored. The dominance of computing technologies, driven particularly by the gaming industry...

  3. Denoising and Back Ground Clutter of Video Sequence using Adaptive Gaussian Mixture Model Based Segmentation for Human Action Recognition

    Directory of Open Access Journals (Sweden)

    Shanmugapriya. K

    2014-01-01

    Full Text Available The human action recognition system first gathers images by simply querying the name of the action on a web image search engine like Google or Yahoo. Based on the assumption that the set of retrieved images contains relevant images of the queried action, we construct a dataset of action images in an incremental manner. This yields a large image set, which includes images of actions taken from multiple viewpoints in a range of environments, performed by people who have varying body proportions and different clothing. The images mostly present the “key poses” since these images try to convey the action with a single pose. In existing system to support this they first used an incremental image retrieval procedure to collect and clean up the necessary training set for building the human pose classifiers. There are challenges that come at the expense of this broad and representative data. First, the retrieved images are very noisy, since the Web is very diverse. Second, detecting and estimating the pose of humans in still images is more difficult than in videos, partly due to the background clutter and the lack of a foreground mask. In videos, foreground segmentation can exploit motion cues to great benefit. In still images, the only cue at hand is the appearance information and therefore, our model must address various challenges associated with different forms of appearance. Therefore for robust separation, in proposed work a segmentation algorithm based on Gaussian Mixture Models is proposed which is adaptive to light illuminations, shadow and white balance is proposed here. This segmentation algorithm processes the video with or without noise and sets up adaptive background models based on the characteristics also this method is a very effective technique for background modeling which classifies the pixels of a video frame either background or foreground based on probability distribution.

  4. CASTLE3D - A Computer Aided System for Labelling Archaeological Excavations in 3D

    Science.gov (United States)

    Houshiar, H.; Borrmann, D.; Elseberg, J.; Nüchter, A.; Näth, F.; Winkler, S.

    2015-08-01

    one label. Further information such as color, orientation and archaeological notes are added to the label to improve the documentation. The available 3D information allows for easy measurements in the data. The full 3D information of a region of interest can be segmented from the entire data. By joining this data from different georeferenced views the full 3D shape of findings is stored. All the generated documentation in CASTLE3D is exported to an XML format and serves as input for other systems and databases. Apart from presenting the functionalities of CASTLE3D we evaluate its documentation process in a sample project. For this purpose we export the data to the Adiuvabit database (http://adiuvabit.de) where more information is added for further analysis. The documentation process is compared to traditional documentation methods and it is shown how the automated system helps in accelerating the documentation process and decreases errors to a minimum.

  5. Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer

    Science.gov (United States)

    Luiza Bondar, M.; Hoogeman, Mischa; Schillemans, Wilco; Heijmen, Ben

    2013-08-01

    For online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and (2) to improve the segmentation accuracy by including prior knowledge on the daily bladder volume or on the daily coordinates of implanted fiducial markers. The tested methods were: shape deformation (SD) and atlas-based segmentation (ABAS) using two non-rigid registration methods: demons and a hierarchical algorithm. Tests on 102 CT-scans of 13 patients demonstrated that the segmentation accuracy significantly increased by including the bladder volume predicted with a simple 1D model based on a manually defined bladder top. Moreover, manually identified implanted fiducial markers significantly improved the accuracy of the SD method. For patients with large cervix-uterus volume regression, the use of CT-data acquired toward the end of the treatment was required to improve segmentation accuracy. Including prior knowledge, the segmentation results of SD (Dice similarity coefficient 85 ± 6%, error margin 2.2 ± 2.3 mm, average time around 1 min) and of ABAS using hierarchical non-rigid registration (Dice 82 ± 10%, error margin 3.1 ± 2.3 mm, average time around 30 s) support their use for image guided online adaptive radiotherapy of cervical cancer.

  6. METROLOGICAL PERFORMANCE OF SEM 3D TECHNIQUES

    DEFF Research Database (Denmark)

    Marinello, Francesco; Carmignato, Simone; Savio, Enrico;

    2008-01-01

    This paper addresses the metrological performance of three-dimensional measurements performed with Scanning Electron Microscopes (SEMs) using reconstruction of surface topography through stereo-photogrammetry. Reconstruction is based on the model function introduced by Piazzesi adapted for eucent...... condition are studied, in order to define a strategy to optimise the measurements taking account of the critical factors in SEM 3D reconstruction. Investigations were performed on a novel sample, specifically developed and implemented for the tests....

  7. Improvement of 3D Scanner

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The disadvantage remaining in 3D scanning system and its reasons are discussed. A new host-and-slave structure with high speed image acquisition and processing system is proposed to quicken the image processing and improve the performance of 3D scanning system.

  8. 3D Printing for Bricks

    OpenAIRE

    ECT Team, Purdue

    2015-01-01

    Building Bytes, by Brian Peters, is a project that uses desktop 3D printers to print bricks for architecture. Instead of using an expensive custom-made printer, it uses a normal standard 3D printer which is available for everyone and makes it more accessible and also easier for fabrication.

  9. Skin Color Segmentation in YCBCR Color Space with Adaptive Fuzzy Neural Network (Anfis

    Directory of Open Access Journals (Sweden)

    Mohammad Saber Iraji

    2012-05-01

    Full Text Available In this paper, an efficient and accurate method for human color skin recognition in color images with different light intensity will proposed .first we transform inputted color image from RGB color space to YCBCR color space and then accurate and appropriate decision on that if it is in human color skin or not will be adopted according to YCBCR color space using fuzzy, adaptive fuzzy neural network(anfis methods for each pixel of that image. In our proposed system adaptive fuzzy neural network(anfis has less error and system worked more accurate and appropriative than prior methods.

  10. Evaluation of the Segmentation by Multispectral Fusion Approach with Adaptive Operators : Application to Medical Images

    Directory of Open Access Journals (Sweden)

    Lamiche Chaabane

    2011-09-01

    Full Text Available With the development of acquisition image techniques, more and more image data from different sources of image become available. Multi-modality image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single modality. In medical imaging based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents the evaluation of the segmentation of MR images using the multispectral fusion approach in the possibility theory context . Some results are presented and discussed.

  11. A specification of 3D manipulation in virtual environments

    Science.gov (United States)

    Su, S. Augustine; Furuta, Richard

    1994-01-01

    In this paper we discuss the modeling of three basic kinds of 3-D manipulations in the context of a logical hand device and our virtual panel architecture. The logical hand device is a useful software abstraction representing hands in virtual environments. The virtual panel architecture is the 3-D component of the 2-D window systems. Both of the abstractions are intended to form the foundation for adaptable 3-D manipulation.

  12. 3D printing in dentistry.

    Science.gov (United States)

    Dawood, A; Marti Marti, B; Sauret-Jackson, V; Darwood, A

    2015-12-01

    3D printing has been hailed as a disruptive technology which will change manufacturing. Used in aerospace, defence, art and design, 3D printing is becoming a subject of great interest in surgery. The technology has a particular resonance with dentistry, and with advances in 3D imaging and modelling technologies such as cone beam computed tomography and intraoral scanning, and with the relatively long history of the use of CAD CAM technologies in dentistry, it will become of increasing importance. Uses of 3D printing include the production of drill guides for dental implants, the production of physical models for prosthodontics, orthodontics and surgery, the manufacture of dental, craniomaxillofacial and orthopaedic implants, and the fabrication of copings and frameworks for implant and dental restorations. This paper reviews the types of 3D printing technologies available and their various applications in dentistry and in maxillofacial surgery. PMID:26657435

  13. 3D printing in dentistry.

    Science.gov (United States)

    Dawood, A; Marti Marti, B; Sauret-Jackson, V; Darwood, A

    2015-12-01

    3D printing has been hailed as a disruptive technology which will change manufacturing. Used in aerospace, defence, art and design, 3D printing is becoming a subject of great interest in surgery. The technology has a particular resonance with dentistry, and with advances in 3D imaging and modelling technologies such as cone beam computed tomography and intraoral scanning, and with the relatively long history of the use of CAD CAM technologies in dentistry, it will become of increasing importance. Uses of 3D printing include the production of drill guides for dental implants, the production of physical models for prosthodontics, orthodontics and surgery, the manufacture of dental, craniomaxillofacial and orthopaedic implants, and the fabrication of copings and frameworks for implant and dental restorations. This paper reviews the types of 3D printing technologies available and their various applications in dentistry and in maxillofacial surgery.

  14. PLOT3D user's manual

    Science.gov (United States)

    Walatka, Pamela P.; Buning, Pieter G.; Pierce, Larry; Elson, Patricia A.

    1990-01-01

    PLOT3D is a computer graphics program designed to visualize the grids and solutions of computational fluid dynamics. Seventy-four functions are available. Versions are available for many systems. PLOT3D can handle multiple grids with a million or more grid points, and can produce varieties of model renderings, such as wireframe or flat shaded. Output from PLOT3D can be used in animation programs. The first part of this manual is a tutorial that takes the reader, keystroke by keystroke, through a PLOT3D session. The second part of the manual contains reference chapters, including the helpfile, data file formats, advice on changing PLOT3D, and sample command files.

  15. 3-D Video Processing for 3-D TV

    Science.gov (United States)

    Sohn, Kwanghoon; Kim, Hansung; Kim, Yongtae

    One of the most desirable ways of realizing high quality information and telecommunication services has been called "The Sensation of Reality," which can be achieved by visual communication based on 3-D (Three-dimensional) images. These kinds of 3-D imaging systems have revealed potential applications in the fields of education, entertainment, medical surgery, video conferencing, etc. Especially, three-dimensional television (3-D TV) is believed to be the next generation of TV technology. Figure 13.1 shows how TV's display technologies have evolved , and Fig. 13.2 details the evolution of TV broadcasting as forecasted by the ETRI (Electronics and Telecommunications Research Institute). It is clear that 3-D TV broadcasting will be the next development in this field, and realistic broadcasting will soon follow.

  16. ADT-3D Tumor Detection Assistant in 3D

    Directory of Open Access Journals (Sweden)

    Jaime Lazcano Bello

    2008-12-01

    Full Text Available The present document describes ADT-3D (Three-Dimensional Tumor Detector Assistant, a prototype application developed to assist doctors diagnose, detect and locate tumors in the brain by using CT scan. The reader may find on this document an introduction to tumor detection; ADT-3D main goals; development details; description of the product; motivation for its development; result’s study; and areas of applicability.

  17. Unassisted 3D camera calibration

    Science.gov (United States)

    Atanassov, Kalin; Ramachandra, Vikas; Nash, James; Goma, Sergio R.

    2012-03-01

    With the rapid growth of 3D technology, 3D image capture has become a critical part of the 3D feature set on mobile phones. 3D image quality is affected by the scene geometry as well as on-the-device processing. An automatic 3D system usually assumes known camera poses accomplished by factory calibration using a special chart. In real life settings, pose parameters estimated by factory calibration can be negatively impacted by movements of the lens barrel due to shaking, focusing, or camera drop. If any of these factors displaces the optical axes of either or both cameras, vertical disparity might exceed the maximum tolerable margin and the 3D user may experience eye strain or headaches. To make 3D capture more practical, one needs to consider unassisted (on arbitrary scenes) calibration. In this paper, we propose an algorithm that relies on detection and matching of keypoints between left and right images. Frames containing erroneous matches, along with frames with insufficiently rich keypoint constellations, are detected and discarded. Roll, pitch yaw , and scale differences between left and right frames are then estimated. The algorithm performance is evaluated in terms of the remaining vertical disparity as compared to the maximum tolerable vertical disparity.

  18. Hand Gesture Spotting Based on 3D Dynamic Features Using Hidden Markov Models

    Science.gov (United States)

    Elmezain, Mahmoud; Al-Hamadi, Ayoub; Michaelis, Bernd

    In this paper, we propose an automatic system that handles hand gesture spotting and recognition simultaneously in stereo color image sequences without any time delay based on Hidden Markov Models (HMMs). Color and 3D depth map are used to segment hand regions. The hand trajectory will determine in further step using Mean-shift algorithm and Kalman filter to generate 3D dynamic features. Furthermore, k-means clustering algorithm is employed for the HMMs codewords. To spot meaningful gestures accurately, a non-gesture model is proposed, which provides confidence limit for the calculated likelihood by other gesture models. The confidence measures are used as an adaptive threshold for spotting meaningful gestures. Experimental results show that the proposed system can successfully recognize isolated gestures with 98.33% and meaningful gestures with 94.35% reliability for numbers (0-9).

  19. Handbook of 3D integration

    CERN Document Server

    Garrou , Philip; Ramm , Peter

    2014-01-01

    Edited by key figures in 3D integration and written by top authors from high-tech companies and renowned research institutions, this book covers the intricate details of 3D process technology.As such, the main focus is on silicon via formation, bonding and debonding, thinning, via reveal and backside processing, both from a technological and a materials science perspective. The last part of the book is concerned with assessing and enhancing the reliability of the 3D integrated devices, which is a prerequisite for the large-scale implementation of this emerging technology. Invaluable reading fo

  20. Tuotekehitysprojekti: 3D-tulostin

    OpenAIRE

    Pihlajamäki, Janne

    2011-01-01

    Opinnäytetyössä tutustuttiin 3D-tulostamisen teknologiaan. Työssä käytiin läpi 3D-tulostimesta tehty tuotekehitysprojekti. Sen lisäksi esiteltiin yleisellä tasolla tuotekehitysprosessi ja syntyneiden tulosten mahdollisia suojausmenetelmiä. Tavoitteena tässä työssä oli kehittää markkinoilta jo löytyvää kotitulostin-tasoista 3D-laiteteknologiaa lähemmäksi ammattilaistason ratkaisua. Tavoitteeseen pyrittiin keskittymällä parantamaan laitteella saavutettavaa tulostustarkkuutta ja -nopeutt...

  1. 3D on the internet

    OpenAIRE

    Puntar, Matej

    2012-01-01

    The purpose of this thesis is the presentation of already established and new technologies of displaying 3D content in a web browser. The thesis begins with a short presentation of the history of 3D content available on the internet and its development together with advantages and disadvantages of individual technologies. The latter two are described in detail as well is their use and the differences among them. Special emphasis has been given to WebGL, the newest technology of 3D conte...

  2. Color 3D Reverse Engineering

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    This paper presents a principle and a method of col or 3D laser scanning measurement. Based on the fundamental monochrome 3D measureme nt study, color information capture, color texture mapping, coordinate computati on and other techniques are performed to achieve color 3D measurement. The syste m is designed and composed of a line laser light emitter, one color CCD camera, a motor-driven rotary filter, a circuit card and a computer. Two steps in captu ring object's images in the measurement process: Firs...

  3. Exploration of 3D Printing

    OpenAIRE

    Lin, Zeyu

    2014-01-01

    3D printing technology is introduced and defined in this Thesis. Some methods of 3D printing are illustrated and their principles are explained with pictures. Most of the essential parts are presented with pictures and their effects are explained within the whole system. Problems on Up! Plus 3D printer are solved and a DIY product is made with this machine. The processes of making product are recorded and the items which need to be noticed during the process are the highlight in this th...

  4. 3D scanning and 3D printing as innovative technologies for fabricating personalized topical drug delivery systems.

    Science.gov (United States)

    Goyanes, Alvaro; Det-Amornrat, Usanee; Wang, Jie; Basit, Abdul W; Gaisford, Simon

    2016-07-28

    Acne is a multifactorial inflammatory skin disease with high prevalence. In this work, the potential of 3D printing to produce flexible personalised-shape anti-acne drug (salicylic acid) loaded devices was demonstrated by two different 3D printing (3DP) technologies: Fused Deposition Modelling (FDM) and stereolithography (SLA). 3D scanning technology was used to obtain a 3D model of a nose adapted to the morphology of an individual. In FDM 3DP, commercially produced Flex EcoPLA™ (FPLA) and polycaprolactone (PCL) filaments were loaded with salicylic acid by hot melt extrusion (HME) (theoretical drug loading - 2% w/w) and used as feedstock material for 3D printing. Drug loading in the FPLA-salicylic acid and PCL-salicylic acid 3D printed patches was 0.4% w/w and 1.2% w/w respectively, indicating significant thermal degradation of drug during HME and 3D printing. Diffusion testing in Franz cells using a synthetic membrane revealed that the drug loaded printed samples released 3D printing technology to manufacture anti-acne devices with salicylic acid. The combination of 3D scanning and 3D printing has the potential to offer solutions to produce personalised drug loaded devices, adapted in shape and size to individual patients.

  5. 3D Road Scene Interpretation for Autonomous Vehicle Driving

    OpenAIRE

    Foresti, Gian Luca; Regazzoni, Carlo

    1999-01-01

    In this paper, the problem of 3D road scene interpretation for autonomous vehicle driving is addressed. In particular, the problems of road detection and obstacle avoidance in outdoor environments are investigated. A set of descriptive primitives (straight and circular line segments) is selected to describe 3D objects which commonly occur in road scenes, e.g., people, cars, trucks, houses, etc. First, these primitives are extracted directly from the input image of the scene, and then are grou...

  6. Materialedreven 3d digital formgivning

    DEFF Research Database (Denmark)

    Hansen, Flemming Tvede

    2010-01-01

    traditionel keramisk produktionssammenhæng. Problemstillingen opmuntrede endvidere til i et samarbejde med en programmør at udvikle et 3d digitalt redskab, der er blevet kaldt et digitalt interaktivt formgivningsredskab (DIF). Eksperimentet undersøger interaktive 3d digitale dynamiske systemer, der...... samarbejder med designere fra fagområder som interaktionsdesign og programmering. Afhandlingen peger på et fremtidigt forskningsfelt indenfor generative og responderende digitale systemer til 3d formgivning, der ligeledes inkluderer følesansen. Endvidere er det relevant at forske i, hvordan de RP teknikker...... formgivning og Rapid Prototyping (RP). RP er en fællesbetegnelse for en række af de teknikker, der muliggør at overføre den digitale form til 3d fysisk form. Forskningsprojektet koncentrerer sig om to overordnede forskningsspørgsmål. Det første handler om, hvordan viden og erfaring indenfor det keramiske...

  7. 3D Face Apperance Model

    DEFF Research Database (Denmark)

    Lading, Brian; Larsen, Rasmus; Astrom, K

    2006-01-01

    We build a 3D face shape model, including inter- and intra-shape variations, derive the analytical Jacobian of its resulting 2D rendered image, and show example of its fitting performance with light, pose, id, expression and texture variations......We build a 3D face shape model, including inter- and intra-shape variations, derive the analytical Jacobian of its resulting 2D rendered image, and show example of its fitting performance with light, pose, id, expression and texture variations...

  8. Main: TATCCAYMOTIFOSRAMY3D [PLACE

    Lifescience Database Archive (English)

    Full Text Available TATCCAYMOTIFOSRAMY3D S000256 01-August-2006 (last modified) kehi TATCCAY motif foun...d in rice (O.s.) RAmy3D alpha-amylase gene promoter; Y=T/C; a GATA motif as its antisense sequence; TATCCAY ...motif and G motif (see S000130) are responsible for sugar repression (Toyofuku et al. 1998); GATA; amylase; sugar; repression; rice (Oryza sativa) TATCCAY ...

  9. Combinatorial 3D Mechanical Metamaterials

    Science.gov (United States)

    Coulais, Corentin; Teomy, Eial; de Reus, Koen; Shokef, Yair; van Hecke, Martin

    2015-03-01

    We present a class of elastic structures which exhibit 3D-folding motion. Our structures consist of cubic lattices of anisotropic unit cells that can be tiled in a complex combinatorial fashion. We design and 3d-print this complex ordered mechanism, in which we combine elastic hinges and defects to tailor the mechanics of the material. Finally, we use this large design space to encode smart functionalities such as surface patterning and multistability.

  10. AI 3D Cybug Gaming

    CERN Document Server

    Ahmed, Zeeshan

    2010-01-01

    In this short paper I briefly discuss 3D war Game based on artificial intelligence concepts called AI WAR. Going in to the details, I present the importance of CAICL language and how this language is used in AI WAR. Moreover I also present a designed and implemented 3D War Cybug for AI WAR using CAICL and discus the implemented strategy to defeat its enemies during the game life.

  11. 3D Face Appearance Model

    DEFF Research Database (Denmark)

    Lading, Brian; Larsen, Rasmus; Åström, Kalle

    2006-01-01

    We build a 3d face shape model, including inter- and intra-shape variations, derive the analytical jacobian of its resulting 2d rendered image, and show example of its fitting performance with light, pose, id, expression and texture variations.}......We build a 3d face shape model, including inter- and intra-shape variations, derive the analytical jacobian of its resulting 2d rendered image, and show example of its fitting performance with light, pose, id, expression and texture variations.}...

  12. In vivo validation of cardiac output assessment in non-standard 3D echocardiographic images

    Science.gov (United States)

    Nillesen, M. M.; Lopata, R. G. P.; de Boode, W. P.; Gerrits, I. H.; Huisman, H. J.; Thijssen, J. M.; Kapusta, L.; de Korte, C. L.

    2009-04-01

    Automatic segmentation of the endocardial surface in three-dimensional (3D) echocardiographic images is an important tool to assess left ventricular (LV) geometry and cardiac output (CO). The presence of speckle noise as well as the nonisotropic characteristics of the myocardium impose strong demands on the segmentation algorithm. In the analysis of normal heart geometries of standardized (apical) views, it is advantageous to incorporate a priori knowledge about the shape and appearance of the heart. In contrast, when analyzing abnormal heart geometries, for example in children with congenital malformations, this a priori knowledge about the shape and anatomy of the LV might induce erroneous segmentation results. This study describes a fully automated segmentation method for the analysis of non-standard echocardiographic images, without making strong assumptions on the shape and appearance of the heart. The method was validated in vivo in a piglet model. Real-time 3D echocardiographic image sequences of five piglets were acquired in radiofrequency (rf) format. These ECG-gated full volume images were acquired intra-operatively in a non-standard view. Cardiac blood flow was measured simultaneously by an ultrasound transit time flow probe positioned around the common pulmonary artery. Three-dimensional adaptive filtering using the characteristics of speckle was performed on the demodulated rf data to reduce the influence of speckle noise and to optimize the distinction between blood and myocardium. A gradient-based 3D deformable simplex mesh was then used to segment the endocardial surface. A gradient and a speed force were included as external forces of the model. To balance data fitting and mesh regularity, one fixed set of weighting parameters of internal, gradient and speed forces was used for all data sets. End-diastolic and end-systolic volumes were computed from the segmented endocardial surface. The cardiac output derived from this automatic segmentation was

  13. In vivo validation of cardiac output assessment in non-standard 3D echocardiographic images

    Energy Technology Data Exchange (ETDEWEB)

    Nillesen, M M; Lopata, R G P; Gerrits, I H; Thijssen, J M; De Korte, C L [Clinical Physics Laboratory-833, Department of Pediatrics, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); De Boode, W P [Neonatology, Department of Pediatrics, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); Huisman, H J [Department of Radiology, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); Kapusta, L [Pediatric Cardiology, Department of Pediatrics, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands)], E-mail: m.m.nillesen@cukz.umcn.nl

    2009-04-07

    Automatic segmentation of the endocardial surface in three-dimensional (3D) echocardiographic images is an important tool to assess left ventricular (LV) geometry and cardiac output (CO). The presence of speckle noise as well as the nonisotropic characteristics of the myocardium impose strong demands on the segmentation algorithm. In the analysis of normal heart geometries of standardized (apical) views, it is advantageous to incorporate a priori knowledge about the shape and appearance of the heart. In contrast, when analyzing abnormal heart geometries, for example in children with congenital malformations, this a priori knowledge about the shape and anatomy of the LV might induce erroneous segmentation results. This study describes a fully automated segmentation method for the analysis of non-standard echocardiographic images, without making strong assumptions on the shape and appearance of the heart. The method was validated in vivo in a piglet model. Real-time 3D echocardiographic image sequences of five piglets were acquired in radiofrequency (rf) format. These ECG-gated full volume images were acquired intra-operatively in a non-standard view. Cardiac blood flow was measured simultaneously by an ultrasound transit time flow probe positioned around the common pulmonary artery. Three-dimensional adaptive filtering using the characteristics of speckle was performed on the demodulated rf data to reduce the influence of speckle noise and to optimize the distinction between blood and myocardium. A gradient-based 3D deformable simplex mesh was then used to segment the endocardial surface. A gradient and a speed force were included as external forces of the model. To balance data fitting and mesh regularity, one fixed set of weighting parameters of internal, gradient and speed forces was used for all data sets. End-diastolic and end-systolic volumes were computed from the segmented endocardial surface. The cardiac output derived from this automatic segmentation was

  14. 3-D model-based vehicle tracking.

    Science.gov (United States)

    Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

    2005-10-01

    This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter. PMID:16238061

  15. Global minimization of adaptive local image fitting energy for image segmentation

    Institute of Scientific and Technical Information of China (English)

    Guoqi Liu; Zhiheng Zhou; Shengli Xie

    2014-01-01

    The active contour model based on local image fitting (LIF) energy is an effective method to deal with intensity inhomo-geneities, but it always conflicts with the local minimum problem because LIF has a nonconvex energy function form. At the same time, the parameters of LIF are hard to be chosen for better per-formance. A global minimization of the adaptive LIF energy model is proposed. The regularized length term which constrains the zero level set is introduced to improve the accuracy of the bound-aries, and a global minimization of the active contour model is presented. In addition, based on the statistical information of the intensity histogram, the standard deviation σ with respect to the truncated Gaussian window is automatical y computed accord-ing to images. Consequently, the proposed method improves the performance and adaptivity to deal with the intensity inhomo-geneities. Experimental results for synthetic and real images show desirable performance and efficiency of the proposed method.

  16. Cyto-3D-print to attach mitotic cells.

    Science.gov (United States)

    Castroagudin, Michelle R; Zhai, Yujia; Li, Zhi; Marnell, Michael G; Glavy, Joseph S

    2016-08-01

    The Cyto-3D-print is an adapter that adds cytospin capability to a standard centrifuge. Like standard cytospinning, Cyto-3D-print increases the surface attachment of mitotic cells while giving a higher degree of adaptability to other slide chambers than available commercial devices. The use of Cyto-3D-print is cost effective, safe, and applicable to many slide designs. It is durable enough for repeated use and made of biodegradable materials for environment-friendly disposal. PMID:26464272

  17. Development of 3D statistical mandible models for cephalometric measurements

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sung Goo; Yi, Won Jin; Hwang, Soon Jung; Choi, Soon Chul; Lee, Sam Sun; Heo, Min Suk; Huh, Kyung Hoe; Kim, Tae Il [School of Dentistry, Seoul National University, Seoul (Korea, Republic of); Hong, Helen; Yoo, Ji Hyun [Division of Multimedia Engineering, Seoul Women' s University, Seoul (Korea, Republic of)

    2012-09-15

    The aim of this study was to provide sex-matched three-dimensional (3D) statistical shape models of the mandible, which would provide cephalometric parameters for 3D treatment planning and cephalometric measurements in orthognathic surgery. The subjects used to create the 3D shape models of the mandible included 23 males and 23 females. The mandibles were segmented semi-automatically from 3D facial CT images. Each individual mandible shape was reconstructed as a 3D surface model, which was parameterized to establish correspondence between different individual surfaces. The principal component analysis (PCA) applied to all mandible shapes produced a mean model and characteristic models of variation. The cephalometric parameters were measured directly from the mean models to evaluate the 3D shape models. The means of the measured parameters were compared with those from other conventional studies. The male and female 3D statistical mean models were developed from 23 individual mandibles, respectively. The male and female characteristic shapes of variation produced by PCA showed a large variability included in the individual mandibles. The cephalometric measurements from the developed models were very close to those from some conventional studies. We described the construction of 3D mandibular shape models and presented the application of the 3D mandibular template in cephalometric measurements. Optimal reference models determined from variations produced by PCA could be used for craniofacial patients with various types of skeletal shape.

  18. MPML3D: Scripting Agents for the 3D Internet.

    Science.gov (United States)

    Prendinger, Helmut; Ullrich, Sebastian; Nakasone, Arturo; Ishizuka, Mitsuru

    2011-05-01

    The aim of this paper is two-fold. First, it describes a scripting language for specifying communicative behavior and interaction of computer-controlled agents ("bots") in the popular three-dimensional (3D) multiuser online world of "Second Life" and the emerging "OpenSimulator" project. While tools for designing avatars and in-world objects in Second Life exist, technology for nonprogrammer content creators of scenarios involving scripted agents is currently missing. Therefore, we have implemented new client software that controls bots based on the Multimodal Presentation Markup Language 3D (MPML3D), a highly expressive XML-based scripting language for controlling the verbal and nonverbal behavior of interacting animated agents. Second, the paper compares Second Life and OpenSimulator platforms and discusses the merits and limitations of each from the perspective of agent control. Here, we also conducted a small study that compares the network performance of both platforms.

  19. Neural Network Based 3D Surface Reconstruction

    Directory of Open Access Journals (Sweden)

    Vincy Joseph

    2009-11-01

    Full Text Available This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D surface reconstruction model. The neural network combines the diffuse and specular components into a hybrid model. The proposed model considers the characteristics of each point and the variant albedo to prevent the reconstructed surface from being distorted. The neural network inputs are the pixel values of the two-dimensional images to be reconstructed. The normal vectors of the surface can then be obtained from the output of the neural network after supervised learning, where the illuminant direction does not have to be known in advance. Finally, the obtained normal vectors can be applied to integration method when reconstructing 3-D objects. Facial images were used for training in the proposed approach

  20. From 3D view to 3D print

    Science.gov (United States)

    Dima, M.; Farisato, G.; Bergomi, M.; Viotto, V.; Magrin, D.; Greggio, D.; Farinato, J.; Marafatto, L.; Ragazzoni, R.; Piazza, D.

    2014-08-01

    In the last few years 3D printing is getting more and more popular and used in many fields going from manufacturing to industrial design, architecture, medical support and aerospace. 3D printing is an evolution of bi-dimensional printing, which allows to obtain a solid object from a 3D model, realized with a 3D modelling software. The final product is obtained using an additive process, in which successive layers of material are laid down one over the other. A 3D printer allows to realize, in a simple way, very complex shapes, which would be quite difficult to be produced with dedicated conventional facilities. Thanks to the fact that the 3D printing is obtained superposing one layer to the others, it doesn't need any particular work flow and it is sufficient to simply draw the model and send it to print. Many different kinds of 3D printers exist based on the technology and material used for layer deposition. A common material used by the toner is ABS plastics, which is a light and rigid thermoplastic polymer, whose peculiar mechanical properties make it diffusely used in several fields, like pipes production and cars interiors manufacturing. I used this technology to create a 1:1 scale model of the telescope which is the hardware core of the space small mission CHEOPS (CHaracterising ExOPlanets Satellite) by ESA, which aims to characterize EXOplanets via transits observations. The telescope has a Ritchey-Chrétien configuration with a 30cm aperture and the launch is foreseen in 2017. In this paper, I present the different phases for the realization of such a model, focusing onto pros and cons of this kind of technology. For example, because of the finite printable volume (10×10×12 inches in the x, y and z directions respectively), it has been necessary to split the largest parts of the instrument in smaller components to be then reassembled and post-processed. A further issue is the resolution of the printed material, which is expressed in terms of layers

  1. 3D scanning and 3D printing as innovative technologies for fabricating personalized topical drug delivery systems.

    Science.gov (United States)

    Goyanes, Alvaro; Det-Amornrat, Usanee; Wang, Jie; Basit, Abdul W; Gaisford, Simon

    2016-07-28

    Acne is a multifactorial inflammatory skin disease with high prevalence. In this work, the potential of 3D printing to produce flexible personalised-shape anti-acne drug (salicylic acid) loaded devices was demonstrated by two different 3D printing (3DP) technologies: Fused Deposition Modelling (FDM) and stereolithography (SLA). 3D scanning technology was used to obtain a 3D model of a nose adapted to the morphology of an individual. In FDM 3DP, commercially produced Flex EcoPLA™ (FPLA) and polycaprolactone (PCL) filaments were loaded with salicylic acid by hot melt extrusion (HME) (theoretical drug loading - 2% w/w) and used as feedstock material for 3D printing. Drug loading in the FPLA-salicylic acid and PCL-salicylic acid 3D printed patches was 0.4% w/w and 1.2% w/w respectively, indicating significant thermal degradation of drug during HME and 3D printing. Diffusion testing in Franz cells using a synthetic membrane revealed that the drug loaded printed samples released manufacture anti-acne devices with salicylic acid. The combination of 3D scanning and 3D printing has the potential to offer solutions to produce personalised drug loaded devices, adapted in shape and size to individual patients. PMID:27189134

  2. The EISCAT_3D Science Case

    Science.gov (United States)

    Tjulin, A.; Mann, I.; McCrea, I.; Aikio, A. T.

    2013-05-01

    projection in the high-latitude ionosphere. EISCAT_3D can also be used to study solar system properties. Thanks to the high power and great accuracy, mapping of objects like the Moon and asteroids is possible. With the high power and large antenna aperture, incoherent scatter radars can be extraordinarily good monitors of extraterrestrial dust and its interaction with the atmosphere. Although incoherent scatter radars, such as EISCAT_3D, are few in number, the power and versatility of their measurement technique mean that they can measure parameters which are not obtainable otherwise, and thus also be a cornerstone in the international efforts to measure and predict space weather effects. Finally, over the years the EISCAT radars have served as a testbed for new ideas in radar coding and data analysis. EISCAT_3D will be the first of a new generation of "software radars" whose advanced capabilities will be realised not by its hardware but by the flexibility and adaptability of the scheduling, beam-forming, signal processing and analysis software used to control the radar and process its data. Thus, new techniques will be developed into standard observing applications for implementation in the next generation of software radars.

  3. Remote 3D Medical Consultation

    Science.gov (United States)

    Welch, Greg; Sonnenwald, Diane H.; Fuchs, Henry; Cairns, Bruce; Mayer-Patel, Ketan; Yang, Ruigang; State, Andrei; Towles, Herman; Ilie, Adrian; Krishnan, Srinivas; Söderholm, Hanna M.

    Two-dimensional (2D) video-based telemedical consultation has been explored widely in the past 15-20 years. Two issues that seem to arise in most relevant case studies are the difficulty associated with obtaining the desired 2D camera views, and poor depth perception. To address these problems we are exploring the use of a small array of cameras to synthesize a spatially continuous range of dynamic three-dimensional (3D) views of a remote environment and events. The 3D views can be sent across wired or wireless networks to remote viewers with fixed displays or mobile devices such as a personal digital assistant (PDA). The viewpoints could be specified manually or automatically via user head or PDA tracking, giving the remote viewer virtual head- or hand-slaved (PDA-based) remote cameras for mono or stereo viewing. We call this idea remote 3D medical consultation (3DMC). In this article we motivate and explain the vision for 3D medical consultation; we describe the relevant computer vision/graphics, display, and networking research; we present a proof-of-concept prototype system; and we present some early experimental results supporting the general hypothesis that 3D remote medical consultation could offer benefits over conventional 2D televideo.

  4. Octree-based Robust Watermarking for 3D Model

    Directory of Open Access Journals (Sweden)

    Su Cai

    2011-02-01

    Full Text Available Three robust blind watermarking methods of 3D models based on Octree are proposed in this paper: OTC-W, OTP-W and Zero-W. Primary Component Analysis and Octree partition are used on 3D meshes. A scrambled binary image for OTC-W and a scrambled RGB image for OTP-W are separately embedded adaptively into the single child nodes at the bottom level of Octree structure. The watermark can be extracted without the original image and 3D model. Those two methods have high embedding capacity for 3D meshes. Meanwhile, they are robust against geometric transformation (like translation, rotation, uniform scaling and vertex reordering attacks. For Zero-W, higher nodes of Octree are used to construct ‘Zero-watermark’, which can resist simplification, noise and remeshing attacks. All those three methods are fit for 3D point cloud data and arbitrary 3D meshes.Three robust blind watermarking methods of 3D models based on Octree are proposed in this paper: OTC-W, OTP-W and Zero-W. Primary Component Analysis and Octree partition are used on 3D meshes. A scrambled binary image for OTC-W and a scrambled RGB image for OTP-W are separately embedded adaptively into the single child nodes at the bottom level of Octree structure. The watermark can be extracted without the original image and 3D model. Those two methods have high embedding capacity for 3D meshes. Meanwhile, they are robust against geometric transformation (like translation, rotation, uniform scaling and vertex reordering attacks. For Zero-W, higher nodes of Octree are used to construct ‘Zero-watermark’, which can resist simplification, noise and remeshing attacks. All those three methods are fit for 3D point cloud data and arbitrary 3D meshes.

  5. 3D Imager and Method for 3D imaging

    NARCIS (Netherlands)

    Kumar, P.; Staszewski, R.; Charbon, E.

    2013-01-01

    3D imager comprising at least one pixel, each pixel comprising a photodetectorfor detecting photon incidence and a time-to-digital converter system configured for referencing said photon incidence to a reference clock, and further comprising a reference clock generator provided for generating the re

  6. Modification of 3D milling machine to 3D printer

    OpenAIRE

    Halamíček, Lukáš

    2015-01-01

    Tato práce se zabývá přestavbou gravírovací frézky na 3D tiskárnu. V první části se práce zabývá možnými technologiemi 3D tisku a možností jejich využití u přestavby. Dále jsou popsány a vybrány vhodné součásti pro přestavbu. V další části je realizováno řízení ohřevu podložky, trysky a řízení posuvu drátu pomocí softwaru TwinCat od společnosti Beckhoff na průmyslovém počítači. Výsledkem práce by měla být oživená 3D tiskárna. This thesis deals with rebuilding of engraving machine to 3D pri...

  7. Markerless 3D Face Tracking

    DEFF Research Database (Denmark)

    Walder, Christian; Breidt, Martin; Bulthoff, Heinrich;

    2009-01-01

    We present a novel algorithm for the markerless tracking of deforming surfaces such as faces. We acquire a sequence of 3D scans along with color images at 40Hz. The data is then represented by implicit surface and color functions, using a novel partition-of-unity type method of efficiently...... combining local regressors using nearest neighbor searches. Both these functions act on the 4D space of 3D plus time, and use temporal information to handle the noise in individual scans. After interactive registration of a template mesh to the first frame, it is then automatically deformed to track...... the scanned surface, using the variation of both shape and color as features in a dynamic energy minimization problem. Our prototype system yields high-quality animated 3D models in correspondence, at a rate of approximately twenty seconds per timestep. Tracking results for faces and other objects...

  8. Crowded Field 3D Spectroscopy

    CERN Document Server

    Becker, T; Roth, M M; Becker, Thomas; Fabrika, Sergei; Roth, Martin M.

    2003-01-01

    The quantitative spectroscopy of stellar objects in complex environments is mainly limited by the ability of separating the object from the background. Standard slit spectroscopy, restricting the field of view to one dimension, is obviously not the proper technique in general. The emerging Integral Field (3D) technique with spatially resolved spectra of a two-dimensional field of view provides a great potential for applying advanced subtraction methods. In this paper an image reconstruction algorithm to separate point sources and a smooth background is applied to 3D data. Several performance tests demonstrate the photometric quality of the method. The algorithm is applied to real 3D observations of a sample Planetary Nebula in M31, whose spectrum is contaminated by the bright and complex galaxy background. The ability of separating sources is also studied in a crowded stellar field in M33.

  9. 3D-grafiikkamoottori mobiililaitteille

    OpenAIRE

    Vahlman, Lauri

    2014-01-01

    Tässä insinöörityössä käydään läpi mobiililaitteille suunnatun yksinkertaisen 3D-grafiikkamoottorin suunnittelu ja toteutus käyttäen OpenGL ES -rajapintaa. Työssä esitellään grafiikkamoottorin toteutuksessa käytettyjä tekniikoita sekä tutustutaan moottorin rakenteeseen ja toteutuksellisiin yksityiskohtiin. Työn alkupuolella tutustutaan myös modernin 3D-grafiikan yleisiin periaatteisiin ja toimintaan sekä käydään läpi 3D-grafiikkaan liittyviä suorituskykyongelmia. Työn loppupuolella esitel...

  10. 3D vector flow imaging

    DEFF Research Database (Denmark)

    Pihl, Michael Johannes

    The main purpose of this PhD project is to develop an ultrasonic method for 3D vector flow imaging. The motivation is to advance the field of velocity estimation in ultrasound, which plays an important role in the clinic. The velocity of blood has components in all three spatial dimensions, yet...... conventional methods can estimate only the axial component. Several approaches for 3D vector velocity estimation have been suggested, but none of these methods have so far produced convincing in vivo results nor have they been adopted by commercial manufacturers. The basis for this project is the Transverse...... on the TO fields are suggested. They can be used to optimize the TO method. In the third part, a TO method for 3D vector velocity estimation is proposed. It employs a 2D phased array transducer and decouples the velocity estimation into three velocity components, which are estimated simultaneously based on 5...

  11. Microfluidic 3D Helix Mixers

    Directory of Open Access Journals (Sweden)

    Georgette B. Salieb-Beugelaar

    2016-10-01

    Full Text Available Polymeric microfluidic systems are well suited for miniaturized devices with complex functionality, and rapid prototyping methods for 3D microfluidic structures are increasingly used. Mixing at the microscale and performing chemical reactions at the microscale are important applications of such systems and we therefore explored feasibility, mixing characteristics and the ability to control a chemical reaction in helical 3D channels produced by the emerging thread template method. Mixing at the microscale is challenging because channel size reduction for improving solute diffusion comes at the price of a reduced Reynolds number that induces a strictly laminar flow regime and abolishes turbulence that would be desired for improved mixing. Microfluidic 3D helix mixers were rapidly prototyped in polydimethylsiloxane (PDMS using low-surface energy polymeric threads, twisted to form 2-channel and 3-channel helices. Structure and flow characteristics were assessed experimentally by microscopy, hydraulic measurements and chromogenic reaction, and were modeled by computational fluid dynamics. We found that helical 3D microfluidic systems produced by thread templating allow rapid prototyping, can be used for mixing and for controlled chemical reaction with two or three reaction partners at the microscale. Compared to the conventional T-shaped microfluidic system used as a control device, enhanced mixing and faster chemical reaction was found to occur due to the combination of diffusive mixing in small channels and flow folding due to the 3D helix shape. Thus, microfluidic 3D helix mixers can be rapidly prototyped using the thread template method and are an attractive and competitive method for fluid mixing and chemical reactions at the microscale.

  12. Ideal 3D asymmetric concentrator

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Botella, Angel [Departamento Fisica Aplicada a los Recursos Naturales, Universidad Politecnica de Madrid, E.T.S.I. de Montes, Ciudad Universitaria s/n, 28040 Madrid (Spain); Fernandez-Balbuena, Antonio Alvarez; Vazquez, Daniel; Bernabeu, Eusebio [Departamento de Optica, Universidad Complutense de Madrid, Fac. CC. Fisicas, Ciudad Universitaria s/n, 28040 Madrid (Spain)

    2009-01-15

    Nonimaging optics is a field devoted to the design of optical components for applications such as solar concentration or illumination. In this field, many different techniques have been used for producing reflective and refractive optical devices, including reverse engineering techniques. In this paper we apply photometric field theory and elliptic ray bundles method to study 3D asymmetric - without rotational or translational symmetry - concentrators, which can be useful components for nontracking solar applications. We study the one-sheet hyperbolic concentrator and we demonstrate its behaviour as ideal 3D asymmetric concentrator. (author)

  13. Advanced 3-D Ultrasound Imaging

    DEFF Research Database (Denmark)

    Rasmussen, Morten Fischer

    The main purpose of the PhD project was to develop methods that increase the 3-D ultrasound imaging quality available for the medical personnel in the clinic. Acquiring a 3-D volume gives the medical doctor the freedom to investigate the measured anatomy in any slice desirable after the scan has...... beamforming. This is achieved partly because synthetic aperture imaging removes the limitation of a fixed transmit focal depth and instead enables dynamic transmit focusing. Lately, the major ultrasound companies have produced ultrasound scanners using 2-D transducer arrays with enough transducer elements...

  14. 3D modeling of buildings outstanding sites

    CERN Document Server

    Héno, Rapha?le

    2014-01-01

    Conventional topographic databases, obtained by capture on aerial or spatial images provide a simplified 3D modeling of our urban environment, answering the needs of numerous applications (development, risk prevention, mobility management, etc.). However, when we have to represent and analyze more complex sites (monuments, civil engineering works, archeological sites, etc.), these models no longer suffice and other acquisition and processing means have to be implemented. This book focuses on the study of adapted lifting means for "notable buildings". The methods tackled in this book cover las

  15. APPLICATION OF 3D MODELING IN 3D PRINTING FOR THE LOWER JAW RECONSTRUCTION

    Directory of Open Access Journals (Sweden)

    Yu. Yu. Dikov

    2015-01-01

    Full Text Available Aim of study: improvement of functional and aesthetic results of microsurgery reconstructions of the lower jaw due to the use of the methodology of 3D modeling and 3D printing. Application of this methodology has been demonstrated on the example of treatment of 4 patients with locally distributed tumors of the mouth cavity, who underwent excision of the tumor with simultaneous reconstruction of the lower jaw with revascularized fibular graft.Before, one patient has already undergo segmental resection of the lower jaw with the defect replacement with the avascular ileac graft and a reconstruction plate. Then, a relapse of the disease and lysis of the graft has developed with him. Modeling of the graft according to the shape of the lower jaw was performed by making osteotomies of the bone part of the graft using three-dimensional virtual models created by computed tomography data. Then these 3D models were printed with a 3D printer of plastic with the scale of 1:1 with the fused deposition modeling (FDM technology and were used during the surgery in the course of modeling of the graft. Sterilizing of the plastic model was performed in the formalin chamber.This methodology allowed more specific reconstruction of the resected fragment of the lower jaw and get better functional and aesthetic results and prepare patients to further dental rehabilitation. Advantages of this methodology are the possibility of simultaneous performance of stages of reconstruction and resection and shortening of the time of surgery.

  16. PubChem3D: Biologically relevant 3-D similarity

    Directory of Open Access Journals (Sweden)

    Kim Sunghwan

    2011-07-01

    Full Text Available Abstract Background The use of 3-D similarity techniques in the analysis of biological data and virtual screening is pervasive, but what is a biologically meaningful 3-D similarity value? Can one find statistically significant separation between "active/active" and "active/inactive" spaces? These questions are explored using 734,486 biologically tested chemical structures, 1,389 biological assay data sets, and six different 3-D similarity types utilized by PubChem analysis tools. Results The similarity value distributions of 269.7 billion unique conformer pairs from 734,486 biologically tested compounds (all-against-all from PubChem were utilized to help work towards an answer to the question: what is a biologically meaningful 3-D similarity score? The average and standard deviation for the six similarity measures STST-opt, CTST-opt, ComboTST-opt, STCT-opt, CTCT-opt, and ComboTCT-opt were 0.54 ± 0.10, 0.07 ± 0.05, 0.62 ± 0.13, 0.41 ± 0.11, 0.18 ± 0.06, and 0.59 ± 0.14, respectively. Considering that this random distribution of biologically tested compounds was constructed using a single theoretical conformer per compound (the "default" conformer provided by PubChem, further study may be necessary using multiple diverse conformers per compound; however, given the breadth of the compound set, the single conformer per compound results may still apply to the case of multi-conformer per compound 3-D similarity value distributions. As such, this work is a critical step, covering a very wide corpus of chemical structures and biological assays, creating a statistical framework to build upon. The second part of this study explored the question of whether it was possible to realize a statistically meaningful 3-D similarity value separation between reputed biological assay "inactives" and "actives". Using the terminology of noninactive-noninactive (NN pairs and the noninactive-inactive (NI pairs to represent comparison of the "active/active" and

  17. 3D Face Apperance Model

    OpenAIRE

    Lading, Brian; Larsen, Rasmus; Astrom, K

    2006-01-01

    We build a 3D face shape model, including inter- and intra-shape variations, derive the analytical Jacobian of its resulting 2D rendered image, and show example of its fitting performance with light, pose, id, expression and texture variations

  18. 3D Face Appearance Model

    OpenAIRE

    Lading, Brian; Larsen, Rasmus; Åström, Kalle

    2006-01-01

    We build a 3d face shape model, including inter- and intra-shape variations, derive the analytical jacobian of its resulting 2d rendered image, and show example of its fitting performance with light, pose, id, expression and texture variations.}

  19. Making Inexpensive 3-D Models

    Science.gov (United States)

    Manos, Harry

    2016-01-01

    Visual aids are important to student learning, and they help make the teacher's job easier. Keeping with the "TPT" theme of "The Art, Craft, and Science of Physics Teaching," the purpose of this article is to show how teachers, lacking equipment and funds, can construct a durable 3-D model reference frame and a model gravity…

  20. When Art Meets 3D

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The presentation of the vanguard work,My Dream3D,the innovative production by the China Disabled People’s Performing Art Troupe(CDPPAT),directed by Joy Joosang Park,provided the film’s domestic premiere at Beijing’s Olympic Park onApril7.The show provided an intriguing insight not

  1. 3D terahertz beam profiling

    DEFF Research Database (Denmark)

    Pedersen, Pernille Klarskov; Strikwerda, Andrew; Wang, Tianwu;

    2013-01-01

    We present a characterization of THz beams generated in both a two-color air plasma and in a LiNbO3 crystal. Using a commercial THz camera, we record intensity images as a function of distance through the beam waist, from which we extract 2D beam profiles and visualize our measurements into 3D beam...

  2. 3D Printing: Exploring Capabilities

    Science.gov (United States)

    Samuels, Kyle; Flowers, Jim

    2015-01-01

    As 3D printers become more affordable, schools are using them in increasing numbers. They fit well with the emphasis on product design in technology and engineering education, allowing students to create high-fidelity physical models to see and test different iterations in their product designs. They may also help students to "think in three…

  3. Viewing galaxies in 3D

    CERN Document Server

    Krajnović, Davor

    2016-01-01

    Thanks to a technique that reveals galaxies in 3D, astronomers can now show that many galaxies have been wrongly classified. Davor Krajnovi\\'c argues that the classification scheme proposed 85 years ago by Edwin Hubble now needs to be revised.

  4. A Texture Analysis of 3D Radar Images

    NARCIS (Netherlands)

    Deiana, D.; Yarovoy, A.

    2009-01-01

    In this paper a texture feature coding method to be applied to high-resolution 3D radar images in order to improve target detection is developed. An automatic method for image segmentation based on texture features is proposed. The method has been able to automatically detect weak targets which fail

  5. Robust hashing for 3D models

    Science.gov (United States)

    Berchtold, Waldemar; Schäfer, Marcel; Rettig, Michael; Steinebach, Martin

    2014-02-01

    3D models and applications are of utmost interest in both science and industry. With the increment of their usage, their number and thereby the challenge to correctly identify them increases. Content identification is commonly done by cryptographic hashes. However, they fail as a solution in application scenarios such as computer aided design (CAD), scientific visualization or video games, because even the smallest alteration of the 3D model, e.g. conversion or compression operations, massively changes the cryptographic hash as well. Therefore, this work presents a robust hashing algorithm for 3D mesh data. The algorithm applies several different bit extraction methods. They are built to resist desired alterations of the model as well as malicious attacks intending to prevent correct allocation. The different bit extraction methods are tested against each other and, as far as possible, the hashing algorithm is compared to the state of the art. The parameters tested are robustness, security and runtime performance as well as False Acceptance Rate (FAR) and False Rejection Rate (FRR), also the probability calculation of hash collision is included. The introduced hashing algorithm is kept adaptive e.g. in hash length, to serve as a proper tool for all applications in practice.

  6. Designing TSVs for 3D Integrated Circuits

    CERN Document Server

    Khan, Nauman

    2013-01-01

    This book explores the challenges and presents best strategies for designing Through-Silicon Vias (TSVs) for 3D integrated circuits.  It describes a novel technique to mitigate TSV-induced noise, the GND Plug, which is superior to others adapted from 2-D planar technologies, such as a backside ground plane and traditional substrate contacts. The book also investigates, in the form of a comparative study, the impact of TSV size and granularity, spacing of C4 connectors, off-chip power delivery network, shared and dedicated TSVs, and coaxial TSVs on the quality of power delivery in 3-D ICs. The authors provide detailed best design practices for designing 3-D power delivery networks.  Since TSVs occupy silicon real-estate and impact device density, this book provides four iterative algorithms to minimize the number of TSVs in a power delivery network. Unlike other existing methods, these algorithms can be applied in early design stages when only functional block- level behaviors and a floorplan are available....

  7. SynthCam3D: Semantic Understanding With Synthetic Indoor Scenes

    OpenAIRE

    Handa, Ankur; Patraucean, Viorica; Badrinarayanan, Vijay; Stent, Simon; Cipolla, Roberto

    2015-01-01

    We are interested in automatic scene understanding from geometric cues. To this end, we aim to bring semantic segmentation in the loop of real-time reconstruction. Our semantic segmentation is built on a deep autoencoder stack trained exclusively on synthetic depth data generated from our novel 3D scene library, SynthCam3D. Importantly, our network is able to segment real world scenes without any noise modelling. We present encouraging preliminary results.

  8. PLOT3D/AMES, UNIX SUPERCOMPUTER AND SGI IRIS VERSION (WITHOUT TURB3D)

    Science.gov (United States)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  9. PLOT3D/AMES, UNIX SUPERCOMPUTER AND SGI IRIS VERSION (WITH TURB3D)

    Science.gov (United States)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  10. Priprava 3D modelov za 3D tisk

    OpenAIRE

    Pikovnik, Tomaž

    2015-01-01

    Po mnenju nekaterih strokovnjakov bo aditivna proizvodnja (ali 3D tiskanje) spremenila proizvodnjo industrijo, saj si bo vsak posameznik lahko natisnil svoj objekt po želji. V diplomski nalogi so predstavljene nekatere tehnologije aditivne proizvodnje. V nadaljevanju diplomske naloge je predstavljena izdelava makete hiše v merilu 1:100, vse od modeliranja do tiskanja. Poseben poudarek je posvečen predelavi modela, da je primeren za tiskanje, kjer je razvit pristop za hitrejše i...

  11. Post processing of 3D models for 3D printing

    OpenAIRE

    Pikovnik, Tomaž

    2015-01-01

    According to the opinion of some experts the additive manufacturing or 3D printing will change manufacturing industry, because any individual could print their own model according to his or her wishes. In this graduation thesis some of the additive manufacturing technologies are presented. Furthermore in the production of house scale model in 1:100 is presented, starting from modeling to printing. Special attention is given to postprocessing of the building model elements us...

  12. 3D Cameras: 3D Computer Vision of Wide Scope

    OpenAIRE

    May, Stefan; Pervoelz, Kai; Surmann, Hartmut

    2007-01-01

    First of all, a short comparison of range sensors and their underlying principles was given. The chapter further focused on 3D cameras. The latest innovations have given a significant improvement for the measurement accuracy, wherefore this technology has attracted attention in the robotics community. This was also the motivation for the examination in this chapter. On this account, several applications were presented, which represents common problems in the domain of autonomous robotics. For...

  13. DYNA3D2000*, Explicit 3-D Hydrodynamic FEM Program

    International Nuclear Information System (INIS)

    1 - Description of program or function: DYNA3D2000 is a nonlinear explicit finite element code for analyzing 3-D structures and solid continuum. The code is vectorized and available on several computer platforms. The element library includes continuum, shell, beam, truss and spring/damper elements to allow maximum flexibility in modeling physical problems. Many materials are available to represent a wide range of material behavior, including elasticity, plasticity, composites, thermal effects and rate dependence. In addition, DYNA3D has a sophisticated contact interface capability, including frictional sliding, single surface contact and automatic contact generation. 2 - Method of solution: Discretization of a continuous model transforms partial differential equations into algebraic equations. A numerical solution is then obtained by solving these algebraic equations through a direct time marching scheme. 3 - Restrictions on the complexity of the problem: Recent software improvements have eliminated most of the user identified limitations with dynamic memory allocation and a very large format description that has pushed potential problem sizes beyond the reach of most users. The dominant restrictions remain in code execution speed and robustness, which the developers constantly strive to improve

  14. 3D Aware Correction and Completion of Depth Maps in Piecewise Planar Scenes

    KAUST Repository

    Thabet, Ali Kassem

    2015-04-16

    RGB-D sensors are popular in the computer vision community, especially for problems of scene understanding, semantic scene labeling, and segmentation. However, most of these methods depend on reliable input depth measurements, while discarding unreliable ones. This paper studies how reliable depth values can be used to correct the unreliable ones, and how to complete (or extend) the available depth data beyond the raw measurements of the sensor (i.e. infer depth at pixels with unknown depth values), given a prior model on the 3D scene. We consider piecewise planar environments in this paper, since many indoor scenes with man-made objects can be modeled as such. We propose a framework that uses the RGB-D sensor’s noise profile to adaptively and robustly fit plane segments (e.g. floor and ceiling) and iteratively complete the depth map, when possible. Depth completion is formulated as a discrete labeling problem (MRF) with hard constraints and solved efficiently using graph cuts. To regularize this problem, we exploit 3D and appearance cues that encourage pixels to take on depth values that will be compatible in 3D to the piecewise planar assumption. Extensive experiments, on a new large-scale and challenging dataset, show that our approach results in more accurate depth maps (with 20 % more depth values) than those recorded by the RGB-D sensor. Additional experiments on the NYUv2 dataset show that our method generates more 3D aware depth. These generated depth maps can also be used to improve the performance of a state-of-the-art RGB-D SLAM method.

  15. INTERACTIVE 3D LANDSCAPES ON LINE

    Directory of Open Access Journals (Sweden)

    B. Fanini

    2012-09-01

    Full Text Available The paper describes challenges identified while developing browser embedded 3D landscape rendering applications, our current approach and work-flow and how recent development in browser technologies could affect. All the data, even if processed by optimization and decimation tools, result in very huge databases that require paging, streaming and Level-of-Detail techniques to be implemented to allow remote web based real time fruition. Our approach has been to select an open source scene-graph based visual simulation library with sufficient performance and flexibility and adapt it to the web by providing a browser plug-in. Within the current Montegrotto VR Project, content produced with new pipelines has been integrated. The whole Montegrotto Town has been generated procedurally by CityEngine. We used this procedural approach, based on algorithms and procedures because it is particularly functional to create extensive and credible urban reconstructions. To create the archaeological sites we used optimized mesh acquired with laser scanning and photogrammetry techniques whereas to realize the 3D reconstructions of the main historical buildings we adopted computer-graphic software like blender and 3ds Max. At the final stage, semi-automatic tools have been developed and used up to prepare and clusterise 3D models and scene graph routes for web publishing. Vegetation generators have also been used with the goal of populating the virtual scene to enhance the user perceived realism during the navigation experience. After the description of 3D modelling and optimization techniques, the paper will focus and discuss its results and expectations.

  16. Interactive 3d Landscapes on Line

    Science.gov (United States)

    Fanini, B.; Calori, L.; Ferdani, D.; Pescarin, S.

    2011-09-01

    The paper describes challenges identified while developing browser embedded 3D landscape rendering applications, our current approach and work-flow and how recent development in browser technologies could affect. All the data, even if processed by optimization and decimation tools, result in very huge databases that require paging, streaming and Level-of-Detail techniques to be implemented to allow remote web based real time fruition. Our approach has been to select an open source scene-graph based visual simulation library with sufficient performance and flexibility and adapt it to the web by providing a browser plug-in. Within the current Montegrotto VR Project, content produced with new pipelines has been integrated. The whole Montegrotto Town has been generated procedurally by CityEngine. We used this procedural approach, based on algorithms and procedures because it is particularly functional to create extensive and credible urban reconstructions. To create the archaeological sites we used optimized mesh acquired with laser scanning and photogrammetry techniques whereas to realize the 3D reconstructions of the main historical buildings we adopted computer-graphic software like blender and 3ds Max. At the final stage, semi-automatic tools have been developed and used up to prepare and clusterise 3D models and scene graph routes for web publishing. Vegetation generators have also been used with the goal of populating the virtual scene to enhance the user perceived realism during the navigation experience. After the description of 3D modelling and optimization techniques, the paper will focus and discuss its results and expectations.

  17. PLOT3D/AMES, SGI IRIS VERSION (WITH TURB3D)

    Science.gov (United States)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  18. PLOT3D/AMES, SGI IRIS VERSION (WITHOUT TURB3D)

    Science.gov (United States)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  19. PLOT3D- DRAWING THREE DIMENSIONAL SURFACES

    Science.gov (United States)

    Canright, R. B.

    1994-01-01

    PLOT3D is a package of programs to draw three-dimensional surfaces of the form z = f(x,y). The function f and the boundary values for x and y are the input to PLOT3D. The surface thus defined may be drawn after arbitrary rotations. However, it is designed to draw only functions in rectangular coordinates expressed explicitly in the above form. It cannot, for example, draw a sphere. Output is by off-line incremental plotter or online microfilm recorder. This package, unlike other packages, will plot any function of the form z = f(x,y) and portrays continuous and bounded functions of two independent variables. With curve fitting; however, it can draw experimental data and pictures which cannot be expressed in the above form. The method used is division into a uniform rectangular grid of the given x and y ranges. The values of the supplied function at the grid points (x, y) are calculated and stored; this defines the surface. The surface is portrayed by connecting successive (y,z) points with straight-line segments for each x value on the grid and, in turn, connecting successive (x,z) points for each fixed y value on the grid. These lines are then projected by parallel projection onto the fixed yz-plane for plotting. This program has been implemented on the IBM 360/67 with on-line CDC microfilm recorder.

  20. FR3D: finding local and composite recurrent structural motifs in RNA 3D structures.

    Science.gov (United States)

    Sarver, Michael; Zirbel, Craig L; Stombaugh, Jesse; Mokdad, Ali; Leontis, Neocles B

    2008-01-01

    New methods are described for finding recurrent three-dimensional (3D) motifs in RNA atomic-resolution structures. Recurrent RNA 3D motifs are sets of RNA nucleotides with similar spatial arrangements. They can be local or composite. Local motifs comprise nucleotides that occur in the same hairpin or internal loop. Composite motifs comprise nucleotides belonging to three or more different RNA strand segments or molecules. We use a base-centered approach to construct efficient, yet exhaustive search procedures using geometric, symbolic, or mixed representations of RNA structure that we implement in a suite of MATLAB programs, "Find RNA 3D" (FR3D). The first modules of FR3D preprocess structure files to classify base-pair and -stacking interactions. Each base is represented geometrically by the position of its glycosidic nitrogen in 3D space and by the rotation matrix that describes its orientation with respect to a common frame. Base-pairing and base-stacking interactions are calculated from the base geometries and are represented symbolically according to the Leontis/Westhof basepairing classification, extended to include base-stacking. These data are stored and used to organize motif searches. For geometric searches, the user supplies the 3D structure of a query motif which FR3D uses to find and score geometrically similar candidate motifs, without regard to the sequential position of their nucleotides in the RNA chain or the identity of their bases. To score and rank candidate motifs, FR3D calculates a geometric discrepancy by rigidly rotating candidates to align optimally with the query motif and then comparing the relative orientations of the corresponding bases in the query and candidate motifs. Given the growing size of the RNA structure database, it is impossible to explicitly compute the discrepancy for all conceivable candidate motifs, even for motifs with less than ten nucleotides. The screening algorithm that we describe finds all candidate motifs whose

  1. RECONSTRUCTION OF 3D VECTOR MODELS OF BUILDINGS BY COMBINATION OF ALS, TLS AND VLS DATA

    Directory of Open Access Journals (Sweden)

    H. Boulaassal

    2012-09-01

    Full Text Available Airborne Laser Scanning (ALS, Terrestrial Laser Scanning (TLS and Vehicle based Laser Scanning (VLS are widely used as data acquisition methods for 3D building modelling. ALS data is often used to generate, among others, roof models. TLS data has proven its effectiveness in the geometric reconstruction of building façades. Although the operating algorithms used in the processing chain of these two kinds of data are quite similar, their combination should be more investigated. This study explores the possibility of combining ALS and TLS data for simultaneously producing 3D building models from bird point of view and pedestrian point of view. The geometric accuracy of roofs and façades models is different due to the acquisition techniques. In order to take these differences into account, the surfaces composing roofs and façades are extracted with the same algorithm of segmentation. Nevertheless the segmentation algorithm must be adapted to the properties of the different point clouds. It is based on the RANSAC algorithm, but has been applied in a sequential way in order to extract all potential planar clusters from airborne and terrestrial datasets. Surfaces are fitted to planar clusters, allowing edge detection and reconstruction of vector polygons. Models resulting from TLS data are obviously more accurate than those generated from ALS data. Therefore, the geometry of the roofs is corrected and adapted according to the geometry of the corresponding façades. Finally, the effects of the differences between raw ALS and TLS data on the results of the modeling process are analyzed. It is shown that such combination could be used to produce reliable 3D building models.

  2. Quantification of the accuracy of MRI generated 3D models of long bones compared to CT generated 3D models.

    Science.gov (United States)

    Rathnayaka, Kanchana; Momot, Konstantin I; Noser, Hansrudi; Volp, Andrew; Schuetz, Michael A; Sahama, Tony; Schmutz, Beat

    2012-04-01

    Orthopaedic fracture fixation implants are increasingly being designed using accurate 3D models of long bones based on computer tomography (CT). Unlike CT, magnetic resonance imaging (MRI) does not involve ionising radiation and is therefore a desirable alternative to CT. This study aims to quantify the accuracy of MRI-based 3D models compared to CT-based 3D models of long bones. The femora of five intact cadaver ovine limbs were scanned using a 1.5 T MRI and a CT scanner. Image segmentation of CT and MRI data was performed using a multi-threshold segmentation method. Reference models were generated by digitising the bone surfaces free of soft tissue with a mechanical contact scanner. The MRI- and CT-derived models were validated against the reference models. The results demonstrated that the CT-based models contained an average error of 0.15 mm while the MRI-based models contained an average error of 0.23 mm. Statistical validation shows that there are no significant differences between 3D models based on CT and MRI data. These results indicate that the geometric accuracy of MRI based 3D models was comparable to that of CT-based models and therefore MRI is a potential alternative to CT for generation of 3D models with high geometric accuracy.

  3. A low-resolution 3D holographic volumetric display

    Science.gov (United States)

    Khan, Javid; Underwood, Ian; Greenaway, Alan; Halonen, Mikko

    2010-05-01

    A simple low resolution volumetric display is presented, based on holographic volume-segments. The display system comprises a proprietary holographic screen, laser projector, associated optics plus a control unit. The holographic screen resembles a sheet of frosted glass about A4 in size (20x30cm). The holographic screen is rear-illuminated by the laser projector, which is in turn driven by the controller, to produce simple 3D images that appear outside the plane of the screen. A series of spatially multiplexed and interleaved interference patterns are pre-encoded across the surface of the holographic screen. Each illumination pattern is capable of reconstructing a single holographic volume-segment. Up to nine holograms are multiplexed on the holographic screen in a variety of configurations including a series of numeric and segmented digits. The demonstrator has good results under laboratory conditions with moving colour 3D images in front of or behind the holographic screen.

  4. 3DFC: a new container for 3D file formats compositing

    OpenAIRE

    Bouville Berthelot, Rozenn; Royan, Jérôme; Duval, Thierry; Arnaldi, Bruno

    2012-01-01

    International audience; We present a 3D container model that enables the compositing of 3D file formats. It allows not only to compose 3D scenes made of several 3D files of different types but also to combine their functionalities and to make them interact together in the rendering window. This model, calls 3DFC for 3D File Container, relies on the Scene Graph Adapter (SGA) architecture that makes it possible to load any scene-graph-based 3D file format in a 3D application whatever the involv...

  5. 3D Building Reconstruction Using Dense Photogrammetric Point Cloud

    Science.gov (United States)

    Malihi, S.; Valadan Zoej, M. J.; Hahn, M.; Mokhtarzade, M.; Arefi, H.

    2016-06-01

    Three dimensional models of urban areas play an important role in city planning, disaster management, city navigation and other applications. Reconstruction of 3D building models is still a challenging issue in 3D city modelling. Point clouds generated from multi view images of UAV is a novel source of spatial data, which is used in this research for building reconstruction. The process starts with the segmentation of point clouds of roofs and walls into planar groups. By generating related surfaces and using geometrical constraints plus considering symmetry, a 3d model of building is reconstructed. In a refinement step, dormers are extracted, and their models are reconstructed. The details of the 3d reconstructed model are in LoD3 level, with respect to modelling eaves, fractions of roof and dormers.

  6. Highly compressible 3D periodic graphene aerogel microlattices.

    Science.gov (United States)

    Zhu, Cheng; Han, T Yong-Jin; Duoss, Eric B; Golobic, Alexandra M; Kuntz, Joshua D; Spadaccini, Christopher M; Worsley, Marcus A

    2015-04-22

    Graphene is a two-dimensional material that offers a unique combination of low density, exceptional mechanical properties, large surface area and excellent electrical conductivity. Recent progress has produced bulk 3D assemblies of graphene, such as graphene aerogels, but they possess purely stochastic porous networks, which limit their performance compared with the potential of an engineered architecture. Here we report the fabrication of periodic graphene aerogel microlattices, possessing an engineered architecture via a 3D printing technique known as direct ink writing. The 3D printed graphene aerogels are lightweight, highly conductive and exhibit supercompressibility (up to 90% compressive strain). Moreover, the Young's moduli of the 3D printed graphene aerogels show an order of magnitude improvement over bulk graphene materials with comparable geometric density and possess large surface areas. Adapting the 3D printing technique to graphene aerogels realizes the possibility of fabricating a myriad of complex aerogel architectures for a broad range of applications.

  7. Highly compressible 3D periodic graphene aerogel microlattices

    Science.gov (United States)

    Zhu, Cheng; Han, T. Yong-Jin; Duoss, Eric B.; Golobic, Alexandra M.; Kuntz, Joshua D.; Spadaccini, Christopher M.; Worsley, Marcus A.

    2015-01-01

    Graphene is a two-dimensional material that offers a unique combination of low density, exceptional mechanical properties, large surface area and excellent electrical conductivity. Recent progress has produced bulk 3D assemblies of graphene, such as graphene aerogels, but they possess purely stochastic porous networks, which limit their performance compared with the potential of an engineered architecture. Here we report the fabrication of periodic graphene aerogel microlattices, possessing an engineered architecture via a 3D printing technique known as direct ink writing. The 3D printed graphene aerogels are lightweight, highly conductive and exhibit supercompressibility (up to 90% compressive strain). Moreover, the Young's moduli of the 3D printed graphene aerogels show an order of magnitude improvement over bulk graphene materials with comparable geometric density and possess large surface areas. Adapting the 3D printing technique to graphene aerogels realizes the possibility of fabricating a myriad of complex aerogel architectures for a broad range of applications. PMID:25902277

  8. 3D Printable Graphene Composite.

    Science.gov (United States)

    Wei, Xiaojun; Li, Dong; Jiang, Wei; Gu, Zheming; Wang, Xiaojuan; Zhang, Zengxing; Sun, Zhengzong

    2015-07-08

    In human being's history, both the Iron Age and Silicon Age thrived after a matured massive processing technology was developed. Graphene is the most recent superior material which could potentially initialize another new material Age. However, while being exploited to its full extent, conventional processing methods fail to provide a link to today's personalization tide. New technology should be ushered in. Three-dimensional (3D) printing fills the missing linkage between graphene materials and the digital mainstream. Their alliance could generate additional stream to push the graphene revolution into a new phase. Here we demonstrate for the first time, a graphene composite, with a graphene loading up to 5.6 wt%, can be 3D printable into computer-designed models. The composite's linear thermal coefficient is below 75 ppm·°C(-1) from room temperature to its glass transition temperature (Tg), which is crucial to build minute thermal stress during the printing process.

  9. 3-D Relativistic MHD Simulations

    Science.gov (United States)

    Nishikawa, K.-I.; Frank, J.; Koide, S.; Sakai, J.-I.; Christodoulou, D. M.; Sol, H.; Mutel, R. L.

    1998-12-01

    We present 3-D numerical simulations of moderately hot, supersonic jets propagating initially along or obliquely to the field lines of a denser magnetized background medium with Lorentz factors of W = 4.56 and evolving in a four-dimensional spacetime. The new results are understood as follows: Relativistic simulations have consistently shown that these jets are effectively heavy and so they do not suffer substantial momentum losses and are not decelerated as efficiently as their nonrelativistic counterparts. In addition, the ambient magnetic field, however strong, can be pushed aside with relative ease by the beam, provided that the degrees of freedom associated with all three spatial dimensions are followed self-consistently in the simulations. This effect is analogous to pushing Japanese ``noren'' or vertical Venetian blinds out of the way while the slats are allowed to bend in 3-D space rather than as a 2-D slab structure.

  10. 3D Printed Robotic Hand

    Science.gov (United States)

    Pizarro, Yaritzmar Rosario; Schuler, Jason M.; Lippitt, Thomas C.

    2013-01-01

    Dexterous robotic hands are changing the way robots and humans interact and use common tools. Unfortunately, the complexity of the joints and actuations drive up the manufacturing cost. Some cutting edge and commercially available rapid prototyping machines now have the ability to print multiple materials and even combine these materials in the same job. A 3D model of a robotic hand was designed using Creo Parametric 2.0. Combining "hard" and "soft" materials, the model was printed on the Object Connex350 3D printer with the purpose of resembling as much as possible the human appearance and mobility of a real hand while needing no assembly. After printing the prototype, strings where installed as actuators to test mobility. Based on printing materials, the manufacturing cost of the hand was $167, significantly lower than other robotic hands without the actuators since they have more complex assembly processes.

  11. Forensic 3D Scene Reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    LITTLE,CHARLES Q.; PETERS,RALPH R.; RIGDON,J. BRIAN; SMALL,DANIEL E.

    1999-10-12

    Traditionally law enforcement agencies have relied on basic measurement and imaging tools, such as tape measures and cameras, in recording a crime scene. A disadvantage of these methods is that they are slow and cumbersome. The development of a portable system that can rapidly record a crime scene with current camera imaging, 3D geometric surface maps, and contribute quantitative measurements such as accurate relative positioning of crime scene objects, would be an asset to law enforcement agents in collecting and recording significant forensic data. The purpose of this project is to develop a feasible prototype of a fast, accurate, 3D measurement and imaging system that would support law enforcement agents to quickly document and accurately record a crime scene.

  12. 3D Backscatter Imaging System

    Science.gov (United States)

    Turner, D. Clark (Inventor); Whitaker, Ross (Inventor)

    2016-01-01

    Systems and methods for imaging an object using backscattered radiation are described. The imaging system comprises both a radiation source for irradiating an object that is rotationally movable about the object, and a detector for detecting backscattered radiation from the object that can be disposed on substantially the same side of the object as the source and which can be rotationally movable about the object. The detector can be separated into multiple detector segments with each segment having a single line of sight projection through the object and so detects radiation along that line of sight. Thus, each detector segment can isolate the desired component of the backscattered radiation. By moving independently of each other about the object, the source and detector can collect multiple images of the object at different angles of rotation and generate a three dimensional reconstruction of the object. Other embodiments are described.

  13. [Real time 3D echocardiography

    Science.gov (United States)

    Bauer, F.; Shiota, T.; Thomas, J. D.

    2001-01-01

    Three-dimensional representation of the heart is an old concern. Usually, 3D reconstruction of the cardiac mass is made by successive acquisition of 2D sections, the spatial localisation and orientation of which require complex guiding systems. More recently, the concept of volumetric acquisition has been introduced. A matricial emitter-receiver probe complex with parallel data processing provides instantaneous of a pyramidal 64 degrees x 64 degrees volume. The image is restituted in real time and is composed of 3 planes (planes B and C) which can be displaced in all spatial directions at any time during acquisition. The flexibility of this system of acquisition allows volume and mass measurement with greater accuracy and reproducibility, limiting inter-observer variability. Free navigation of the planes of investigation allows reconstruction for qualitative and quantitative analysis of valvular heart disease and other pathologies. Although real time 3D echocardiography is ready for clinical usage, some improvements are still necessary to improve its conviviality. Then real time 3D echocardiography could be the essential tool for understanding, diagnosis and management of patients.

  14. [Real time 3D echocardiography in congenital heart disease].

    Science.gov (United States)

    Acar, P; Dulac, Y; Taktak, A; Villacèque, M

    2004-05-01

    The introduction of the 3D mode in echocardiography has led to its use in everyday clinical practice. One hundred and fifty real time 3D echocardiographic examinations were performed in 20 foetus, 110 children and 20 adults with various congenital heart lesions (shunts, valvular lesions, aortic diseases). The 4x matricial probe enables the instantaneous acquisition of transthoracic volumes. Four modes of 3D imaging were used: real time, total volume, colour Doppler and biplane. Quantitative measurements were performed at an outlying station. The feasibility of the method in the foetus, the child and the adult was respectively 90%, 99% and 85%. Real time 3D echocardiography did not affect the diagnoses made by standard echocardiography. The 3D imaging gave a more accurate description of atrial septal defects and congenital valvular lesions. Biplane imaging was decisive in the quantitative approach to aortic dilatation of Marfan's syndrome and in segmental analysis of the foetal heart. 3D colour Doppler imaging has been disappointing but the possibilities of volumic quantification of blood flow are very promising. The present limitations of the method are the inadequate resolution in the small child and the absence of quantitative measurement on the echograph. The facility of utilisation of the matricial probe should lead to routine usage of 3D echocardiography as with 2D and the Doppler modes. Its value should be decisive in many congenital cardiac lesions requiring surgery or interventional catheterisation. PMID:15214550

  15. 3-D Reconstruction of Medical Image Using Wavelet Transform and Snake Model

    Directory of Open Access Journals (Sweden)

    Jinyong Cheng

    2009-12-01

    Full Text Available Medical image segmentation is an important step in 3-D reconstruction, and 3-D reconstruction from medical images is an important application of computer graphics and biomedicine image processing. An improved image segmentation method which is suitable for 3-D reconstruction is presented in this paper. A 3-D reconstruction algorithm is used to reconstruct the 3-D model from medical images. Rough edge is obtained by multi-scale wavelet transform at first. With the rough edge, improved gradient vector flow snake model is used and the object contour in the image is found. In the experiments, we reconstruct 3-D models of kidney, liver and brain putamen. The performances of the experiments indicate that the new algorithm can produce accurate 3-D reconstruction.

  16. Spectral mesh segmentation

    OpenAIRE

    Liu, Rong

    2009-01-01

    Polygonal meshes are ubiquitous in geometric modeling. They are widely used in many applications, such as computer games, computer-aided design, animation, and visualization. One of the important problems in mesh processing and analysis is segmentation, where the goal is to partition a mesh into segments to suit the particular application at hand. In this thesis we study structural-level mesh segmentation, which seeks to decompose a given 3D shape into parts according to human intuition. We t...

  17. Segmentation of Planar Surfaces from Laser Scanning Data Using the Magnitude of Normal Position Vector for Adaptive Neighborhoods

    OpenAIRE

    Changjae Kim; Ayman Habib; Muwook Pyeon; Goo-rak Kwon; Jaehoon Jung; Joon Heo

    2016-01-01

    Diverse approaches to laser point segmentation have been proposed since the emergence of the laser scanning system. Most of these segmentation techniques, however, suffer from limitations such as sensitivity to the choice of seed points, lack of consideration of the spatial relationships among points, and inefficient performance. In an effort to overcome these drawbacks, this paper proposes a segmentation methodology that: (1) reduces the dimensions of the attribute space; (2) considers the a...

  18. Joint Rendering and Segmentation of Free-Viewpoint Video

    Directory of Open Access Journals (Sweden)

    Ishii Masato

    2010-01-01

    Full Text Available Abstract This paper presents a method that jointly performs synthesis and object segmentation of free-viewpoint video using multiview video as the input. This method is designed to achieve robust segmentation from online video input without per-frame user interaction and precomputations. This method shares a calculation process between the synthesis and segmentation steps; the matching costs calculated through the synthesis step are adaptively fused with other cues depending on the reliability in the segmentation step. Since the segmentation is performed for arbitrary viewpoints directly, the extracted object can be superimposed onto another 3D scene with geometric consistency. We can observe that the object and new background move naturally along with the viewpoint change as if they existed together in the same space. In the experiments, our method can process online video input captured by a 25-camera array and show the result image at 4.55 fps.

  19. Wireless 3D Chocolate Printer

    Directory of Open Access Journals (Sweden)

    FROILAN G. DESTREZA

    2014-02-01

    Full Text Available This study is for the BSHRM Students of Batangas State University (BatStateU ARASOF for the researchers believe that the Wireless 3D Chocolate Printer would be helpful in their degree program especially on making creative, artistic, personalized and decorative chocolate designs. The researchers used the Prototyping model as procedural method for the successful development and implementation of the hardware and software. This method has five phases which are the following: quick plan, quick design, prototype construction, delivery and feedback and communication. This study was evaluated by the BSHRM Students and the assessment of the respondents regarding the software and hardware application are all excellent in terms of Accuracy, Effecitveness, Efficiency, Maintainability, Reliability and User-friendliness. Also, the overall level of acceptability of the design project as evaluated by the respondents is excellent. With regard to the observation about the best raw material to use in 3D printing, the chocolate is good to use as the printed material is slightly distorted,durable and very easy to prepare; the icing is also good to use as the printed material is not distorted and is very durable but consumes time to prepare; the flour is not good as the printed material is distorted, not durable but it is easy to prepare. The computation of the economic viability level of 3d printer with reference to ROI is 37.14%. The recommendation of the researchers in the design project are as follows: adding a cooling system so that the raw material will be more durable, development of a more simplified version and improving the extrusion process wherein the user do not need to stop the printing process just to replace the empty syringe with a new one.

  20. INGRID, 3-D Mesh Generator for Program DYNA3D and NIKE3D and FACET and TOPAZ3D

    International Nuclear Information System (INIS)

    1 - Description of program or function: INGRID is a general-purpose, three-dimensional mesh generator developed for use with finite element, nonlinear, structural dynamics codes. INGRID generates the large and complex input data files for DYNA3D (NESC 9909), NIKE3D (NESC 9725), FACET, and TOPAZ3D. One of the greatest advantages of INGRID is that virtually any shape can be described without resorting to wedge elements, tetrahedrons, triangular elements or highly distorted quadrilateral or hexahedral elements. Other capabilities available are in the areas of geometry and graphics. Exact surface equations and surface intersections considerably improve the ability to deal with accurate models, and a hidden line graphics algorithm is included which is efficient on the most complicated meshes. The most important new capability is associated with the boundary conditions, loads, and material properties required by nonlinear mechanics programs. Commands have been designed for each case to minimize user effort. This is particularly important since special processing is almost always required for each load or boundary condition. 2 - Method of solution: Geometries are described primarily using the index space notation of the INGEN program (NESC 975) with an additional type of notation, index progression. Index progressions provide a concise and simple method for describing complex structures; the concept was developed to facilitate defining multiple regions in index space. Rather than specifying the minimum and maximum indices for a region, one specifies the progression of indices along the I, J and K directions, respectively. The index progression method allows the analyst to describe most geometries including nodes and elements with roughly the same amount of input as a solids modeler