3D prostate TRUS segmentation using globally optimized volume-preserving prior.

Science.gov (United States)

Qiu, Wu; Rajchl, Martin; Guo, Fumin; Sun, Yue; Ukwatta, Eranga; Fenster, Aaron; Yuan, Jing

2014-01-01

An efficient and accurate segmentation of 3D transrectal ultrasound (TRUS) images plays an important role in the planning and treatment of the practical 3D TRUS guided prostate biopsy. However, a meaningful segmentation of 3D TRUS images tends to suffer from US speckles, shadowing and missing edges etc, which make it a challenging task to delineate the correct prostate boundaries. In this paper, we propose a novel convex optimization based approach to extracting the prostate surface from the given 3D TRUS image, while preserving a new global volume-size prior. We, especially, study the proposed combinatorial optimization problem by convex relaxation and introduce its dual continuous max-flow formulation with the new bounded flow conservation constraint, which results in an efficient numerical solver implemented on GPUs. Experimental results using 12 patient 3D TRUS images show that the proposed approach while preserving the volume-size prior yielded a mean DSC of 89.5% +/- 2.4%, a MAD of 1.4 +/- 0.6 mm, a MAXD of 5.2 +/- 3.2 mm, and a VD of 7.5% +/- 6.2% in - 1 minute, deomonstrating the advantages of both accuracy and efficiency. In addition, the low standard deviation of the segmentation accuracy shows a good reliability of the proposed approach.

3D Building Models Segmentation Based on K-Means++ Cluster Analysis

Science.gov (United States)

Zhang, C.; Mao, B.

2016-10-01

3D mesh model segmentation is drawing increasing attentions from digital geometry processing field in recent years. The original 3D mesh model need to be divided into separate meaningful parts or surface patches based on certain standards to support reconstruction, compressing, texture mapping, model retrieval and etc. Therefore, segmentation is a key problem for 3D mesh model segmentation. In this paper, we propose a method to segment Collada (a type of mesh model) 3D building models into meaningful parts using cluster analysis. Common clustering methods segment 3D mesh models by K-means, whose performance heavily depends on randomized initial seed points (i.e., centroid) and different randomized centroid can get quite different results. Therefore, we improved the existing method and used K-means++ clustering algorithm to solve this problem. Our experiments show that K-means++ improves both the speed and the accuracy of K-means, and achieve good and meaningful results.

3D BUILDING MODELS SEGMENTATION BASED ON K-MEANS++ CLUSTER ANALYSIS

Directory of Open Access Journals (Sweden)

C. Zhang

2016-10-01

Full Text Available 3D mesh model segmentation is drawing increasing attentions from digital geometry processing field in recent years. The original 3D mesh model need to be divided into separate meaningful parts or surface patches based on certain standards to support reconstruction, compressing, texture mapping, model retrieval and etc. Therefore, segmentation is a key problem for 3D mesh model segmentation. In this paper, we propose a method to segment Collada (a type of mesh model 3D building models into meaningful parts using cluster analysis. Common clustering methods segment 3D mesh models by K-means, whose performance heavily depends on randomized initial seed points (i.e., centroid and different randomized centroid can get quite different results. Therefore, we improved the existing method and used K-means++ clustering algorithm to solve this problem. Our experiments show that K-means++ improves both the speed and the accuracy of K-means, and achieve good and meaningful results.

Interactive 3D segmentation using connected orthogonal contours

NARCIS (Netherlands)

de Bruin, P. W.; Dercksen, V. J.; Post, F. H.; Vossepoel, A. M.; Streekstra, G. J.; Vos, F. M.

2005-01-01

This paper describes a new method for interactive segmentation that is based on cross-sectional design and 3D modelling. The method represents a 3D model by a set of connected contours that are planar and orthogonal. Planar contours overlayed on image data are easily manipulated and linked contours

QED in d=3 from the epsilon-expansion.

CERN Multimedia

CERN. Geneva

2015-01-01

In my talk, based on the recent work 1508.06278, I will consider the Renormalization Group flow of Quantum Electrodynamics in d=3 coupled to N_f flavors of fermions. For N_f smaller than a critical value N_f^c, chiral symmetry breaking is believed to take place. For N_f > N_f^c, the theory flows to an interacting fixed point that can be studied in the epsilon-expansion, using the fixed point in d=4-2\\epsilon. I will discuss the computation of the anomalous dimensions of fermion bilinears and quadrilinear operators, as well as some more conceptual aspects concerning the enhancement of global symmetries in d=3. For small N_f, a quadrilinear operator can become relevant in the IR and destabilize the fixed point. Therefore, the epsilon-expansion can be used to estimate N_f^c.

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

International Nuclear Information System (INIS)

Iturrondobeitia, M.; Okariz, A.; Fernandez-Martinez, R.; Jimbert, P.; Guraya, T.; Ibarretxe, J.

2015-01-01

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 clay (%) and the actual one. The method is first validated using a fictitious set of objects, and then applied on a nanocomposite

Anisotropic Diffusion based Brain MRI Segmentation and 3D Reconstruction

Directory of Open Access Journals (Sweden)

M. Arfan Jaffar

2012-06-01

Full Text Available In medical field visualization of the organs is very imperative for accurate diagnosis and treatment of any disease. Brain tumor diagnosis and surgery also required impressive 3D visualization of the brain to the radiologist. Detection and 3D reconstruction of brain tumors from MRI is a computationally time consuming and error-prone task. Proposed system detects and presents a 3D visualization model of the brain and tumor inside which greatly helps the radiologist to effectively diagnose and analyze the brain tumor. We proposed a multi-phase segmentation and visualization technique which overcomes the many problems of 3D volume segmentation methods like lake of fine details. In this system segmentation is done in three different phases which reduces the error chances. The system finds contours for skull, brain and tumor. These contours are stacked over and two novel methods are used to find the 3D visualization models. The results of these techniques, particularly of interpolation based, are impressive. Proposed system is tested against publically available data set [41] and MRI datasets available from MRI aamp; CT center Rawalpindi, Pakistan [42].

3D-SIFT-Flow for atlas-based CT liver image segmentation.

Science.gov (United States)

Xu, Yan; Xu, Chenchao; Kuang, Xiao; Wang, Hongkai; Chang, Eric I-Chao; Huang, Weimin; Fan, Yubo

2016-05-01

In this paper, the authors proposed a new 3D registration algorithm, 3D-scale invariant feature transform (SIFT)-Flow, for multiatlas-based liver segmentation in computed tomography (CT) images. In the registration work, the authors developed a new registration method that takes advantage of dense correspondence using the informative and robust SIFT feature. The authors computed the dense SIFT features for the source image and the target image and designed an objective function to obtain the correspondence between these two images. Labeling of the source image was then mapped to the target image according to the former correspondence, resulting in accurate segmentation. In the fusion work, the 2D-based nonparametric label transfer method was extended to 3D for fusing the registered 3D atlases. Compared with existing registration algorithms, 3D-SIFT-Flow has its particular advantage in matching anatomical structures (such as the liver) that observe large variation/deformation. The authors observed consistent improvement over widely adopted state-of-the-art registration methods such as ELASTIX, ANTS, and multiatlas fusion methods such as joint label fusion. Experimental results of liver segmentation on the MICCAI 2007 Grand Challenge are encouraging, e.g., Dice overlap ratio 96.27% ± 0.96% by our method compared with the previous state-of-the-art result of 94.90% ± 2.86%. Experimental results show that 3D-SIFT-Flow is robust for segmenting the liver from CT images, which has large tissue deformation and blurry boundary, and 3D label transfer is effective and efficient for improving the registration accuracy.

Dual optimization based prostate zonal segmentation in 3D MR images.

Science.gov (United States)

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2014-05-01

Efficient and accurate segmentation of the prostate and two of its clinically meaningful sub-regions: the central gland (CG) and peripheral zone (PZ), from 3D MR images, is of great interest in image-guided prostate interventions and diagnosis of prostate cancer. In this work, a novel multi-region segmentation approach is proposed to simultaneously segment the prostate and its two major sub-regions from only a single 3D T2-weighted (T2w) MR image, which makes use of the prior spatial region consistency and incorporates a customized prostate appearance model into the segmentation task. The formulated challenging combinatorial optimization problem is solved by means of convex relaxation, for which a novel spatially continuous max-flow model is introduced as the dual optimization formulation to the studied convex relaxed optimization problem with region consistency constraints. The proposed continuous max-flow model derives an efficient duality-based algorithm that enjoys numerical advantages and can be easily implemented on GPUs. The proposed approach was validated using 18 3D prostate T2w MR images with a body-coil and 25 images with an endo-rectal coil. Experimental results demonstrate that the proposed method is capable of efficiently and accurately extracting both the prostate zones: CG and PZ, and the whole prostate gland from the input 3D prostate MR images, with a mean Dice similarity coefficient (DSC) of 89.3±3.2% for the whole gland (WG), 82.2±3.0% for the CG, and 69.1±6.9% for the PZ in 3D body-coil MR images; 89.2±3.3% for the WG, 83.0±2.4% for the CG, and 70.0±6.5% for the PZ in 3D endo-rectal coil MR images. In addition, the experiments of intra- and inter-observer variability introduced by user initialization indicate a good reproducibility of the proposed approach in terms of volume difference (VD) and coefficient-of-variation (CV) of DSC. Copyright © 2014 Elsevier B.V. All rights reserved.

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

OpenAIRE

Shuo-Tsung Chen; Tzung-Dau Wang; Wen-Jeng Lee; Tsai-Wei Huang; Pei-Kai Hung; Cheng-Yu Wei; Chung-Ming Chen; Woon-Man Kung

2015-01-01

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 c...

3D-SIFT-Flow for atlas-based CT liver image segmentation

Energy Technology Data Exchange (ETDEWEB)

Xu, Yan, E-mail: xuyan04@gmail.com [State Key Laboratory of Software Development Environment and Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beihang University, Beijing 100191, China and Research Institute of Beihang University in Shenzhen and Microsoft Research, Beijing 100080 (China); Xu, Chenchao, E-mail: chenchaoxu33@gmail.com; Kuang, Xiao, E-mail: kuangxiao.ace@gmail.com [School of Biological Science and Medical Engineering, Beihang University, Beijing 100191 (China); Wang, Hongkai, E-mail: wang.hongkai@gmail.com [Department of Biomedical Engineering, Dalian University of Technology, Dalian 116024 (China); Chang, Eric I-Chao, E-mail: eric.chang@microsoft.com [Microsoft Research, Beijing 100080 (China); Huang, Weimin, E-mail: wmhuang@i2r.a-star.edu.sg [Institute for Infocomm Research (I2R), Singapore 138632 (Singapore); Fan, Yubo, E-mail: yubofan@buaa.edu.cn [Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beihang University, Beijing 100191 (China)

2016-05-15

Purpose: In this paper, the authors proposed a new 3D registration algorithm, 3D-scale invariant feature transform (SIFT)-Flow, for multiatlas-based liver segmentation in computed tomography (CT) images. Methods: In the registration work, the authors developed a new registration method that takes advantage of dense correspondence using the informative and robust SIFT feature. The authors computed the dense SIFT features for the source image and the target image and designed an objective function to obtain the correspondence between these two images. Labeling of the source image was then mapped to the target image according to the former correspondence, resulting in accurate segmentation. In the fusion work, the 2D-based nonparametric label transfer method was extended to 3D for fusing the registered 3D atlases. Results: Compared with existing registration algorithms, 3D-SIFT-Flow has its particular advantage in matching anatomical structures (such as the liver) that observe large variation/deformation. The authors observed consistent improvement over widely adopted state-of-the-art registration methods such as ELASTIX, ANTS, and multiatlas fusion methods such as joint label fusion. Experimental results of liver segmentation on the MICCAI 2007 Grand Challenge are encouraging, e.g., Dice overlap ratio 96.27% ± 0.96% by our method compared with the previous state-of-the-art result of 94.90% ± 2.86%. Conclusions: Experimental results show that 3D-SIFT-Flow is robust for segmenting the liver from CT images, which has large tissue deformation and blurry boundary, and 3D label transfer is effective and efficient for improving the registration accuracy.

3D-SIFT-Flow for atlas-based CT liver image segmentation

International Nuclear Information System (INIS)

Xu, Yan; Xu, Chenchao; Kuang, Xiao; Wang, Hongkai; Chang, Eric I-Chao; Huang, Weimin; Fan, Yubo

2016-01-01

Purpose: In this paper, the authors proposed a new 3D registration algorithm, 3D-scale invariant feature transform (SIFT)-Flow, for multiatlas-based liver segmentation in computed tomography (CT) images. Methods: In the registration work, the authors developed a new registration method that takes advantage of dense correspondence using the informative and robust SIFT feature. The authors computed the dense SIFT features for the source image and the target image and designed an objective function to obtain the correspondence between these two images. Labeling of the source image was then mapped to the target image according to the former correspondence, resulting in accurate segmentation. In the fusion work, the 2D-based nonparametric label transfer method was extended to 3D for fusing the registered 3D atlases. Results: Compared with existing registration algorithms, 3D-SIFT-Flow has its particular advantage in matching anatomical structures (such as the liver) that observe large variation/deformation. The authors observed consistent improvement over widely adopted state-of-the-art registration methods such as ELASTIX, ANTS, and multiatlas fusion methods such as joint label fusion. Experimental results of liver segmentation on the MICCAI 2007 Grand Challenge are encouraging, e.g., Dice overlap ratio 96.27% ± 0.96% by our method compared with the previous state-of-the-art result of 94.90% ± 2.86%. Conclusions: Experimental results show that 3D-SIFT-Flow is robust for segmenting the liver from CT images, which has large tissue deformation and blurry boundary, and 3D label transfer is effective and efficient for improving the registration accuracy.

Fast Segmentation From Blurred Data in 3D Fluorescence Microscopy.

Science.gov (United States)

Storath, Martin; Rickert, Dennis; Unser, Michael; Weinmann, Andreas

2017-10-01

We develop a fast algorithm for segmenting 3D images from linear measurements based on the Potts model (or piecewise constant Mumford-Shah model). To that end, we first derive suitable space discretizations of the 3D Potts model, which are capable of dealing with 3D images defined on non-cubic grids. Our discretization allows us to utilize a specific splitting approach, which results in decoupled subproblems of moderate size. The crucial point in the 3D setup is that the number of independent subproblems is so large that we can reasonably exploit the parallel processing capabilities of the graphics processing units (GPUs). Our GPU implementation is up to 18 times faster than the sequential CPU version. This allows to process even large volumes in acceptable runtimes. As a further contribution, we extend the algorithm in order to deal with non-negativity constraints. We demonstrate the efficiency of our method for combined image deconvolution and segmentation on simulated data and on real 3D wide field fluorescence microscopy data.

3D segmentation of scintigraphic images with validation on realistic GATE simulations

International Nuclear Information System (INIS)

Burg, Samuel

2011-01-01

The objective of this thesis was to propose a new 3D segmentation method for scintigraphic imaging. The first part of the work was to simulate 3D volumes with known ground truth in order to validate a segmentation method over other. Monte-Carlo simulations were performed using the GATE software (Geant4 Application for Emission Tomography). For this, we characterized and modeled the gamma camera 'γ Imager' Biospace"T"M by comparing each measurement from a simulated acquisition to his real equivalent. The 'low level' segmentation tool that we have developed is based on a modeling of the levels of the image by probabilistic mixtures. Parameters estimation is done by an SEM algorithm (Stochastic Expectation Maximization). The 3D volume segmentation is achieved by an ICM algorithm (Iterative Conditional Mode). We compared the segmentation based on Gaussian and Poisson mixtures to segmentation by thresholding on the simulated volumes. This showed the relevance of the segmentations obtained using probabilistic mixtures, especially those obtained with Poisson mixtures. Those one has been used to segment real "1"8FDG PET images of the brain and to compute descriptive statistics of the different tissues. In order to obtain a 'high level' segmentation method and find anatomical structures (necrotic part or active part of a tumor, for example), we proposed a process based on the point processes formalism. A feasibility study has yielded very encouraging results. (author) [fr

Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: A grand challenge.

Science.gov (United States)

Zheng, Guoyan; Chu, Chengwen; Belavý, Daniel L; Ibragimov, Bulat; Korez, Robert; Vrtovec, Tomaž; Hutt, Hugo; Everson, Richard; Meakin, Judith; Andrade, Isabel Lŏpez; Glocker, Ben; Chen, Hao; Dou, Qi; Heng, Pheng-Ann; Wang, Chunliang; Forsberg, Daniel; Neubert, Aleš; Fripp, Jurgen; Urschler, Martin; Stern, Darko; Wimmer, Maria; Novikov, Alexey A; Cheng, Hui; Armbrecht, Gabriele; Felsenberg, Dieter; Li, Shuo

2017-01-01

The evaluation of changes in Intervertebral Discs (IVDs) with 3D Magnetic Resonance (MR) Imaging (MRI) can be of interest for many clinical applications. This paper presents the evaluation of both IVD localization and IVD segmentation methods submitted to the Automatic 3D MRI IVD Localization and Segmentation challenge, held at the 2015 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2015) with an on-site competition. With the construction of a manually annotated reference data set composed of 25 3D T2-weighted MR images acquired from two different studies and the establishment of a standard validation framework, quantitative evaluation was performed to compare the results of methods submitted to the challenge. Experimental results show that overall the best localization method achieves a mean localization distance of 0.8 mm and the best segmentation method achieves a mean Dice of 91.8%, a mean average absolute distance of 1.1 mm and a mean Hausdorff distance of 4.3 mm, respectively. The strengths and drawbacks of each method are discussed, which provides insights into the performance of different IVD localization and segmentation methods. Copyright © 2016 Elsevier B.V. All rights reserved.

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

DEFF Research Database (Denmark)

Jørgensen, Peter Stanley; Bowen, Jacob R.

2008-01-01

Routine use of 3D characterization of SOFCs by focused ion beam (FIB) serial sectioning is generally restricted by the time consuming task of manually delineating structures within each image slice. We apply advanced image analysis algorithms to automatically segment the porosity phase of an SOFC...... 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...... reveals and good correspondence and the two approaches are quantitatively compared. It is concluded that the. automatic approach is more robust, more reproduceable and orders of magnitude quicker than manual segmentation of SOFC anode porosity for subsequent quantitative 3D analysis. Lastly...

FROM2D to 3d Supervised Segmentation and Classification for Cultural Heritage Applications

Science.gov (United States)

Grilli, E.; Dininno, D.; Petrucci, G.; Remondino, F.

2018-05-01

The digital management of architectural heritage information is still a complex problem, as a heritage object requires an integrated representation of various types of information in order to develop appropriate restoration or conservation strategies. Currently, there is extensive research focused on automatic procedures of segmentation and classification of 3D point clouds or meshes, which can accelerate the study of a monument and integrate it with heterogeneous information and attributes, useful to characterize and describe the surveyed object. The aim of this study is to propose an optimal, repeatable and reliable procedure to manage various types of 3D surveying data and associate them with heterogeneous information and attributes to characterize and describe the surveyed object. In particular, this paper presents an approach for classifying 3D heritage models, starting from the segmentation of their textures based on supervised machine learning methods. Experimental results run on three different case studies demonstrate that the proposed approach is effective and with many further potentials.

Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images

Science.gov (United States)

Zhou, Xiangrong; Yamada, Kazuma; Kojima, Takuya; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi

2018-02-01

The purpose of this study is to evaluate and compare the performance of modern deep learning techniques for automatically recognizing and segmenting multiple organ regions on 3D CT images. CT image segmentation is one of the important task in medical image analysis and is still very challenging. Deep learning approaches have demonstrated the capability of scene recognition and semantic segmentation on nature images and have been used to address segmentation problems of medical images. Although several works showed promising results of CT image segmentation by using deep learning approaches, there is no comprehensive evaluation of segmentation performance of the deep learning on segmenting multiple organs on different portions of CT scans. In this paper, we evaluated and compared the segmentation performance of two different deep learning approaches that used 2D- and 3D deep convolutional neural networks (CNN) without- and with a pre-processing step. A conventional approach that presents the state-of-the-art performance of CT image segmentation without deep learning was also used for comparison. A dataset that includes 240 CT images scanned on different portions of human bodies was used for performance evaluation. The maximum number of 17 types of organ regions in each CT scan were segmented automatically and compared to the human annotations by using ratio of intersection over union (IU) as the criterion. The experimental results demonstrated the IUs of the segmentation results had a mean value of 79% and 67% by averaging 17 types of organs that segmented by a 3D- and 2D deep CNN, respectively. All the results of the deep learning approaches showed a better accuracy and robustness than the conventional segmentation method that used probabilistic atlas and graph-cut methods. The effectiveness and the usefulness of deep learning approaches were demonstrated for solving multiple organs segmentation problem on 3D CT images.

Super-Segments Based Classification of 3D Urban Street Scenes

Directory of Open Access Journals (Sweden)

Yu Zhou

2012-12-01

Full Text Available We address the problem of classifying 3D point clouds: given 3D urban street scenes gathered by a lidar sensor, we wish to assign a class label to every point. This work is a key step toward realizing applications in robots and cars, for example. In this paper, we present a novel approach to the classification of 3D urban scenes based on super-segments, which are generated from point clouds by two stages of segmentation: a clustering stage and a grouping stage. Then, six effective normal and dimension features that vary with object class are extracted at the super-segment level for training some general classifiers. We evaluate our method both quantitatively and qualitatively using the challenging Velodyne lidar data set. The results show that by only using normal and dimension features we can achieve better recognition than can be achieved with high-dimensional shape descriptors. We also evaluate the adopting of the MRF framework in our approach, but the experimental results indicate that thisbarely improved the accuracy of the classified results due to the sparse property of the super-segments.

Point Cluster Analysis Using a 3D Voronoi Diagram with Applications in Point Cloud Segmentation

Directory of Open Access Journals (Sweden)

Shen Ying

2015-08-01

Full Text Available Three-dimensional (3D point analysis and visualization is one of the most effective methods of point cluster detection and segmentation in geospatial datasets. However, serious scattering and clotting characteristics interfere with the visual detection of 3D point clusters. To overcome this problem, this study proposes the use of 3D Voronoi diagrams to analyze and visualize 3D points instead of the original data item. The proposed algorithm computes the cluster of 3D points by applying a set of 3D Voronoi cells to describe and quantify 3D points. The decompositions of point cloud of 3D models are guided by the 3D Voronoi cell parameters. The parameter values are mapped from the Voronoi cells to 3D points to show the spatial pattern and relationships; thus, a 3D point cluster pattern can be highlighted and easily recognized. To capture different cluster patterns, continuous progressive clusters and segmentations are tested. The 3D spatial relationship is shown to facilitate cluster detection. Furthermore, the generated segmentations of real 3D data cases are exploited to demonstrate the feasibility of our approach in detecting different spatial clusters for continuous point cloud segmentation.

Segmentation process significantly influences the accuracy of 3D surface models derived from cone beam computed tomography

International Nuclear Information System (INIS)

Fourie, Zacharias; Damstra, Janalt; Schepers, Rutger H.; Gerrits, Peter O.; Ren Yijin

2012-01-01

Aims: To assess the accuracy of surface models derived from 3D cone beam computed tomography (CBCT) with two different segmentation protocols. Materials and methods: Seven fresh-frozen cadaver heads were used. There was no conflict of interests in this study. CBCT scans were made of the heads and 3D surface models were created of the mandible using two different segmentation protocols. The one series of 3D models was segmented by a commercial software company, while the other series was done by an experienced 3D clinician. The heads were then macerated following a standard process. A high resolution laser surface scanner was used to make a 3D model of the macerated mandibles, which acted as the reference 3D model or “gold standard”. The 3D models generated from the two rendering protocols were compared with the “gold standard” using a point-based rigid registration algorithm to superimpose the three 3D models. The linear difference at 25 anatomic and cephalometric landmarks between the laser surface scan and the 3D models generate from the two rendering protocols was measured repeatedly in two sessions with one week interval. Results: The agreement between the repeated measurement was excellent (ICC = 0.923–1.000). The mean deviation from the gold standard by the 3D models generated from the CS group was 0.330 mm ± 0.427, while the mean deviation from the Clinician's rendering was 0.763 mm ± 0.392. The surface models segmented by both CS and DS protocols tend to be larger than those of the reference models. In the DS group, the biggest mean differences with the LSS models were found at the points ConLatR (CI: 0.83–1.23), ConMedR (CI: −3.16 to 2.25), CoLatL (CI: −0.68 to 2.23), Spine (CI: 1.19–2.28), ConAntL (CI: 0.84–1.69), ConSupR (CI: −1.12 to 1.47) and RetMolR (CI: 0.84–1.80). Conclusion: The Commercially segmented models resembled the reality more closely than the Doctor's segmented models. If 3D models are needed for surgical drilling

Impacts of Built-Up Area Expansion in 2D and 3D on Regional Surface Temperature

Directory of Open Access Journals (Sweden)

Hongyan Cai

2017-10-01

Full Text Available Many studies have reported the thermal effects of urban expansion from non-built-up land; however, how changes in building height in built-up land influence the regional thermal environment is still uncertain. Thus, taking the transitional region between the Chinese megacities of Beijing and Tianjin as the study area, this study investigated the impacts of built-up land expansion in 2D and 3D on regional land surface temperature (LST. The expansion in 2D refers to the conversion from non-built-up land to built-up land, whereas the expansion in 3D characterized the building height change in the built-up land, referring to the conversion from low- and moderate-rise building (LMRB to high-rise building (HRB lands. The land use change from 2010 to 2015 was manually interpreted from high spatial resolution SPOT5 and Gaofen2 images, and the LST information in the corresponding period was derived from Landsat5/8 thermal images using an image-based method. The results showed that between 2010 and 2015, approximately 87.25 km2 non-built-up land was transformed to built-up land, and 13.21 km2 LMRB land was built into HRB land. These two types of built-up land expansions have induced opposing thermal effects in regard to regional surface temperature. The built-up land expansions from cropland and urban green land have raised the regional LST. However, the built-up land expansion from LMRB to HRB lands has induced a cooling effect. Thus, this study suggested that for the cooling urban design, the building height should also be considered. Furthermore, for future studies on thermal impacts of urbanization, it should be cautioned that, besides the urban area expansion, the building height change should also be emphasized due to its potential cooling effects.

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. Copyright © 2012 Elsevier B.V. All rights reserved.

Deformable M-Reps for 3D Medical Image Segmentation

Science.gov (United States)

Pizer, Stephen M.; Fletcher, P. Thomas; Joshi, Sarang; Thall, Andrew; Chen, James Z.; Fridman, Yonatan; Fritsch, Daniel S.; Gash, Graham; Glotzer, John M.; Jiroutek, Michael R.; Lu, Conglin; Muller, Keith E.; Tracton, Gregg; Yushkevich, Paul; Chaney, Edward L.

2013-01-01

M-reps (formerly called DSLs) are a multiscale medial means for modeling and rendering 3D solid geometry. They are particularly well suited to model anatomic objects and in particular to capture prior geometric information effectively in deformable models segmentation approaches. The representation is based on figural models, which define objects at coarse scale by a hierarchy of figures – each figure generally a slab representing a solid region and its boundary simultaneously. This paper focuses on the use of single figure models to segment objects of relatively simple structure. A single figure is a sheet of medial atoms, which is interpolated from the model formed by a net, i.e., a mesh or chain, of medial atoms (hence the name m-reps), each atom modeling a solid region via not only a position and a width but also a local figural frame giving figural directions and an object angle between opposing, corresponding positions on the boundary implied by the m-rep. The special capability of an m-rep is to provide spatial and orientational correspondence between an object in two different states of deformation. This ability is central to effective measurement of both geometric typicality and geometry to image match, the two terms of the objective function optimized in segmentation by deformable models. The other ability of m-reps central to effective segmentation is their ability to support segmentation at multiple levels of scale, with successively finer precision. Objects modeled by single figures are segmented first by a similarity transform augmented by object elongation, then by adjustment of each medial atom, and finally by displacing a dense sampling of the m-rep implied boundary. While these models and approaches also exist in 2D, we focus on 3D objects. The segmentation of the kidney from CT and the hippocampus from MRI serve as the major examples in this paper. The accuracy of segmentation as compared to manual, slice-by-slice segmentation is reported. PMID

Segmentation of multiple heart cavities in 3-D transesophageal ultrasound images

NARCIS (Netherlands)

Haak, A.; Vegas-Sanchez-Ferrero, G.; Mulder, H.W.; Ren, B.; Kirisli, H.A.; Metz, C.; van Burken, G.; van Stralen, M.; Pluim, J.P.W.; Steen, van der A.F.W.; Walsum, van T.; Bosch, J.G.

Three-dimensional transesophageal echocardiography (TEE) is an excellent modality for real-time visualization of the heart and monitoring of interventions. To improve the usability of 3-D TEE for intervention monitoring and catheter guidance, automated segmentation is desired. However, 3-D TEE

Soft tissue segmentation and 3D display from computerized tomography and magnetic resonance imaging

International Nuclear Information System (INIS)

Fan, R.T.; Trivedi, S.S.; Fellingham, L.L.; Gamboa-Aldeco, A.; Hedgcock, M.W.

1987-01-01

Volume calculation and 3D display of human anatomy facilitate a physician's diagnosis, treatment, and evaluation. Accurate segmentation of soft tissue structures is a prerequisite for such volume calculations and 3D displays, but segmentation by hand-outlining structures is often tedious and time-consuming. In this paper, methods based on analysis of statistics of image gray level are applied to segmentation of soft tissue in medical images, with the goal of making segmentation automatic or semi-automatic. The resulting segmented images, volume calculations, and 3D displays are analyzed and compared with results based on physician-drawn outlines as well as actual volume measurements

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

Energy Technology Data Exchange (ETDEWEB)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich [Departments of Electrical and Computer Engineering and Internal Medicine, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16, A-8010 Graz (Austria); Department of Electrical and Computer Engineering, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Radiology, Medical University Graz, Auenbruggerplatz 34, A-8010 Graz (Austria)

2012-03-15

Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

International Nuclear Information System (INIS)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

2012-01-01

Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods.

Science.gov (United States)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

2012-03-01

Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and∕or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of user interaction

A wavelet-based Bayesian framework for 3D object segmentation in microscopy

Science.gov (United States)

Pan, Kangyu; Corrigan, David; Hillebrand, Jens; Ramaswami, Mani; Kokaram, Anil

2012-03-01

In confocal microscopy, target objects are labeled with fluorescent markers in the living specimen, and usually appear with irregular brightness in the observed images. Also, due to the existence of out-of-focus objects in the image, the segmentation of 3-D objects in the stack of image slices captured at different depth levels of the specimen is still heavily relied on manual analysis. In this paper, a novel Bayesian model is proposed for segmenting 3-D synaptic objects from given image stack. In order to solve the irregular brightness and out-offocus problems, the segmentation model employs a likelihood using the luminance-invariant 'wavelet features' of image objects in the dual-tree complex wavelet domain as well as a likelihood based on the vertical intensity profile of the image stack in 3-D. Furthermore, a smoothness 'frame' prior based on the a priori knowledge of the connections of the synapses is introduced to the model for enhancing the connectivity of the synapses. As a result, our model can successfully segment the in-focus target synaptic object from a 3D image stack with irregular brightness.

Segmentation of multiple heart cavities in 3-D transesophageal ultrasound images.

Science.gov (United States)

Haak, Alexander; Vegas-Sánchez-Ferrero, Gonzalo; Mulder, Harriët W; Ren, Ben; Kirişli, Hortense A; Metz, Coert; van Burken, Gerard; van Stralen, Marijn; Pluim, Josien P W; van der Steen, Antonius F W; van Walsum, Theo; Bosch, Johannes G

2015-06-01

Three-dimensional transesophageal echocardiography (TEE) is an excellent modality for real-time visualization of the heart and monitoring of interventions. To improve the usability of 3-D TEE for intervention monitoring and catheter guidance, automated segmentation is desired. However, 3-D TEE segmentation is still a challenging task due to the complex anatomy with multiple cavities, the limited TEE field of view, and typical ultrasound artifacts. We propose to segment all cavities within the TEE view with a multi-cavity active shape model (ASM) in conjunction with a tissue/blood classification based on a gamma mixture model (GMM). 3-D TEE image data of twenty patients were acquired with a Philips X7-2t matrix TEE probe. Tissue probability maps were estimated by a two-class (blood/tissue) GMM. A statistical shape model containing the left ventricle, right ventricle, left atrium, right atrium, and aorta was derived from computed tomography angiography (CTA) segmentations by principal component analysis. ASMs of the whole heart and individual cavities were generated and consecutively fitted to tissue probability maps. First, an average whole-heart model was aligned with the 3-D TEE based on three manually indicated anatomical landmarks. Second, pose and shape of the whole-heart ASM were fitted by a weighted update scheme excluding parts outside of the image sector. Third, pose and shape of ASM for individual heart cavities were initialized by the previous whole heart ASM and updated in a regularized manner to fit the tissue probability maps. The ASM segmentations were validated against manual outlines by two observers and CTA derived segmentations. Dice coefficients and point-to-surface distances were used to determine segmentation accuracy. ASM segmentations were successful in 19 of 20 cases. The median Dice coefficient for all successful segmentations versus the average observer ranged from 90% to 71% compared with an inter-observer range of 95% to 84%. The

Sloped Terrain Segmentation for Autonomous Drive Using Sparse 3D Point Cloud

Directory of Open Access Journals (Sweden)

Seoungjae Cho

2014-01-01

Full Text Available A ubiquitous environment for road travel that uses wireless networks requires the minimization of data exchange between vehicles. An algorithm that can segment the ground in real time is necessary to obtain location data between vehicles simultaneously executing autonomous drive. This paper proposes a framework for segmenting the ground in real time using a sparse three-dimensional (3D point cloud acquired from undulating terrain. A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR sensors. For efficient ground segmentation, 3D point clouds are quantized in units of volume pixels (voxels and overlapping data is eliminated. We reduce nonoverlapping voxels to two dimensions by implementing a lowermost heightmap. The ground area is determined on the basis of the number of voxels in each voxel group. We execute ground segmentation in real time by proposing an approach to minimize the comparison between neighboring voxels. Furthermore, we experimentally verify that ground segmentation can be executed at about 19.31 ms per frame.

War, traffic and iatrogenic injuries of D3 duodenal segment

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Ignjatović Dragan

2005-01-01

Full Text Available Background. Injuries of the duodenum at the level of aortomesenteric clamp (segment D3 are with a high incidence of death due to the development of fistula and peritonitis. In three successfully managed cases, we applied the biliary surgery method. Case reports. All three cases were with the injuries of D3 duodenal segment. The first patient suffered from the blast perforation of duodenum at the level of the aortomesenteric clamp which occurred at the 7th day after the injury. The second patient suffered from the duodenal injury caused in a traffic accident. The third patient suffered from an iatrogenic injury at the beginning of D3 duodenal segment inflicted during ureterolithotomy. The described surgical procedure included basically the suture to narrow the site of the injury, then lateroterminal anastomosis with the Roux-en-Y jejunal flexure and, finally, the placement of a silicone prosthesis starting from the duodenum through the site of injury and the Roux-en-Y out. Octreotide and the total parenteral nutrition were administered to the patients postoperatively. Conclusion. The use of the releasing silicone prosthesis in all three patients provided the repair of the site of the injury with anastomosed Reux-en-Y jejunum.

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

Science.gov (United States)

Chen, Xinjian; Bagci, Ulas

2011-08-01

This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images. 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. The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10 degrees and 0.03, and over all foot bones are about 3.5709 mm, 0.35 degrees 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 all foot bones for

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

International Nuclear Information System (INIS)

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 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

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

Directory of Open Access Journals (Sweden)

Chunlei Xia

2015-08-01

Full Text Available 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.

Effect of 24,25-dihydroxyvitamin D3 on 1,25-dihydroxyvitamin D3 [1,25-(OH)2D3] metabolism in vitamin D-deficient rats infused with 1,25-(OH)2D3

International Nuclear Information System (INIS)

Yamato, H.; Matsumoto, T.; Fukumoto, S.; Ikeda, K.; Ishizuka, S.; Ogata, E.

1989-01-01

Previous studies revealed that administration of 24,25-dihydroxyvitamin D3 [24,25-(OH)2D3] to calcium (Ca)-deficient rats causes a dose-dependent reduction in markedly elevated serum 1,25-(OH)2D3 level. Although the results suggested that the metabolism of 1,25-(OH)2D3 was accelerated by 24,25-(OH)2D3, those experiments could not define whether the enhanced metabolism of 1,25-(OH)2D3 played a role in the reduction in the serum 1,25-(OH)2D3 level. In the present study, in order to address this issue more specifically, serum 1,25-(OH)2D3 was maintained solely by exogenous administration through miniosmotic pumps of 1,25-(OH)2D3 into vitamin D-deficient rats. Thus, by measuring the serum 1,25-(OH)2D3 concentration, the effect of 24,25-(OH)2D3 on the MCR of 1,25-(OH)2D3 could be examined. Administration of 24,25-(OH)2D3 caused a dose-dependent enhancement in the MCR of 1,25-(OH)2D3, and 1 microgram/100 g rat.day 24,25-(OH)2D3, which elevated serum 24,25-(OH)2D3 to 8.6 +/- 1.3 ng/ml, significantly increased MCR and suppressed serum levels of 1,25-(OH)2D3. The effect of 24,25-(OH)2D3 on 1,25-(OH)2D3 metabolism developed with a rapid time course, and the recovery of iv injected [1 beta-3H]1,25-(OH)2D3 in blood was significantly reduced within 1 h. In addition, there was an increase in radioactivity in the water-soluble fraction of serum as well as in urine, suggesting that 1,25-(OH)2D3 is rapidly degraded to a water-soluble metabolite(s). Furthermore, the reduction in serum 1,25-(OH)2D3 was associated with a reduction in both serum and urinary Ca levels. Because the conversion of [3H]24,25-(OH)2D3 to [3H]1,24,25-(OH)2D3 or other metabolites was minimal in these rats, 24,25-(OH)2D3 appears to act without being converted into other metabolites. These results demonstrate that 24,25-(OH)2D3 rapidly stimulates the metabolism of 1,25-(OH)2D3 and reduces its serum level

Segmentation of the lumen and media-adventitia boundaries of the common carotid artery from 3D ultrasound images

Science.gov (United States)

Ukwatta, E.; Awad, J.; Ward, A. D.; Samarabandu, J.; Krasinski, A.; Parraga, G.; Fenster, A.

2011-03-01

Three-dimensional ultrasound (3D US) vessel wall volume (VWV) measurements provide high measurement sensitivity and reproducibility for the monitoring and assessment of carotid atherosclerosis. In this paper, we describe a semiautomated approach based on the level set method to delineate the media-adventitia and lumen boundaries of the common carotid artery from 3D US images to support the computation of VWV. Due to the presence of plaque and US image artifacts, the carotid arteries are challenging to segment using image information alone. Our segmentation framework combines several image cues with domain knowledge and limited user interaction. Our method was evaluated with respect to manually outlined boundaries on 430 2D US images extracted from 3D US images of 30 patients who have carotid stenosis of 60% or more. The VWV given by our method differed from that given by manual segmentation by 6.7% +/- 5.0%. For the media-adventitia and lumen segmentations, respectively, our method yielded Dice coefficients of 95.2% +/- 1.6%, 94.3% +/- 2.6%, mean absolute distances of 0.3 +/- 0.1 mm, 0.2 +/- 0.1 mm, maximum absolute distances of 0.8 +/- 0.4 mm, 0.6 +/- 0.3 mm, and volume differences of 4.2% +/- 3.1%, 3.4% +/- 2.6%. The realization of a semi-automated segmentation method will accelerate the translation of 3D carotid US to clinical care for the rapid, non-invasive, and economical monitoring of atherosclerotic disease progression and regression during therapy.

Dynamical compactification of D-dimensional gravity coupled to antisymmetric tensors in a 1/D expansion

International Nuclear Information System (INIS)

Foda, O.

1984-12-01

The effective potential of components of the curl of an antisymmetric tensor coupled to gravity in D dimensions is evaluated in a 1/D expansion. For large D, only highest-rank propagators contribute to leading order, while multiloop diagrams are suppressed by phase-space factors. Divergences are regulated by a cut-off LAMBDA, that we interpret as the mass-breaking scale of a larger theory that is finite. As an application we consider the bosonic sector of D=11, N=1 supergravity. If the full theory is finite, then LAMBDA is msub(SUSY): the scale below which the fermion sector decouples. For m 9 sub(SUSY)>1/akappa 2 , (kappa 2 : the D=11 Newton's coupling, a approx.= O(1)) the 11-dimensional symmetric vacuum is unstable under compactification. For m 9 sub(SUSY) 2 , it is metastable. To leading order in 1/D, all gauge dependence cancels identically, while ghosts as well as the graviton decouple. (author)

Oblique needle segmentation and tracking for 3D TRUS guided prostate brachytherapy

International Nuclear Information System (INIS)

Wei Zhouping; Gardi, Lori; Downey, Donal B.; Fenster, Aaron

2005-01-01

An algorithm was developed in order to segment and track brachytherapy needles inserted along oblique trajectories. Three-dimensional (3D) transrectal ultrasound (TRUS) images of the rigid rod simulating the needle inserted into the tissue-mimicking agar and chicken breast phantoms were obtained to test the accuracy of the algorithm under ideal conditions. Because the robot possesses high positioning and angulation accuracies, we used the robot as a ''gold standard,'' and compared the results of algorithm segmentation to the values measured by the robot. Our testing results showed that the accuracy of the needle segmentation algorithm depends on the needle insertion distance into the 3D TRUS image and the angulations with respect to the TRUS transducer, e.g., at a 10 deg. insertion anglulation in agar phantoms, the error of the algorithm in determining the needle tip position was less than 1 mm when the insertion distance was greater than 15 mm. Near real-time needle tracking was achieved by scanning a small volume containing the needle. Our tests also showed that, the segmentation time was less than 60 ms, and the scanning time was less than 1.2 s, when the insertion distance into the 3D TRUS image was less than 55 mm. In our needle tracking tests in chicken breast phantoms, the errors in determining the needle orientation were less than 2 deg. in robot yaw and 0.7 deg. in robot pitch orientations, for up to 20 deg. needle insertion angles with the TRUS transducer in the horizontal plane when the needle insertion distance was greater than 15 mm

Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks

Science.gov (United States)

Roth, Holger; Oda, Masahiro; Shimizu, Natsuki; Oda, Hirohisa; Hayashi, Yuichiro; Kitasaka, Takayuki; Fujiwara, Michitaka; Misawa, Kazunari; Mori, Kensaku

2018-03-01

Pancreas segmentation in computed tomography imaging has been historically difficult for automated methods because of the large shape and size variations between patients. In this work, we describe a custom-build 3D fully convolutional network (FCN) that can process a 3D image including the whole pancreas and produce an automatic segmentation. We investigate two variations of the 3D FCN architecture; one with concatenation and one with summation skip connections to the decoder part of the network. We evaluate our methods on a dataset from a clinical trial with gastric cancer patients, including 147 contrast enhanced abdominal CT scans acquired in the portal venous phase. Using the summation architecture, we achieve an average Dice score of 89.7 +/- 3.8 (range [79.8, 94.8])% in testing, achieving the new state-of-the-art performance in pancreas segmentation on this dataset.

A phylogenetic framework for root lesion nematodes of the genus Pratylenchus (Nematoda): Evidence from 18S and D2-D3 expansion segments of 28S ribosomal RNA genes and morphological characters.

Science.gov (United States)

Subbotin, Sergei A; Ragsdale, Erik J; Mullens, Teresa; Roberts, Philip A; Mundo-Ocampo, Manuel; Baldwin, James G

2008-08-01

The root lesion nematodes of the genus Pratylenchus Filipjev, 1936 are migratory endoparasites of plant roots, considered among the most widespread and important nematode parasites in a variety of crops. We obtained gene sequences from the D2 and D3 expansion segments of 28S rRNA partial and 18S rRNA from 31 populations belonging to 11 valid and two unidentified species of root lesion nematodes and five outgroup taxa. These datasets were analyzed using maximum parsimony and Bayesian inference. The alignments were generated using the secondary structure models for these molecules and analyzed with Bayesian inference under the standard models and the complex model, considering helices under the doublet model and loops and bulges under the general time reversible model. The phylogenetic informativeness of morphological characters is tested by reconstruction of their histories on rRNA based trees using parallel parsimony and Bayesian approaches. Phylogenetic and sequence analyses of the 28S D2-D3 dataset with 145 accessions for 28 species and 18S dataset with 68 accessions for 15 species confirmed among large numbers of geographical diverse isolates that most classical morphospecies are monophyletic. Phylogenetic analyses revealed at least six distinct major clades of examined Pratylenchus species and these clades are generally congruent with those defined by characters derived from lip patterns, numbers of lip annules, and spermatheca shape. Morphological results suggest the need for sophisticated character discovery and analysis for morphology based phylogenetics in nematodes.

A Hierarchical Building Segmentation in Digital Surface Models for 3D Reconstruction

Directory of Open Access Journals (Sweden)

Yiming Yan

2017-01-01

Full Text Available In this study, a hierarchical method for segmenting buildings in a digital surface model (DSM, which is used in a novel framework for 3D reconstruction, is proposed. Most 3D reconstructions of buildings are model-based. However, the limitations of these methods are overreliance on completeness of the offline-constructed models of buildings, and the completeness is not easily guaranteed since in modern cities buildings can be of a variety of types. Therefore, a model-free framework using high precision DSM and texture-images buildings was introduced. There are two key problems with this framework. The first one is how to accurately extract the buildings from the DSM. Most segmentation methods are limited by either the terrain factors or the difficult choice of parameter-settings. A level-set method are employed to roughly find the building regions in the DSM, and then a recently proposed ‘occlusions of random textures model’ are used to enhance the local segmentation of the buildings. The second problem is how to generate the facades of buildings. Synergizing with the corresponding texture-images, we propose a roof-contour guided interpolation of building facades. The 3D reconstruction results achieved by airborne-like images and satellites are compared. Experiments show that the segmentation method has good performance, and 3D reconstruction is easily performed by our framework, and better visualization results can be obtained by airborne-like images, which can be further replaced by UAV images.

A software tool for automatic classification and segmentation of 2D/3D medical images

International Nuclear Information System (INIS)

Strzelecki, Michal; Szczypinski, Piotr; Materka, Andrzej; Klepaczko, Artur

2013-01-01

Modern medical diagnosis utilizes techniques of visualization of human internal organs (CT, MRI) or of its metabolism (PET). However, evaluation of acquired images made by human experts is usually subjective and qualitative only. Quantitative analysis of MR data, including tissue classification and segmentation, is necessary to perform e.g. attenuation compensation, motion detection, and correction of partial volume effect in PET images, acquired with PET/MR scanners. This article presents briefly a MaZda software package, which supports 2D and 3D medical image analysis aiming at quantification of image texture. MaZda implements procedures for evaluation, selection and extraction of highly discriminative texture attributes combined with various classification, visualization and segmentation tools. Examples of MaZda application in medical studies are also provided

A software tool for automatic classification and segmentation of 2D/3D medical images

Energy Technology Data Exchange (ETDEWEB)

Strzelecki, Michal, E-mail: michal.strzelecki@p.lodz.pl [Institute of Electronics, Technical University of Lodz, Wolczanska 211/215, 90-924 Lodz (Poland); Szczypinski, Piotr; Materka, Andrzej; Klepaczko, Artur [Institute of Electronics, Technical University of Lodz, Wolczanska 211/215, 90-924 Lodz (Poland)

2013-02-21

Modern medical diagnosis utilizes techniques of visualization of human internal organs (CT, MRI) or of its metabolism (PET). However, evaluation of acquired images made by human experts is usually subjective and qualitative only. Quantitative analysis of MR data, including tissue classification and segmentation, is necessary to perform e.g. attenuation compensation, motion detection, and correction of partial volume effect in PET images, acquired with PET/MR scanners. This article presents briefly a MaZda software package, which supports 2D and 3D medical image analysis aiming at quantification of image texture. MaZda implements procedures for evaluation, selection and extraction of highly discriminative texture attributes combined with various classification, visualization and segmentation tools. Examples of MaZda application in medical studies are also provided.

The hominoid-specific gene TBC1D3 promotes generation of basal neural progenitors and induces cortical folding in mice

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Ju, Xiang-Chun; Hou, Qiong-Qiong; Sheng, Ai-Li; Wu, Kong-Yan; Zhou, Yang; Jin, Ying; Wen, Tieqiao; Yang, Zhengang; Wang, Xiaoqun; Luo, Zhen-Ge

2016-01-01

Cortical expansion and folding are often linked to the evolution of higher intelligence, but molecular and cellular mechanisms underlying cortical folding remain poorly understood. The hominoid-specific gene TBC1D3 undergoes segmental duplications during hominoid evolution, but its role in brain development has not been explored. Here, we found that expression of TBC1D3 in ventricular cortical progenitors of mice via in utero electroporation caused delamination of ventricular radial glia cells (vRGs) and promoted generation of self-renewing basal progenitors with typical morphology of outer radial glia (oRG), which are most abundant in primates. Furthermore, down-regulation of TBC1D3 in cultured human brain slices decreased generation of oRGs. Interestingly, localized oRG proliferation resulting from either in utero electroporation or transgenic expression of TBC1D3, was often found to underlie cortical regions exhibiting folding. Thus, we have identified a hominoid gene that is required for oRG generation in regulating the cortical expansion and folding. DOI: http://dx.doi.org/10.7554/eLife.18197.001 PMID:27504805

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

International Nuclear Information System (INIS)

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

2006-01-01

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

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

International Nuclear Information System (INIS)

Fiorina, E.; Valzano, S.; Arteche Diaz, R.; Bosco, P.; Gargano, G.; Megna, R.; Oppedisano, C.; Massafra, A.

2011-01-01

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.

Expansion of Bone Marrow Mesenchymal Stromal Cells in Perfused 3D Ceramic Scaffolds Enhances In Vivo Bone Formation.

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Hoch, Allison I; Duhr, Ralph; Di Maggio, Nunzia; Mehrkens, Arne; Jakob, Marcel; Wendt, David

2017-12-01

Bone marrow-derived mesenchymal stromal cells (BMSC), when expanded directly within 3D ceramic scaffolds in perfusion bioreactors, more reproducibly form bone when implanted in vivo as compared to conventional expansion on 2D polystyrene dishes/flasks. Since the bioreactor-based expansion on 3D ceramic scaffolds encompasses multiple aspects that are inherently different from expansion on 2D polystyrene, we aimed to decouple the effects of specific parameters among these two model systems. We assessed the effects of the: 1) 3D scaffold vs. 2D surface; 2) ceramic vs. polystyrene materials; and 3) BMSC niche established within the ceramic pores during in vitro culture, on subsequent in vivo bone formation. While BMSC expanded on 3D polystyrene scaffolds in the bioreactor could maintain their in vivo osteogenic potential, results were similar as BMSC expanded in monolayer on 2D polystyrene, suggesting little influence of the scaffold 3D environment. Bone formation was most reproducible when BMSC are expanded on 3D ceramic, highlighting the influence of the ceramic substrate. The presence of a pre-formed niche within the scaffold pores had negligible effects on the in vivo bone formation. The results of this study allow a greater understanding of the parameters required for perfusion bioreactor-based manufacturing of osteogenic grafts for clinical applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ultrafast superpixel segmentation of large 3D medical datasets

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Leblond, Antoine; Kauffmann, Claude

2016-03-01

Even with recent hardware improvements, superpixel segmentation of large 3D medical images at interactive speed (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.

3D GEOMARKETING SEGMENTATION: A HIGHER SPATIAL DIMENSION PLANNING PERSPECTIVE

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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

Computerized liver volumetry on MRI by using 3D geodesic active contour segmentation.

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Huynh, Hieu Trung; Karademir, Ibrahim; Oto, Aytekin; Suzuki, Kenji

2014-01-01

Our purpose was to develop an accurate automated 3D liver segmentation scheme for measuring liver volumes on MRI. Our scheme for MRI liver volumetry consisted of three main stages. First, the preprocessing stage was applied to T1-weighted MRI of the liver in the portal venous phase to reduce noise and produce the boundary-enhanced image. This boundary-enhanced image was used as a speed function for a 3D fast-marching algorithm to generate an initial surface that roughly approximated the shape of the liver. A 3D geodesic-active-contour segmentation algorithm refined the initial surface to precisely determine the liver boundaries. The liver volumes determined by our scheme were compared with those manually traced by a radiologist, used as the reference standard. The two volumetric methods reached excellent agreement (intraclass correlation coefficient, 0.98) without statistical significance (p = 0.42). The average (± SD) accuracy was 99.4% ± 0.14%, and the average Dice overlap coefficient was 93.6% ± 1.7%. The mean processing time for our automated scheme was 1.03 ± 0.13 minutes, whereas that for manual volumetry was 24.0 ± 4.4 minutes (p volumetry based on our automated scheme agreed excellently with reference-standard volumetry, and it required substantially less completion time.

Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method.

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Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Hara, Takeshi; Fujita, Hiroshi

2017-10-01

We propose a single network trained by pixel-to-label deep learning to address the general issue of automatic multiple organ segmentation in three-dimensional (3D) computed tomography (CT) images. Our method can be described as a voxel-wise multiple-class classification scheme for automatically assigning labels to each pixel/voxel in a 2D/3D CT image. We simplify the segmentation algorithms of anatomical structures (including multiple organs) in a CT image (generally in 3D) to a majority voting scheme over the semantic segmentation of multiple 2D slices drawn from different viewpoints with redundancy. The proposed method inherits the spirit of fully convolutional networks (FCNs) that consist of "convolution" and "deconvolution" layers for 2D semantic image segmentation, and expands the core structure with 3D-2D-3D transformations to adapt to 3D CT image segmentation. All parameters in the proposed network are trained pixel-to-label from a small number of CT cases with human annotations as the ground truth. The proposed network naturally fulfills the requirements of multiple organ segmentations in CT cases of different sizes that cover arbitrary scan regions without any adjustment. The proposed network was trained and validated using the simultaneous segmentation of 19 anatomical structures in the human torso, including 17 major organs and two special regions (lumen and content inside of stomach). Some of these structures have never been reported in previous research on CT segmentation. A database consisting of 240 (95% for training and 5% for testing) 3D CT scans, together with their manually annotated ground-truth segmentations, was used in our experiments. The results show that the 19 structures of interest were segmented with acceptable accuracy (88.1% and 87.9% voxels in the training and testing datasets, respectively, were labeled correctly) against the ground truth. We propose a single network based on pixel-to-label deep learning to address the challenging

AN ADAPTIVE APPROACH FOR SEGMENTATION OF 3D LASER POINT CLOUD

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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.

Weighted f-values, A-values, and line strengths for the E1 transitions among 3d6, 3d54s, and 3d54p levels of Fe III

International Nuclear Information System (INIS)

Deb, Narayan C.; Hibbert, Alan

2009-01-01

Weighted oscillator strengths, weighted radiative rates, and line strengths for all the E1 transitions between 285 fine-structure levels belonging to the 3d 6 , 3d 5 4s, and 3d 5 4p configurations of Fe III are presented, in ascending order of wavelength. Calculations have been undertaken using the general configuration interaction (CI) code CIV3. The large configuration set is constructed by allowing single and double replacements from any of 3d 6 , 3d 5 4s, 3d 5 4p, and 3d 5 4d configurations to nl orbitals with n≤5,l≤3 as well as 6p. Additional selective promotions from 3s and 3p subshells are also included in the CI expansions to incorporate the important correlation effects in the n=3 shell. Results of some strong transitions between levels of 3d 6 , 3d 5 4s, and 3d 5 4p configurations are also presented and compared with other available calculations. It is found that large disagreements occur in many transitions among the existing calculations

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

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Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi; Åkerfelt, Malin; Nees, Matthias

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.

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.

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

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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).

3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging

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Aloni, Doron; Jung, Jae-Hyun; Yitzhaky, Yitzhak

2017-10-01

Three dimensional (3D) object segmentation and tracking can be useful in various computer vision applications, such as: object surveillance for security uses, robot navigation, etc. We present a method for 3D multiple-object tracking using computational integral imaging, based on accurate 3D object segmentation. The method does not employ object detection by motion analysis in a video as conventionally performed (such as background subtraction or block matching). This means that the movement properties do not significantly affect the detection quality. The object detection is performed by analyzing static 3D image data obtained through computational integral imaging With regard to previous works that used integral imaging data in such a scenario, the proposed method performs the 3D tracking of objects without prior information about the objects in the scene, and it is found efficient under severe noise conditions.

An accurate segmentation method for volumetry of brain tumor in 3D MRI

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Wang, Jiahui; Li, Qiang; Hirai, Toshinori; Katsuragawa, Shigehiko; Li, Feng; Doi, Kunio

2008-03-01

Accurate volumetry of brain tumors in magnetic resonance imaging (MRI) is important for evaluating the interval changes in tumor volumes during and after treatment, and also for planning of radiation therapy. In this study, an automated volumetry method for brain tumors in MRI was developed by use of a new three-dimensional (3-D) image segmentation technique. First, the central location of a tumor was identified by a radiologist, and then a volume of interest (VOI) was determined automatically. To substantially simplify tumor segmentation, we transformed the 3-D image of the tumor into a two-dimensional (2-D) image by use of a "spiral-scanning" technique, in which a radial line originating from the center of the tumor scanned the 3-D image spirally from the "north pole" to the "south pole". The voxels scanned by the radial line provided a transformed 2-D image. We employed dynamic programming to delineate an "optimal" outline of the tumor in the transformed 2-D image. We then transformed the optimal outline back into 3-D image space to determine the volume of the tumor. The volumetry method was trained and evaluated by use of 16 cases with 35 brain tumors. The agreement between tumor volumes provided by computer and a radiologist was employed as a performance metric. Our method provided relatively accurate results with a mean agreement value of 88%.

Intensity-based segmentation and visualization of cells in 3D microscopic images using the GPU

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Kang, Mi-Sun; Lee, Jeong-Eom; Jeon, Woong-ki; Choi, Heung-Kook; Kim, Myoung-Hee

2013-02-01

3D microscopy images contain abundant astronomical data, rendering 3D microscopy image processing time-consuming and laborious on a central processing unit (CPU). To solve these problems, many people crop a region of interest (ROI) of the input image to a small size. Although this reduces cost and time, there are drawbacks at the image processing level, e.g., the selected ROI strongly depends on the user and there is a loss in original image information. To mitigate these problems, we developed a 3D microscopy image processing tool on a graphics processing unit (GPU). Our tool provides efficient and various automatic thresholding methods to achieve intensity-based segmentation of 3D microscopy images. Users can select the algorithm to be applied. Further, the image processing tool provides visualization of segmented volume data and can set the scale, transportation, etc. using a keyboard and mouse. However, the 3D objects visualized fast still need to be analyzed to obtain information for biologists. To analyze 3D microscopic images, we need quantitative data of the images. Therefore, we label the segmented 3D objects within all 3D microscopic images and obtain quantitative information on each labeled object. This information can use the classification feature. A user can select the object to be analyzed. Our tool allows the selected object to be displayed on a new window, and hence, more details of the object can be observed. Finally, we validate the effectiveness of our tool by comparing the CPU and GPU processing times by matching the specification and configuration.

Sci-Thur AM: YIS – 03: Combining sagittally-reconstructed 3D and live-2D ultrasound for high-dose-rate prostate brachytherapy needle segmentation

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Hrinivich, Thomas; Hoover, Douglas; Surry, Kathleen; Edirisinghe, Chandima; D’Souza, David; Fenster, Aaron; Wong, Eugene [University of Western Ontario, London Regional Cancer Program/LHSC, London Regional Cancer Program/LHSC, Robarts Research Institute, London Regional Cancer Program/LHSC, Robarts Research Institute, University of Western Ontario (Canada)

2016-08-15

Ultrasound-guided high-dose-rate prostate brachytherapy (HDR-BT) needle segmentation is performed clinically using live-2D sagittal images. Organ segmentation is then performed using axial images, introducing a source of geometric uncertainty. Sagittally-reconstructed 3D (SR3D) ultrasound enables both needle and organ segmentation, but suffers from shadow artifacts. We present a needle segmentation technique augmenting SR3D with live-2D sagittal images using mechanical probe tracking to mitigate image artifacts and compare it to the clinical standard. Seven prostate cancer patients underwent TRUS-guided HDR-BT during which the clinical and proposed segmentation techniques were completed in parallel using dual ultrasound video outputs. Calibrated needle end-length measurements were used to calculate insertion depth errors (IDEs), and the dosimetric impact of IDEs was evaluated by perturbing clinical treatment plan source positions. The proposed technique provided smaller IDEs than the clinical approach, with mean±SD of −0.3±2.2 mm and −0.5±3.7mm respectively. The proposed and clinical techniques resulted in 84% and 43% of needles with IDEs within ±3mm, and IDE ranges across all needles of [−7.7mm, 5.9mm] and [−9.3mm, 7.7mm] respectively. The proposed and clinical IDEs lead to mean±SD changes in the volume of the prostate receiving the prescription dose of −0.6±0.9% and −2.0±5.3% respectively. The proposed technique provides improved HDR-BT needle segmentation accuracy over the clinical technique leading to decreased dosimetric uncertainty by eliminating the axial-to-sagittal registration, and mitigates the effect of shadow artifacts by incorporating mechanically registered live-2D sagittal images.

Automatic gallbladder segmentation using combined 2D and 3D shape features to perform volumetric analysis in native and secretin-enhanced MRCP sequences.

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Gloger, Oliver; Bülow, Robin; Tönnies, Klaus; Völzke, Henry

2017-11-24

We aimed to develop the first fully automated 3D gallbladder segmentation approach to perform volumetric analysis in volume data of magnetic resonance (MR) cholangiopancreatography (MRCP) sequences. Volumetric gallbladder analysis is performed for non-contrast-enhanced and secretin-enhanced MRCP sequences. Native and secretin-enhanced MRCP volume data were produced with a 1.5-T MR system. Images of coronal maximum intensity projections (MIP) are used to automatically compute 2D characteristic shape features of the gallbladder in the MIP images. A gallbladder shape space is generated to derive 3D gallbladder shape features, which are then combined with 2D gallbladder shape features in a support vector machine approach to detect gallbladder regions in MRCP volume data. A region-based level set approach is used for fine segmentation. Volumetric analysis is performed for both sequences to calculate gallbladder volume differences between both sequences. The approach presented achieves segmentation results with mean Dice coefficients of 0.917 in non-contrast-enhanced sequences and 0.904 in secretin-enhanced sequences. This is the first approach developed to detect and segment gallbladders in MR-based volume data automatically in both sequences. It can be used to perform gallbladder volume determination in epidemiological studies and to detect abnormal gallbladder volumes or shapes. The positive volume differences between both sequences may indicate the quantity of the pancreatobiliary reflux.

Estimation of regional lung expansion via 3D image registration

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Pan, Yan; Kumar, Dinesh; Hoffman, Eric A.; Christensen, Gary E.; McLennan, Geoffrey; Song, Joo Hyun; Ross, Alan; Simon, Brett A.; Reinhardt, Joseph M.

2005-04-01

A method is described to estimate regional lung expansion and related biomechanical parameters using multiple CT images of the lungs, acquired at different inflation levels. In this study, the lungs of two sheep were imaged utilizing a multi-detector row CT at different lung inflations in the prone and supine positions. Using the lung surfaces and the airway branch points for guidance, a 3D inverse consistent image registration procedure was used to match different lung volumes at each orientation. The registration was validated using a set of implanted metal markers. After registration, the Jacobian of the deformation field was computed to express regional expansion or contraction. The regional lung expansion at different pressures and different orientations are compared.

Segmentation of 3d Models for Cultural Heritage Structural Analysis - Some Critical Issues

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Gonizzi Barsanti, S.; Guidi, G.; De Luca, L.

2017-08-01

Cultural Heritage documentation and preservation has become a fundamental concern in this historical period. 3D modelling offers a perfect aid to record ancient buildings and artefacts and can be used as a valid starting point for restoration, conservation and structural analysis, which can be performed by using Finite Element Methods (FEA). The models derived from reality-based techniques, made up of the exterior surfaces of the objects captured at high resolution, are - for this reason - made of millions of polygons. Such meshes are not directly usable in structural analysis packages and need to be properly pre-processed in order to be transformed in volumetric meshes suitable for FEA. In addition, dealing with ancient objects, a proper segmentation of 3D volumetric models is needed to analyse the behaviour of the structure with the most suitable level of detail for the different sections of the structure under analysis. Segmentation of 3D models is still an open issue, especially when dealing with ancient, complicated and geometrically complex objects that imply the presence of anomalies and gaps, due to environmental agents such as earthquakes, pollution, wind and rain, or human factors. The aims of this paper is to critically analyse some of the different methodologies and algorithms available to segment a 3D point cloud or a mesh, identifying difficulties and problems by showing examples on different structures.

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

International Nuclear Information System (INIS)

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

2011-01-01

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 T 2 -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.

3D exemplar-based random walks for tooth segmentation from cone-beam computed tomography images

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Pei, Yuru, E-mail: peiyuru@cis.pku.edu.cn; Ai, Xingsheng; Zha, Hongbin [Department of Machine Intelligence, School of EECS, Peking University, Beijing 100871 (China); Xu, Tianmin [School of Stomatology, Stomatology Hospital, Peking University, Beijing 100081 (China); Ma, Gengyu [uSens, Inc., San Jose, California 95110 (United States)

2016-09-15

Purpose: Tooth segmentation is an essential step in acquiring patient-specific dental geometries from cone-beam computed tomography (CBCT) images. Tooth segmentation from CBCT images is still a challenging task considering the comparatively low image quality caused by the limited radiation dose, as well as structural ambiguities from intercuspation and nearby alveolar bones. The goal of this paper is to present and discuss the latest accomplishments in semisupervised tooth segmentation with adaptive 3D shape constraints. Methods: The authors propose a 3D exemplar-based random walk method of tooth segmentation from CBCT images. The proposed method integrates semisupervised label propagation and regularization by 3D exemplar registration. To begin with, the pure random walk method is to get an initial segmentation of the teeth, which tends to be erroneous because of the structural ambiguity of CBCT images. And then, as an iterative refinement, the authors conduct a regularization by using 3D exemplar registration, as well as label propagation by random walks with soft constraints, to improve the tooth segmentation. In the first stage of the iteration, 3D exemplars with well-defined topologies are adapted to fit the tooth contours, which are obtained from the random walks based segmentation. The soft constraints on voxel labeling are defined by shape-based foreground dentine probability acquired by the exemplar registration, as well as the appearance-based probability from a support vector machine (SVM) classifier. In the second stage, the labels of the volume-of-interest (VOI) are updated by the random walks with soft constraints. The two stages are optimized iteratively. Instead of the one-shot label propagation in the VOI, an iterative refinement process can achieve a reliable tooth segmentation by virtue of exemplar-based random walks with adaptive soft constraints. Results: The proposed method was applied for tooth segmentation of twenty clinically captured CBCT

Segmental and regional quantification of 3D cellular density of human meniscus from osteoarthritic knee.

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Cengiz, Ibrahim Fatih; Pereira, Hélder; Pêgo, José Miguel; Sousa, Nuno; Espregueira-Mendes, João; Oliveira, Joaquim Miguel; Reis, Rui Luís

2017-06-01

The knee menisci have important roles in the knee joint. Complete healing of the meniscus remains a challenge in the clinics. Cellularity is one of the most important biological parameters that must be taken into account in regenerative strategies. However, knowledge on the 3D cellularity of the human meniscus is lacking in the literature. The aim of this study was to quantify the 3D cellular density of human meniscus from the osteoarthritic knee in a segmental and regional manner with respect to laterality. Human lateral menisci were histologically processed and stained with Giemsa for histomorphometric analysis. The cells were counted in an in-depth fashion. 3D cellular density in the vascular region (27 199 cells/mm 3 ) was significantly higher than in the avascular region (12 820 cells/mm 3 ). The cells were observed to possess two distinct morphologies, roundish or flattened. The 3D density of cells with fibrochondrocyte morphology (14 705 cells/mm 3 ) was significantly greater than the 3D density of the cells with fibroblast-like cell morphology (5539 cells/mm 3 ). The best-fit equation for prediction of the 3D density of cells with fibrochondrocyte morphology was found to be: Density of cells with fibrochondrocyte morphology = 1.22 × density of cells withfibroblast-like cell morphology + 7750. The present study revealed the segmental and regional 3D cellular density of human lateral meniscus from osteoarthritic knee with respect to laterality. This crucial but so far missing information will empower cellular strategies aiming at meniscus tissue regeneration. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Automatic airline baggage counting using 3D image segmentation

Science.gov (United States)

Yin, Deyu; Gao, Qingji; Luo, Qijun

2017-06-01

The baggage number needs to be checked automatically during baggage self-check-in. A fast airline baggage counting method is proposed in this paper using image segmentation based on height map which is projected by scanned baggage 3D point cloud. There is height drop in actual edge of baggage so that it can be detected by the edge detection operator. And then closed edge chains are formed from edge lines that is linked by morphological processing. Finally, the number of connected regions segmented by closed chains is taken as the baggage number. Multi-bag experiment that is performed on the condition of different placement modes proves the validity of the method.

An efficient global energy optimization approach for robust 3D plane segmentation of point clouds

Science.gov (United States)

Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian

2018-03-01

Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)

Use of (N-1)-D expansions for N-D phase unwrapping in MRI

Science.gov (United States)

Bones, Philip J.; King, Laura J.; Millane, Rick P.

2017-09-01

In MRI the presence of metal implants causes severe artifacts in images and interferes with the usual techniques used to separate fat signals from other tissues. In the Dixon method, three images are acquired at different echo times to enable the variation in the magnetic field to be estimated. However, the estimate is represented as the phase of a complex quantity and therefore suffers from wrapping. High field gradients near the metal mean that the phase estimate is undersampled and therefore challenging to unwrap. We have developed POP, phase estimation by onion peeling, an algorithm which unwraps the phase along 1-D paths for a 2-D image obtained with the Dixon method. The unwrapping is initially performed along a closed path enclosing the implant and well separated from it. The recovered phase is expanded using a smooth periodic basis along the path. Then, path-by-path, the estimate is applied to the next path and then the expansion coefficients are estimated to best fit the wrapped measurements. We have successfully tested POP on MRI images of specially constructed phantoms and on a group of patients with hip implants. In principle, POP can be extended to 3-D imaging. In that case, POP would entail representing phase with a suitably smooth basis over a series of surfaces enclosing the implant (the "onion skins"), again beginning the phase estimation well away from the implant. An approach for this is proposed. Results are presented for fat and water separation for 2-D images of phantoms and actual patients. The practicality of the method and its employment in clinical MRI are discussed.

Automatic segmentation of MRI head images by 3-D region growing method which utilizes edge information

International Nuclear Information System (INIS)

Jiang, Hao; Suzuki, Hidetomo; Toriwaki, Jun-ichiro

1991-01-01

This paper presents a 3-D segmentation method that automatically extracts soft tissue from multi-sliced MRI head images. MRI produces a sequence of two-dimensional (2-D) images which contains three-dimensional (3-D) information of organs. To utilize such information we need effective algorithms to treat 3-D digital images and to extract organs and tissues of interest. We developed a method to extract the brain from MRI images which uses a region growing procedure and integrates information of uniformity of gray levels and information of the presence of edge segments in the local area around the pixel of interest. First we generate a kernel region which is a part of brain tissue by simple thresholding. Then we grow the region by means of a region growing algorithm under the control of 3-D edge existence to obtain the region of the brain. Our method is rather simple because it uses basic 3-D image processing techniques like spatial difference. It is robust for variation of gray levels inside a tissue since it also refers to the edge information in the process of region growing. Therefore, the method is flexible enough to be applicable to the segmentation of other images including soft tissues which have complicated shapes and fluctuation in gray levels. (author)

A spatiotemporal-based scheme for efficient registration-based segmentation of thoracic 4-D MRI.

Science.gov (United States)

Yang, Y; Van Reeth, E; Poh, C L; Tan, C H; Tham, I W K

2014-05-01

Dynamic three-dimensional (3-D) (four-dimensional, 4-D) magnetic resonance (MR) imaging is gaining importance in the study of pulmonary motion for respiratory diseases and pulmonary tumor motion for radiotherapy. To perform quantitative analysis using 4-D MR images, segmentation of anatomical structures such as the lung and pulmonary tumor is required. Manual segmentation of entire thoracic 4-D MRI data that typically contains many 3-D volumes acquired over several breathing cycles is extremely tedious, time consuming, and suffers high user variability. This requires the development of new automated segmentation schemes for 4-D MRI data segmentation. Registration-based segmentation technique that uses automatic registration methods for segmentation has been shown to be an accurate method to segment structures for 4-D data series. However, directly applying registration-based segmentation to segment 4-D MRI series lacks efficiency. Here we propose an automated 4-D registration-based segmentation scheme that is based on spatiotemporal information for the segmentation of thoracic 4-D MR lung images. The proposed scheme saved up to 95% of computation amount while achieving comparable accurate segmentations compared to directly applying registration-based segmentation to 4-D dataset. The scheme facilitates rapid 3-D/4-D visualization of the lung and tumor motion and potentially the tracking of tumor during radiation delivery.

Fast globally optimal segmentation of 3D prostate MRI with axial symmetry prior.

Science.gov (United States)

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2013-01-01

We propose a novel global optimization approach to segmenting a given 3D prostate T2w magnetic resonance (MR) image, which enforces the inherent axial symmetry of the prostate shape and simultaneously performs a sequence of 2D axial slice-wise segmentations with a global 3D coherence prior. We show that the proposed challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. With this regard, we introduce a novel coupled continuous max-flow model, which is dual to the studied convex relaxed optimization formulation and leads to an efficient multiplier augmented algorithm based on the modern convex optimization theory. Moreover, the new continuous max-flow based algorithm was implemented on GPUs to achieve a substantial improvement in computation. Experimental results using public and in-house datasets demonstrate great advantages of the proposed method in terms of both accuracy and efficiency.

Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images.

Science.gov (United States)

Pouch, Alison M; Aly, Ahmed H; Lai, Eric K; Yushkevich, Natalie; Stoffers, Rutger H; Gorman, Joseph H; Cheung, Albert T; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

2017-09-01

Transesophageal echocardiography is the primary imaging modality for preoperative assessment of mitral valves with ischemic mitral regurgitation (IMR). While there are well known echocardiographic insights into the 3D morphology of mitral valves with IMR, such as annular dilation and leaflet tethering, less is understood about how quantification of valve dynamics can inform surgical treatment of IMR or predict short-term recurrence of the disease. As a step towards filling this knowledge gap, we present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE). The framework integrates multi-atlas label fusion and template-based medial modeling to generate quantitatively descriptive models of valve dynamics. The novelty of this work is that temporal consistency in the rt-3DE segmentations is enforced during both the segmentation and modeling stages with the use of groupwise label fusion and Kalman filtering. The algorithm is evaluated on rt-3DE data series from 10 patients: five with normal mitral valve morphology and five with severe IMR. In these 10 data series that total 207 individual 3DE images, each 3DE segmentation is validated against manual tracing and temporal consistency between segmentations is demonstrated. The ultimate goal is to generate accurate and consistent representations of valve dynamics that can both visually and quantitatively provide insight into normal and pathological valve function.

Automated segmentation of blood-flow regions in large thoracic arteries using 3D-cine PC-MRI measurements.

Science.gov (United States)

van Pelt, Roy; Nguyen, Huy; ter Haar Romeny, Bart; Vilanova, Anna

2012-03-01

Quantitative analysis of vascular blood flow, acquired by phase-contrast MRI, requires accurate segmentation of the vessel lumen. In clinical practice, 2D-cine velocity-encoded slices are inspected, and the lumen is segmented manually. However, segmentation of time-resolved volumetric blood-flow measurements is a tedious and time-consuming task requiring automation. Automated segmentation of large thoracic arteries, based solely on the 3D-cine phase-contrast MRI (PC-MRI) blood-flow data, was done. An active surface model, which is fast and topologically stable, was used. The active surface model requires an initial surface, approximating the desired segmentation. A method to generate this surface was developed based on a voxel-wise temporal maximum of blood-flow velocities. The active surface model balances forces, based on the surface structure and image features derived from the blood-flow data. The segmentation results were validated using volunteer studies, including time-resolved 3D and 2D blood-flow data. The segmented surface was intersected with a velocity-encoded PC-MRI slice, resulting in a cross-sectional contour of the lumen. These cross-sections were compared to reference contours that were manually delineated on high-resolution 2D-cine slices. The automated approach closely approximates the manual blood-flow segmentations, with error distances on the order of the voxel size. The initial surface provides a close approximation of the desired luminal geometry. This improves the convergence time of the active surface and facilitates parametrization. An active surface approach for vessel lumen segmentation was developed, suitable for quantitative analysis of 3D-cine PC-MRI blood-flow data. As opposed to prior thresholding and level-set approaches, the active surface model is topologically stable. A method to generate an initial approximate surface was developed, and various features that influence the segmentation model were evaluated. The active surface

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

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/D

A fully defined and scalable 3D culture system for human pluripotent stem cell expansion and differentiation

Science.gov (United States)

Lei, Yuguo; Schaffer, David V.

2013-12-01

Human pluripotent stem cells (hPSCs), including human embryonic stem cells and induced pluripotent stem cells, are promising for numerous biomedical applications, such as cell replacement therapies, tissue and whole-organ engineering, and high-throughput pharmacology and toxicology screening. Each of these applications requires large numbers of cells of high quality; however, the scalable expansion and differentiation of hPSCs, especially for clinical utilization, remains a challenge. We report a simple, defined, efficient, scalable, and good manufacturing practice-compatible 3D culture system for hPSC expansion and differentiation. It employs a thermoresponsive hydrogel that combines easy manipulation and completely defined conditions, free of any human- or animal-derived factors, and entailing only recombinant protein factors. Under an optimized protocol, the 3D system enables long-term, serial expansion of multiple hPSCs lines with a high expansion rate (∼20-fold per 5-d passage, for a 1072-fold expansion over 280 d), yield (∼2.0 × 107 cells per mL of hydrogel), and purity (∼95% Oct4+), even with single-cell inoculation, all of which offer considerable advantages relative to current approaches. Moreover, the system enabled 3D directed differentiation of hPSCs into multiple lineages, including dopaminergic neuron progenitors with a yield of ∼8 × 107 dopaminergic progenitors per mL of hydrogel and ∼80-fold expansion by the end of a 15-d derivation. This versatile system may be useful at numerous scales, from basic biological investigation to clinical development.

SEGMENTATION OF 3D MODELS FOR CULTURAL HERITAGE STRUCTURAL ANALYSIS – SOME CRITICAL ISSUES

Directory of Open Access Journals (Sweden)

S. Gonizzi Barsanti

2017-08-01

Full Text Available Cultural Heritage documentation and preservation has become a fundamental concern in this historical period. 3D modelling offers a perfect aid to record ancient buildings and artefacts and can be used as a valid starting point for restoration, conservation and structural analysis, which can be performed by using Finite Element Methods (FEA. The models derived from reality-based techniques, made up of the exterior surfaces of the objects captured at high resolution, are - for this reason - made of millions of polygons. Such meshes are not directly usable in structural analysis packages and need to be properly pre-processed in order to be transformed in volumetric meshes suitable for FEA. In addition, dealing with ancient objects, a proper segmentation of 3D volumetric models is needed to analyse the behaviour of the structure with the most suitable level of detail for the different sections of the structure under analysis. Segmentation of 3D models is still an open issue, especially when dealing with ancient, complicated and geometrically complex objects that imply the presence of anomalies and gaps, due to environmental agents such as earthquakes, pollution, wind and rain, or human factors. The aims of this paper is to critically analyse some of the different methodologies and algorithms available to segment a 3D point cloud or a mesh, identifying difficulties and problems by showing examples on different structures.

Potencies of vitamin D analogs, 1α-hydroxyvitamin D3 , 1α-hydroxyvitamin D2 and 25-hydroxyvitamin D3 , in lowering cholesterol in hypercholesterolemic mice in vivo.

Science.gov (United States)

Quach, Holly P; Dzekic, Tamara; Bukuroshi, Paola; Pang, K Sandy

2018-04-01

Vitamin D 3 and the synthetic vitamin D analogs, 1α-hydroxyvitamin D 3 [1α(OH)D 3 ], 1α-hydroxyvitamin D 2 [1α(OH)D 2 ] and 25-hydroxyvitamin D 3 [25(OH)D 3 ] were appraised for their vitamin D receptor (VDR) associated-potencies as cholesterol lowering agents in mice in vivo. These precursors are activated in vivo: 1α(OH)D 3 and 1α(OH)D 2 are transformed by liver CYP2R1 and CYP27A1 to active VDR ligands, 1α,25-dihydroxyvitamin D 3 [1,25(OH) 2 D 3 ] and 1α,25-dihydroxyvitamin D 2 [1,25(OH) 2 D 2 ] , respectively. 1α(OH)D 2 may also be activated by CYP24A1 to 1α,24-dihydroxyvitamin D 2 [1,24(OH) 2 D 2 ], another active VDR ligand. 25(OH)D 3 , the metabolite formed via CYP2R1 and or CYP27A1 in liver from vitamin D 3 , is activated by CYP27B1 in the kidney to 1,25(OH) 2 D 3 . In C57BL/6 mice fed the high fat/high cholesterol Western diet for 3 weeks, vitamin D analogs were administered every other day intraperitoneally during the last week of the diet. The rank order for cholesterol lowering, achieved via mouse liver small heterodimer partner (Shp) inhibition and increased cholesterol 7α-hydroxylase (Cyp7a1) expression, was: 1.75 nmol/kg 1α(OH)D 3  > 1248 nmol/kg 25(OH)D 3 (dose ratio of 0.0014) > > 1625 nmol/kg vitamin D 3 . Except for 1.21 nmol/kg 1α(OH)D 2 that failed to lower liver and plasma cholesterol contents, a significant negative correlation was observed between the liver concentration of 1,25(OH) 2 D 3 formed from the precursors and liver cholesterol levels. The composite results show that vitamin D analogs 1α(OH)D 3 and 25(OH)D 3 exhibit cholesterol lowering properties upon activation to 1,25(OH) 2 D 3 : 1α(OH)D 3 is rapidly activated by liver enzymes and 25(OH)D 3 is slowly activated by renal Cyp27b1 in mouse. Copyright © 2018 John Wiley & Sons, Ltd.

Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.

Science.gov (United States)

Liu, Fang; Zhou, Zhaoye; Jang, Hyungseok; Samsonov, Alexey; Zhao, Gengyan; Kijowski, Richard

2018-04-01

To describe and evaluate a new fully automated musculoskeletal tissue segmentation method using deep convolutional neural network (CNN) and three-dimensional (3D) simplex deformable modeling to improve the accuracy and efficiency of cartilage and bone segmentation within the knee joint. A fully automated segmentation pipeline was built by combining a semantic segmentation CNN and 3D simplex deformable modeling. A CNN technique called SegNet was applied as the core of the segmentation method to perform high resolution pixel-wise multi-class tissue classification. The 3D simplex deformable modeling refined the output from SegNet to preserve the overall shape and maintain a desirable smooth surface for musculoskeletal structure. The fully automated segmentation method was tested using a publicly available knee image data set to compare with currently used state-of-the-art segmentation methods. The fully automated method was also evaluated on two different data sets, which include morphological and quantitative MR images with different tissue contrasts. The proposed fully automated segmentation method provided good segmentation performance with segmentation accuracy superior to most of state-of-the-art methods in the publicly available knee image data set. The method also demonstrated versatile segmentation performance on both morphological and quantitative musculoskeletal MR images with different tissue contrasts and spatial resolutions. The study demonstrates that the combined CNN and 3D deformable modeling approach is useful for performing rapid and accurate cartilage and bone segmentation within the knee joint. The CNN has promising potential applications in musculoskeletal imaging. Magn Reson Med 79:2379-2391, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Computer-aided segmentation system for 3D chest CT

International Nuclear Information System (INIS)

Iwasawa, Tae; Komagata, Takanobu; Ogura, Takashi; Iwao, Yuma; Goto, Toshiyuki; Asakura, Akira; Inoue, Tomio

2012-01-01

We will introduce the quantitative analysis of the chest CT images using computer-assisted segmentation system (Gaussian Histogram Normalized Correlation; GHNC). This system can divide the lung into several patterns, for example, normal, emphysema and fibrous lesion, and measure each lesion volume quantitatively. We analyzed 3D-CT images of 20 patients with lung cancer. GHNC could measure the volumes of emphysema and fibrosis lesions, respectively. GHNC analysis will be feasible for preoperative CT evaluation, especially in the patients with combined pulmonary fibrosis and emphysema. (author)

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods

DEFF Research Database (Denmark)

van der Kleij, Lisa A.; de Bresser, Jeroen; Hendrikse, Jeroen

2018-01-01

ObjectiveIn previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T-2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim...... of this study was to assess the precision of the BPV and ICV measurements of the CSF MRI sequence and to validate the CSF MRI sequence by comparison with 3D T-1-based brain segmentation methods.Materials and methodsTen healthy volunteers (2 females; median age 28 years) were scanned (3T MRI) twice......cc) and CSF HR (5 +/- 5/4 +/- 2cc) were comparable to FSL HR (9 +/- 11/19 +/- 23cc), FSL LR (7 +/- 4,6 +/- 5cc),FreeSurfer HR (5 +/- 3/14 +/- 8cc), FreeSurfer LR (9 +/- 8,12 +/- 10cc), and SPM HR (5 +/- 3/4 +/- 7cc), and SPM LR (5 +/- 4,5 +/- 3cc). The correlation between the measured volumes...

3D variational brain tumor segmentation using Dirichlet priors on a clustered feature set.

Science.gov (United States)

Popuri, Karteek; Cobzas, Dana; Murtha, Albert; Jägersand, Martin

2012-07-01

Brain tumor segmentation is a required step before any radiation treatment or surgery. When performed manually, segmentation is time consuming and prone to human errors. Therefore, there have been significant efforts to automate the process. But, automatic tumor segmentation from MRI data is a particularly challenging task. Tumors have a large diversity in shape and appearance with intensities overlapping the normal brain tissues. In addition, an expanding tumor can also deflect and deform nearby tissue. In our work, we propose an automatic brain tumor segmentation method that addresses these last two difficult problems. We use the available MRI modalities (T1, T1c, T2) and their texture characteristics to construct a multidimensional feature set. Then, we extract clusters which provide a compact representation of the essential information in these features. The main idea in this work is to incorporate these clustered features into the 3D variational segmentation framework. In contrast to previous variational approaches, we propose a segmentation method that evolves the contour in a supervised fashion. The segmentation boundary is driven by the learned region statistics in the cluster space. We incorporate prior knowledge about the normal brain tissue appearance during the estimation of these region statistics. In particular, we use a Dirichlet prior that discourages the clusters from the normal brain region to be in the tumor region. This leads to a better disambiguation of the tumor from brain tissue. We evaluated the performance of our automatic segmentation method on 15 real MRI scans of brain tumor patients, with tumors that are inhomogeneous in appearance, small in size and in proximity to the major structures in the brain. Validation with the expert segmentation labels yielded encouraging results: Jaccard (58%), Precision (81%), Recall (67%), Hausdorff distance (24 mm). Using priors on the brain/tumor appearance, our proposed automatic 3D variational

A 3D Image Filter for Parameter-Free Segmentation of Macromolecular Structures from Electron Tomograms

Science.gov (United States)

Ali, Rubbiya A.; Landsberg, Michael J.; Knauth, Emily; Morgan, Garry P.; Marsh, Brad J.; Hankamer, Ben

2012-01-01

3D image reconstruction of large cellular volumes by electron tomography (ET) at high (≤5 nm) resolution can now routinely resolve organellar and compartmental membrane structures, protein coats, cytoskeletal filaments, and macromolecules. However, current image analysis methods for identifying in situ macromolecular structures within the crowded 3D ultrastructural landscape of a cell remain labor-intensive, time-consuming, and prone to user-bias and/or error. This paper demonstrates the development and application of a parameter-free, 3D implementation of the bilateral edge-detection (BLE) algorithm for the rapid and accurate segmentation of cellular tomograms. The performance of the 3D BLE filter has been tested on a range of synthetic and real biological data sets and validated against current leading filters—the pseudo 3D recursive and Canny filters. The performance of the 3D BLE filter was found to be comparable to or better than that of both the 3D recursive and Canny filters while offering the significant advantage that it requires no parameter input or optimisation. Edge widths as little as 2 pixels are reproducibly detected with signal intensity and grey scale values as low as 0.72% above the mean of the background noise. The 3D BLE thus provides an efficient method for the automated segmentation of complex cellular structures across multiple scales for further downstream processing, such as cellular annotation and sub-tomogram averaging, and provides a valuable tool for the accurate and high-throughput identification and annotation of 3D structural complexity at the subcellular level, as well as for mapping the spatial and temporal rearrangement of macromolecular assemblies in situ within cellular tomograms. PMID:22479430

3D geomarketing segmentation: A higher spatial dimension planning perspective

DEFF Research Database (Denmark)

Suhaibah, A.; Uznir, U.; Rahman, A. A.

2016-01-01

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...... 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...

Interleaved 3D-CNNs for joint segmentation of small-volume structures in head and neck CT images.

Science.gov (United States)

Ren, Xuhua; Xiang, Lei; Nie, Dong; Shao, Yeqin; Zhang, Huan; Shen, Dinggang; Wang, Qian

2018-02-26

Accurate 3D image segmentation is a crucial step in radiation therapy planning of head and neck tumors. These segmentation results are currently obtained by manual outlining of tissues, which is a tedious and time-consuming procedure. Automatic segmentation provides an alternative solution, which, however, is often difficult for small tissues (i.e., chiasm and optic nerves in head and neck CT images) because of their small volumes and highly diverse appearance/shape information. In this work, we propose to interleave multiple 3D Convolutional Neural Networks (3D-CNNs) to attain automatic segmentation of small tissues in head and neck CT images. A 3D-CNN was designed to segment each structure of interest. To make full use of the image appearance information, multiscale patches are extracted to describe the center voxel under consideration and then input to the CNN architecture. Next, as neighboring tissues are often highly related in the physiological and anatomical perspectives, we interleave the CNNs designated for the individual tissues. In this way, the tentative segmentation result of a specific tissue can contribute to refine the segmentations of other neighboring tissues. Finally, as more CNNs are interleaved and cascaded, a complex network of CNNs can be derived, such that all tissues can be jointly segmented and iteratively refined. Our method was validated on a set of 48 CT images, obtained from the Medical Image Computing and Computer Assisted Intervention (MICCAI) Challenge 2015. The Dice coefficient (DC) and the 95% Hausdorff Distance (95HD) are computed to measure the accuracy of the segmentation results. The proposed method achieves higher segmentation accuracy (with the average DC: 0.58 ± 0.17 for optic chiasm, and 0.71 ± 0.08 for optic nerve; 95HD: 2.81 ± 1.56 mm for optic chiasm, and 2.23 ± 0.90 mm for optic nerve) than the MICCAI challenge winner (with the average DC: 0.38 for optic chiasm, and 0.68 for optic nerve; 95HD: 3.48 for

Inferring segmented dense motion layers using 5D tensor voting.

Science.gov (United States)

Min, Changki; Medioni, Gérard

2008-09-01

We present a novel local spatiotemporal approach to produce motion segmentation and dense temporal trajectories from an image sequence. A common representation of image sequences is a 3D spatiotemporal volume, (x,y,t), and its corresponding mathematical formalism is the fiber bundle. However, directly enforcing the spatiotemporal smoothness constraint is difficult in the fiber bundle representation. Thus, we convert the representation into a new 5D space (x,y,t,vx,vy) with an additional velocity domain, where each moving object produces a separate 3D smooth layer. The smoothness constraint is now enforced by extracting 3D layers using the tensor voting framework in a single step that solves both correspondence and segmentation simultaneously. Motion segmentation is achieved by identifying those layers, and the dense temporal trajectories are obtained by converting the layers back into the fiber bundle representation. We proceed to address three applications (tracking, mosaic, and 3D reconstruction) that are hard to solve from the video stream directly because of the segmentation and dense matching steps, but become straightforward with our framework. The approach does not make restrictive assumptions about the observed scene or camera motion and is therefore generally applicable. We present results on a number of data sets.

Analysis of 3-D effects in segmented cylindrical quasi-Halbach magnet arrays

NARCIS (Netherlands)

Meessen, K.J.; Paulides, J.J.H.; Lomonova, E.

2011-01-01

To improve the performance of permanent magnet (PM) machines, quasi-Halbach PM arrays are used to increase the magnetic loading in these machines. In tubular PM actuators, these arrays are often approximated using segmented magnets resulting in a 3-D magnetic field effect. This paper describes the

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

International Nuclear Information System (INIS)

Tran, Thanh N.; Nguyen, Thanh T.; Willemsz, Tofan A.; Kessel, Gijs van; Frijlink, Henderik W.; Voort Maarschalk, Kees van der

2012-01-01

Highlights: ► We revised the DBSCAN algorithm for segmentation and clustering of large 3D image dataset and classified multivariate image. ► The algorithm takes into account the coordinate system of the image data to improve the computational performance. ► The algorithm solved the instability problem in boundaries detection of the original DBSCAN. ► 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.

The Zernike expansion--an example of a merit function for 2D/3D registration based on orthogonal functions.

Science.gov (United States)

Dong, Shuo; Kettenbach, Joachim; Hinterleitner, Isabella; Bergmann, Helmar; Birkfellner, Wolfgang

2008-01-01

Current merit functions for 2D/3D registration usually rely on comparing pixels or small regions of images using some sort of statistical measure. Problems connected to this paradigm the sometimes problematic behaviour of the method if noise or artefacts (for instance a guide wire) are present on the projective image. We present a merit function for 2D/3D registration which utilizes the decomposition of the X-ray and the DRR under comparison into orthogonal Zernike moments; the quality of the match is assessed by an iterative comparison of expansion coefficients. Results in a imaging study on a physical phantom show that--compared to standard cross--correlation the Zernike moment based merit function shows better robustness if histogram content in images under comparison is different, and that time expenses are comparable if the merit function is constructed out of a few significant moments only.

Side chain requirements for affinity and specificity in D5, an HIV-1 antibody derived from the VH1-69 germline segment.

Science.gov (United States)

Stewart, Alex; Harrison, Joseph S; Regula, Lauren K; Lai, Jonathan R

2013-04-08

Analysis of factors contributing to high affinity antibody-protein interactions provides insight into natural antibody evolution, and guides the design of antibodies with new or enhanced function. We previously studied the interaction between antibody D5 and its target, a designed protein based on HIV-1 gp41 known as 5-Helix, as a model system [Da Silva, G. F.; Harrison, J. S.; Lai, J. R., Biochemistry, 2010, 49, 5464-5472]. Antibody D5 represents an interesting case study because it is derived from the VH1-69 germline segment; this germline segment is characterized by a hydrophobic second heavy chain complementarity determining region (HCDR2) that constitutes the major functional paratope in D5 and several antibodies derived from the same progenitor. Here we explore side chain requirements for affinity and specificity in D5 using phage display. Two D5-based libraries were prepared that contained diversity in all three light chain complementarity determining regions (LCDRs 1-3), and in the third HCDR (HCDR3). The first library allowed residues to vary among a restricted set of six amino acids (Tyr/Ala/Asp/Ser/His/Pro; D5-Lib-I). The second library was designed based on a survey of existing VH1-69 antibody structures (D5-Lib-II). Both libraries were subjected to multiple rounds of selection against 5-Helix, and individual clones characterized. We found that selectants from D5-Lib-I generally had moderate affinity and specificity, while many clones from D5-Lib-II exhibited D5-like properties. Additional analysis of the D5-Lib-II functional population revealed position-specific biases for particular amino acids, many that differed from the identity of those side chains in D5. Together these results suggest that there is some permissiveness for alternative side chains in the LCDRs and HCDR3 of D5, but that replacement with a minimal set of residues is not tolerated in this scaffold for 5-Helix recognition. This work provides novel information about this high

3D automatic segmentation method for retinal optical coherence tomography volume data using boundary surface enhancement

Directory of Open Access Journals (Sweden)

Yankui Sun

2016-03-01

Full Text Available With the introduction of spectral-domain optical coherence tomography (SD-OCT, much larger image datasets are routinely acquired compared to what was possible using the previous generation of time-domain OCT. Thus, there is a critical need for the development of three-dimensional (3D segmentation methods for processing these data. We present here a novel 3D automatic segmentation method for retinal OCT volume data. Briefly, to segment a boundary surface, two OCT volume datasets are obtained by using a 3D smoothing filter and a 3D differential filter. Their linear combination is then calculated to generate new volume data with an enhanced boundary surface, where pixel intensity, boundary position information, and intensity changes on both sides of the boundary surface are used simultaneously. Next, preliminary discrete boundary points are detected from the A-Scans of the volume data. Finally, surface smoothness constraints and a dynamic threshold are applied to obtain a smoothed boundary surface by correcting a small number of error points. Our method can extract retinal layer boundary surfaces sequentially with a decreasing search region of volume data. We performed automatic segmentation on eight human OCT volume datasets acquired from a commercial Spectralis OCT system, where each volume of datasets contains 97 OCT B-Scan images with a resolution of 496×512 (each B-Scan comprising 512 A-Scans containing 496 pixels; experimental results show that this method can accurately segment seven layer boundary surfaces in normal as well as some abnormal eyes.

Investigations on the quality of manual image segmentation in 3D radiotherapy planning

International Nuclear Information System (INIS)

Perelmouter, J.; Tuebingen Univ.; Bohsung, J.; Nuesslin, F.; Becker, G.; Kortmann, R.D.; Bamberg, M.

1998-01-01

In 3D radiotherapy planning image segmentation plays an important role in the definition process of target volume and organs at risk. Here, we present a method to quantify the technical precision of the manual image segmentation process. To validate our method we developed a virtual phantom consisting of several geometrical objects of changing form and contrast, which should be contoured by volunteers using the TOMAS tool for manual segmentation of the Heidelberg VOXELPLAN system. The results of this examination are presented. (orig.) [de

Automated segmentation and geometrical modeling of the tricuspid aortic valve in 3D echocardiographic images.

Science.gov (United States)

Pouch, Alison M; Wang, Hongzhi; Takabe, Manabu; Jackson, Benjamin M; Sehgal, Chandra M; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

2013-01-01

The aortic valve has been described with variable anatomical definitions, and the consistency of 2D manual measurement of valve dimensions in medical image data has been questionable. Given the importance of image-based morphological assessment in the diagnosis and surgical treatment of aortic valve disease, there is considerable need to develop a standardized framework for 3D valve segmentation and shape representation. Towards this goal, this work integrates template-based medial modeling and multi-atlas label fusion techniques to automatically delineate and quantitatively describe aortic leaflet geometry in 3D echocardiographic (3DE) images, a challenging task that has been explored only to a limited extent. The method makes use of expert knowledge of aortic leaflet image appearance, generates segmentations with consistent topology, and establishes a shape-based coordinate system on the aortic leaflets that enables standardized automated measurements. In this study, the algorithm is evaluated on 11 3DE images of normal human aortic leaflets acquired at mid systole. The clinical relevance of the method is its ability to capture leaflet geometry in 3DE image data with minimal user interaction while producing consistent measurements of 3D aortic leaflet geometry.

Efficient 3D multi-region prostate MRI segmentation using dual optimization.

Science.gov (United States)

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2013-01-01

Efficient and accurate extraction of the prostate, in particular its clinically meaningful sub-regions from 3D MR images, is of great interest in image-guided prostate interventions and diagnosis of prostate cancer. In this work, we propose a novel multi-region segmentation approach to simultaneously locating the boundaries of the prostate and its two major sub-regions: the central gland and the peripheral zone. The proposed method utilizes the prior knowledge of the spatial region consistency and employs a customized prostate appearance model to simultaneously segment multiple clinically meaningful regions. We solve the resulted challenging combinatorial optimization problem by means of convex relaxation, for which we introduce a novel spatially continuous flow-maximization model and demonstrate its duality to the investigated convex relaxed optimization problem with the region consistency constraint. Moreover, the proposed continuous max-flow model naturally leads to a new and efficient continuous max-flow based algorithm, which enjoys great advantages in numerics and can be readily implemented on GPUs. Experiments using 15 T2-weighted 3D prostate MR images, by inter- and intra-operator variability, demonstrate the promising performance of the proposed approach.

New approach for validating the segmentation of 3D data applied to individual fibre extraction

DEFF Research Database (Denmark)

Emerson, Monica Jane; Dahl, Anders Bjorholm; Dahl, Vedrana Andersen

2017-01-01

We present two approaches for validating the segmentation of 3D data. The first approach consists on comparing the amount of estimated material to a value provided by the manufacturer. The second approach consists on comparing the segmented results to those obtained from imaging modalities...

Aortic root segmentation in 4D transesophageal echocardiography

Science.gov (United States)

Chechani, Shubham; Suresh, Rahul; Patwardhan, Kedar A.

2018-02-01

The Aortic Valve (AV) is an important anatomical structure which lies on the left side of the human heart. The AV regulates the flow of oxygenated blood from the Left Ventricle (LV) to the rest of the body through aorta. Pathologies associated with the AV manifest themselves in structural and functional abnormalities of the valve. Clinical management of pathologies often requires repair, reconstruction or even replacement of the valve through surgical intervention. Assessment of these pathologies as well as determination of specific intervention procedure requires quantitative evaluation of the valvular anatomy. 4D (3D + t) Transesophageal Echocardiography (TEE) is a widely used imaging technique that clinicians use for quantitative assessment of cardiac structures. However, manual quantification of 3D structures is complex, time consuming and suffers from inter-observer variability. Towards this goal, we present a semiautomated approach for segmentation of the aortic root (AR) structure. Our approach requires user-initialized landmarks in two reference frames to provide AR segmentation for full cardiac cycle. We use `coarse-to-fine' B-spline Explicit Active Surface (BEAS) for AR segmentation and Masked Normalized Cross Correlation (NCC) method for AR tracking. Our method results in approximately 0.51 mm average localization error in comparison with ground truth annotation performed by clinical experts on 10 real patient cases (139 3D volumes).

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

International Nuclear Information System (INIS)

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 [fr

Automated volume analysis of head and neck lesions on CT scans using 3D level set segmentation

International Nuclear Information System (INIS)

Street, Ethan; Hadjiiski, Lubomir; Sahiner, Berkman; Gujar, Sachin; Ibrahim, Mohannad; Mukherji, Suresh K.; Chan, Heang-Ping

2007-01-01

The authors have developed a semiautomatic system for segmentation of a diverse set of lesions in head and neck CT scans. The system takes as input an approximate bounding box, and uses a multistage level set to perform the final segmentation. A data set consisting of 69 lesions marked on 33 scans from 23 patients was used to evaluate the performance of the system. The contours from automatic segmentation were compared to both 2D and 3D gold standard contours manually drawn by three experienced radiologists. Three performance metric measures were used for the comparison. In addition, a radiologist provided quality ratings on a 1 to 10 scale for all of the automatic segmentations. For this pilot study, the authors observed that the differences between the automatic and gold standard contours were larger than the interobserver differences. However, the system performed comparably to the radiologists, achieving an average area intersection ratio of 85.4% compared to an average of 91.2% between two radiologists. The average absolute area error was 21.1% compared to 10.8%, and the average 2D distance was 1.38 mm compared to 0.84 mm between the radiologists. In addition, the quality rating data showed that, despite the very lax assumptions made on the lesion characteristics in designing the system, the automatic contours approximated many of the lesions very well

Automated bone segmentation from large field of view 3D MR images of the hip joint

International Nuclear Information System (INIS)

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-01-01

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head–neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone–cartilage interfaces for potential cartilage segmentation. (paper)

Automated bone segmentation from large field of view 3D MR images of the hip joint

Science.gov (United States)

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S.; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-10-01

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.

D{sub s1}{sup *}(2860) and D{sub s3}{sup *}(2860): candidates for 1D charmed-strange mesons

Energy Technology Data Exchange (ETDEWEB)

Song, Qin-Tao [Chinese Academy of Sciences, Nuclear Theory Group, Institute of Modern Physics, Lanzhou (China); Lanzhou University and Institute of Modern Physics of CAS, Research Center for Hadron and CSR Physics, Lanzhou (China); University of Chinese Academy of Sciences, Beijing (China); Chen, Dian-Yong [Chinese Academy of Sciences, Nuclear Theory Group, Institute of Modern Physics, Lanzhou (China); Lanzhou University and Institute of Modern Physics of CAS, Research Center for Hadron and CSR Physics, Lanzhou (China); Liu, Xiang [Lanzhou University and Institute of Modern Physics of CAS, Research Center for Hadron and CSR Physics, Lanzhou (China); Lanzhou University, School of Physical Science and Technology, Lanzhou (China); Matsuki, Takayuki [Tokyo Kasei University, Tokyo (Japan); RIKEN, Theoretical Research Division, Nishina Center, Saitama (Japan)

2015-01-01

Newly observed two charmed-strange resonances, D{sub s1}{sup *}(2860) and D{sub s3}{sup *}(2860), are investigated by calculating their Okubo-Zweig-Iizuka-allowed strong decays, which shows that they are suitable candidates for the 1{sup 3}D{sub 1} and 1{sup 3}D{sub 3} states in the charmed-strange meson family. Our study also predicts other main decay modes of D{sub s1}{sup *}(2860) and D{sub s3}{sup *}(2860), which can be accessible at the future experiment. In addition, the decay behaviors of the spin partners of D{sub s1}{sup *}(2860) and D{sub s3}{sup *}(2860), i.e., 1D(2{sup -}) and 1D'(2{sup -}), are predicted in this work, which are still missing at present. The experimental search for the missing 1D(2{sup -}) and 1D'(2{sup -}) charmed-strange mesons is an intriguing and challenging task for further experiments. (orig.)

Hepatic vessel segmentation for 3D planning of liver surgery experimental evaluation of a new fully automatic algorithm.

Science.gov (United States)

Conversano, Francesco; Franchini, Roberto; Demitri, Christian; Massoptier, Laurent; Montagna, Francesco; Maffezzoli, Alfonso; Malvasi, Antonio; Casciaro, Sergio

2011-04-01

The aim of this study was to identify the optimal parameter configuration of a new algorithm for fully automatic segmentation of hepatic vessels, evaluating its accuracy in view of its use in a computer system for three-dimensional (3D) planning of liver surgery. A phantom reproduction of a human liver with vessels up to the fourth subsegment order, corresponding to a minimum diameter of 0.2 mm, was realized through stereolithography, exploiting a 3D model derived from a real human computed tomographic data set. Algorithm parameter configuration was experimentally optimized, and the maximum achievable segmentation accuracy was quantified for both single two-dimensional slices and 3D reconstruction of the vessel network, through an analytic comparison of the automatic segmentation performed on contrast-enhanced computed tomographic phantom images with actual model features. The optimal algorithm configuration resulted in a vessel detection sensitivity of 100% for vessels > 1 mm in diameter, 50% in the range 0.5 to 1 mm, and 14% in the range 0.2 to 0.5 mm. An average area overlap of 94.9% was obtained between automatically and manually segmented vessel sections, with an average difference of 0.06 mm(2). The average values of corresponding false-positive and false-negative ratios were 7.7% and 2.3%, respectively. A robust and accurate algorithm for automatic extraction of the hepatic vessel tree from contrast-enhanced computed tomographic volume images was proposed and experimentally assessed on a liver model, showing unprecedented sensitivity in vessel delineation. This automatic segmentation algorithm is promising for supporting liver surgery planning and for guiding intraoperative resections. Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.

Accurate and reproducible reconstruction of coronary arteries and endothelial shear stress calculation using 3D OCT: comparative study to 3D IVUS and 3D QCA.

Science.gov (United States)

Toutouzas, Konstantinos; Chatzizisis, Yiannis S; Riga, Maria; Giannopoulos, Andreas; Antoniadis, Antonios P; Tu, Shengxian; Fujino, Yusuke; Mitsouras, Dimitrios; Doulaverakis, Charalampos; Tsampoulatidis, Ioannis; Koutkias, Vassilis G; Bouki, Konstantina; Li, Yingguang; Chouvarda, Ioanna; Cheimariotis, Grigorios; Maglaveras, Nicos; Kompatsiaris, Ioannis; Nakamura, Sunao; Reiber, Johan H C; Rybicki, Frank; Karvounis, Haralambos; Stefanadis, Christodoulos; Tousoulis, Dimitris; Giannoglou, George D

2015-06-01

Geometrically-correct 3D OCT is a new imaging modality with the potential to investigate the association of local hemodynamic microenvironment with OCT-derived high-risk features. We aimed to describe the methodology of 3D OCT and investigate the accuracy, inter- and intra-observer agreement of 3D OCT in reconstructing coronary arteries and calculating ESS, using 3D IVUS and 3D QCA as references. 35 coronary artery segments derived from 30 patients were reconstructed in 3D space using 3D OCT. 3D OCT was validated against 3D IVUS and 3D QCA. The agreement in artery reconstruction among 3D OCT, 3D IVUS and 3D QCA was assessed in 3-mm-long subsegments using lumen morphometry and ESS parameters. The inter- and intra-observer agreement of 3D OCT, 3D IVUS and 3D QCA were assessed in a representative sample of 61 subsegments (n = 5 arteries). The data processing times for each reconstruction methodology were also calculated. There was a very high agreement between 3D OCT vs. 3D IVUS and 3D OCT vs. 3D QCA in terms of total reconstructed artery length and volume, as well as in terms of segmental morphometric and ESS metrics with mean differences close to zero and narrow limits of agreement (Bland-Altman analysis). 3D OCT exhibited excellent inter- and intra-observer agreement. The analysis time with 3D OCT was significantly lower compared to 3D IVUS. Geometrically-correct 3D OCT is a feasible, accurate and reproducible 3D reconstruction technique that can perform reliable ESS calculations in coronary arteries. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluation of multimodal segmentation based on 3D T1-, T2- and FLAIR-weighted images - the difficulty of choosing.

Science.gov (United States)

Lindig, Tobias; Kotikalapudi, Raviteja; Schweikardt, Daniel; Martin, Pascal; Bender, Friedemann; Klose, Uwe; Ernemann, Ulrike; Focke, Niels K; Bender, Benjamin

2018-04-15

Voxel-based morphometry is still mainly based on T1-weighted MRI scans. Misclassification of vessels and dura mater as gray matter has been previously reported. Goal of the present work was to evaluate the effect of multimodal segmentation methods available in SPM12, and their influence on identification of age related atrophy and lesion detection in epilepsy patients. 3D T1-, T2- and FLAIR-images of 77 healthy adults (mean age 35.8 years, 19-66 years, 45 females), 7 patients with malformation of cortical development (MCD) (mean age 28.1 years,19-40 years, 3 females), and 5 patients with left hippocampal sclerosis (LHS) (mean age 49.0 years, 25-67 years, 3 females) from a 3T scanner were evaluated. Segmentation based on T1-only, T1+T2, T1+FLAIR, T2+FLAIR, and T1+T2+FLAIR were compared in the healthy subjects. Clinical VBM results based on the different segmentation approaches for MCD and for LHS were compared. T1-only segmentation overestimated total intracranial volume by about 80ml compared to the other segmentation methods. This was due to misclassification of dura mater and vessels as GM and CSF. Significant differences were found for several anatomical regions: the occipital lobe, the basal ganglia/thalamus, the pre- and postcentral gyrus, the cerebellum, and the brainstem. None of the segmentation methods yielded completely satisfying results for the basal ganglia/thalamus and the brainstem. The best correlation with age could be found for the multimodal T1+T2+FLAIR segmentation. Highest T-scores for identification of LHS were found for T1+T2 segmentation, while highest T-scores for MCD were dependent on lesion and anatomical location. Multimodal segmentation is superior to T1-only segmentation and reduces the misclassification of dura mater and vessels as GM and CSF. Depending on the anatomical region and the pathology of interest (atrophy, lesion detection, etc.), different combinations of T1, T2 and FLAIR yield optimal results. Copyright © 2017 Elsevier

Quantitative studies of the brain specific antigens GFA, 14-3-2, synaptin C1, D1, D2, D3 and D5 in jimpy mouse

DEFF Research Database (Denmark)

Jacque, C M; Baumann, N A; Bock, E

1976-01-01

Seven antigens specific to the nervous tissue were measured in both Jimpy and control mice. The D5 and the GFA protein, both components of the glia, are strongly increased in the mutant while the neuronal components 14-3-2, synaptin C1, D1, D2 and D3 are unchanged....

Network level pavement evaluation with 1 mm 3D survey system

Directory of Open Access Journals (Sweden)

Kelvin C.P. Wang

2015-12-01

Full Text Available The latest iteration of PaveVision3D Ultra can obtain true 1 mm resolution 3D data at full-lane coverage in all 3 directions at highway speed up to 60 mph. This paper introduces the PaveVision3D Ultra technology for rapid network level pavement survey on approximately 1280 center miles of Oklahoma interstate highways. With sophisticated automated distress analyzer (ADA software interface, the collected 1 mm 3D data provide Oklahoma Department of Transportation (ODOT with comprehensive solutions for automated evaluation of pavement surface including longitudinal profile for roughness, transverse profile for rutting, predicted hydroplaning speed for safety analysis, and cracking and various surface defects for distresses. The pruned exact linear time (PELT method, an optimal partitioning algorithm, is implemented to identify change points and dynamically determine homogeneous segments so as to assist ODOT effectively using the available 1 mm 3D pavement surface condition data for decision-making. The application of 1 mm 3D laser imaging technology for network survey is unprecedented. This innovative technology allows highway agencies to access its options in using the 1 mm 3D system for its design and management purposes, particularly to meet the data needs for pavement management system (PMS, pavement ME design and highway performance monitoring system (HPMS.

Communication: Studies of the Lennard-Jones fluid in 2, 3, and 4 dimensions highlight the need for a liquid-state 1/d expansion

International Nuclear Information System (INIS)

Costigliola, Lorenzo; Schrøder, Thomas B.; Dyre, Jeppe C.

2016-01-01

The recent theoretical prediction by Maimbourg and Kurchan [e-print http://arxiv.org/abs/1603.05023 (2016)] that for regular pair-potential systems the virial potential-energy correlation coefficient increases towards unity as the dimension d goes to infinity is investigated for the standard 12-6 Lennard-Jones fluid. This is done by computer simulations for d = 2, 3, 4 going from the critical point along the critical isotherm/isochore to higher density/temperature. In both cases the virial potential-energy correlation coefficient increases significantly. For a given density and temperature relative to the critical point, with increasing number of dimension the Lennard-Jones system conforms better to the hidden-scale-invariance property characterized by high virial potential-energy correlations (a property that leads to the existence of isomorphs in the thermodynamic phase diagram, implying that it becomes effectively one-dimensional in regard to structure and dynamics). The present paper also gives the first numerical demonstration of isomorph invariance of structure and dynamics in four dimensions. Our findings emphasize the need for a universally applicable 1/d expansion in liquid-state theory; we conjecture that the systems known to obey hidden scale invariance in three dimensions are those for which the yet-to-be-developed 1/d expansion converges rapidly.

Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model

Energy Technology Data Exchange (ETDEWEB)

He, Baochun; Huang, Cheng; Zhou, Shoujun; Hu, Qingmao; Jia, Fucang, E-mail: fc.jia@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055 (China); Sharp, Gregory [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114 (United States); Fang, Chihua; Fan, Yingfang [Department of Hepatology (I), Zhujiang Hospital, Southern Medical University, Guangzhou 510280 (China)

2016-05-15

Purpose: A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. Methods: The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods—3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration—are used to establish shape correspondence. Results: The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. Conclusions: The proposed automatic approach

Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model.

Science.gov (United States)

He, Baochun; Huang, Cheng; Sharp, Gregory; Zhou, Shoujun; Hu, Qingmao; Fang, Chihua; Fan, Yingfang; Jia, Fucang

2016-05-01

A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods-3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration-are used to establish shape correspondence. The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. The proposed automatic approach achieves robust, accurate, and fast liver

Differences in 3D vs. 2D analysis in lumbar spinal fusion simulations.

Science.gov (United States)

Hsu, Hung-Wei; Bashkuev, Maxim; Pumberger, Matthias; Schmidt, Hendrik

2018-04-27

Lumbar interbody fusion is currently the gold standard in treating patients with disc degeneration or segmental instability. Despite it having been used for several decades, the non-union rate remains high. A failed fusion is frequently attributed to an inadequate mechanical environment after instrumentation. Finite element (FE) models can provide insights into the mechanics of the fusion process. Previous fusion simulations using FE models showed that the geometries and material of the cage can greatly influence the fusion outcome. However, these studies used axisymmetric models which lacked realistic spinal geometries. Therefore, different modeling approaches were evaluated to understand the bone-formation process. Three FE models of the lumbar motion segment (L4-L5) were developed: 2D, Sym-3D and Nonsym-3D. The fusion process based on existing mechano-regulation algorithms using the FE simulations to evaluate the mechanical environment was then integrated into these models. In addition, the influence of different lordotic angles (5, 10 and 15°) was investigated. The volume of newly formed bone, the axial stiffness of the whole segment and bone distribution inside and surrounding the cage were evaluated. In contrast to the Nonsym-3D, the 2D and Sym-3D models predicted excessive bone formation prior to bridging (peak values with 36 and 9% higher than in equilibrium, respectively). The 3D models predicted a more uniform bone distribution compared to the 2D model. The current results demonstrate the crucial role of the realistic 3D geometry of the lumbar motion segment in predicting bone formation after lumbar spinal fusion. Copyright © 2018 Elsevier Ltd. All rights reserved.

Strong coupling expansion for scattering phases in hamiltonian lattice field theories. Pt. 1. The (d+1)-dimensional Ising model

International Nuclear Information System (INIS)

Dahmen, Bernd

1994-01-01

A systematic method to obtain strong coupling expansions for scattering quantities in hamiltonian lattice field theories is presented. I develop the conceptual ideas for the case of the hamiltonian field theory analogue of the Ising model, in d space and one time dimension. The main result is a convergent series representation for the scattering states and the transition matrix. To be explicit, the special cases of d=1 and d=3 spatial dimensions are discussed in detail. I compute the next-to-leading order approximation for the phase shifts. The application of the method to investigate low-energy scattering phenomena in lattice gauge theory and QCD is proposed. ((orig.))

Segmentation process significantly influences the accuracy of 3D surface models derived from cone beam computed tomography

NARCIS (Netherlands)

Fourie, Zacharias; Damstra, Janalt; Schepers, Rutger H; Gerrits, Pieter; Ren, Yijin

AIMS: To assess the accuracy of surface models derived from 3D cone beam computed tomography (CBCT) with two different segmentation protocols. MATERIALS AND METHODS: Seven fresh-frozen cadaver heads were used. There was no conflict of interests in this study. CBCT scans were made of the heads and 3D

Esophagus segmentation in CT via 3D fully convolutional neural network and random walk.

Science.gov (United States)

Fechter, Tobias; Adebahr, Sonja; Baltas, Dimos; Ben Ayed, Ismail; Desrosiers, Christian; Dolz, Jose

2017-12-01

Precise delineation of organs at risk is a crucial task in radiotherapy treatment planning for delivering high doses to the tumor while sparing healthy tissues. In recent years, automated segmentation methods have shown an increasingly high performance for the delineation of various anatomical structures. However, this task remains challenging for organs like the esophagus, which have a versatile shape and poor contrast to neighboring tissues. For human experts, segmenting the esophagus from CT images is a time-consuming and error-prone process. To tackle these issues, we propose a random walker approach driven by a 3D fully convolutional neural network (CNN) to automatically segment the esophagus from CT images. First, a soft probability map is generated by the CNN. Then, an active contour model (ACM) is fitted to the CNN soft probability map to get a first estimation of the esophagus location. The outputs of the CNN and ACM are then used in conjunction with a probability model based on CT Hounsfield (HU) values to drive the random walker. Training and evaluation were done on 50 CTs from two different datasets, with clinically used peer-reviewed esophagus contours. Results were assessed regarding spatial overlap and shape similarity. The esophagus contours generated by the proposed algorithm showed a mean Dice coefficient of 0.76 ± 0.11, an average symmetric square distance of 1.36 ± 0.90 mm, and an average Hausdorff distance of 11.68 ± 6.80, compared to the reference contours. These results translate to a very good agreement with reference contours and an increase in accuracy compared to existing methods. Furthermore, when considering the results reported in the literature for the publicly available Synapse dataset, our method outperformed all existing approaches, which suggests that the proposed method represents the current state-of-the-art for automatic esophagus segmentation. We show that a CNN can yield accurate estimations of esophagus location, and that

3D knee segmentation based on three MRI sequences from different planes.

Science.gov (United States)

Zhou, L; Chav, R; Cresson, T; Chartrand, G; de Guise, J

2016-08-01

In clinical practice, knee MRI sequences with 3.5~5 mm slice distance in sagittal, coronal, and axial planes are often requested for the knee examination since its acquisition is faster than high-resolution MRI sequence in a single plane, thereby reducing the probability of motion artifact. In order to take advantage of the three sequences from different planes, a 3D segmentation method based on the combination of three knee models obtained from the three sequences is proposed in this paper. In the method, the sub-segmentation is respectively performed with sagittal, coronal, and axial MRI sequence in the image coordinate system. With each sequence, an initial knee model is hierarchically deformed, and then the three deformed models are mapped to reference coordinate system defined by the DICOM standard and combined to obtain a patient-specific model. The experimental results verified that the three sub-segmentation results can complement each other, and their integration can compensate for the insufficiency of boundary information caused by 3.5~5 mm gap between consecutive slices. Therefore, the obtained patient-specific model is substantially more accurate than each sub-segmentation results.

3D Reasoning from Blocks to Stability.

Science.gov (United States)

Zhaoyin Jia; Gallagher, Andrew C; Saxena, Ashutosh; Chen, Tsuhan

2015-05-01

Objects occupy physical space and obey physical laws. To truly understand a scene, we must reason about the space that objects in it occupy, and how each objects is supported stably by each other. In other words, we seek to understand which objects would, if moved, cause other objects to fall. This 3D volumetric reasoning is important for many scene understanding tasks, ranging from segmentation of objects to perception of a rich 3D, physically well-founded, interpretations of the scene. In this paper, we propose a new algorithm to parse a single RGB-D image with 3D block units while jointly reasoning about the segments, volumes, supporting relationships, and object stability. Our algorithm is based on the intuition that a good 3D representation of the scene is one that fits the depth data well, and is a stable, self-supporting arrangement of objects (i.e., one that does not topple). We design an energy function for representing the quality of the block representation based on these properties. Our algorithm fits 3D blocks to the depth values corresponding to image segments, and iteratively optimizes the energy function. Our proposed algorithm is the first to consider stability of objects in complex arrangements for reasoning about the underlying structure of the scene. Experimental results show that our stability-reasoning framework improves RGB-D segmentation and scene volumetric representation.

A new picture on the (3+1)D topological mass mechanism

International Nuclear Information System (INIS)

Ventura, O S; Amaral, R L P G; Costa, J V; Buffon, L O; Lemes, V E R

2004-01-01

We present a class of mappings between the fields of the Cremmer-Sherk and pure BF models in 4D. These mappings are established by two distinct procedures. First, a mapping of their actions is produced iteratively resulting in an expansion of the fields of one model in terms of progressively higher derivatives of the other model fields. Second, an exact mapping is introduced by mapping their quantum correlation functions. The equivalence of both procedures is shown by resorting to the invariance under field scale transformations of the topological action. Related equivalences in 5D and 3D are discussed. The mapping in (2+1)D from the Maxwell-Chern-Simons to pure Chern-Simons models is investigated from a similar perspective

Using one hybrid 3D-1D-3D approach for the conceptual design of WCCB blanket for CFETR

Energy Technology Data Exchange (ETDEWEB)

Jiang, Kecheng; Zhang, Xiaokang [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui, 230031 (China); University of Science and Technology of China, Hefei, Anhui, 230027 (China); Li, Jia [University of Science and Technology of China, Hefei, Anhui, 230027 (China); Ma, Xuebin [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui, 230031 (China); University of Science and Technology of China, Hefei, Anhui, 230027 (China); Liu, Songlin, E-mail: slliu@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui, 230031 (China); University of Science and Technology of China, Hefei, Anhui, 230027 (China)

2017-01-15

Highlights: • The Hybrid 3D-1D-3D approach is used for radial building design of WCCB. • Nuclear heat obtained by this method agrees well with 3D neutronics results. • The final results of temperature and TBR satisfy with the requirements. • All the results show that this approach is high efficiency and high reliability. - Abstract: A hybrid 3D-1D-3D approach is proposed for the conceptual design of a blanket. Firstly, the neutron wall loading (NWL) of each blanket module is obtained through a neutronics calculation employing a 3D model, which contains the geometry outline of in-vacuum vessel components and the exact neutron source distribution. Secondly, a 1D cylindrical model with the blanket module containing a detailed radial building is adopted for the neutronics analysis, with the aim of calculating the tritium breeding ratio (TBR) and nuclear heating. Being normalized to the NWL, the nuclear heating is transferred to a 2D model for thermal-hydraulics analysis using the FLUENT code. Through a series analysis of nuclear-thermal iterations that considers the tritium breeding ratio (TBR) and thermal performance as optimization objectives, the optimized radial building of each module surrounding plasma can be obtained. Thirdly, the 3D structural design of each module is established by adding side walls, cover plates, stiffening plates, and other components based on the radial building. The 3D neutronics and thermal-hydraulics using the detailed blanket modules are re-analyzed. This approach has been successfully applied to the design of a water-cooled ceramic breeder blanket for the Chinese Fusion Engineering Test Reactor (CFETR). The radial building of each blanket module surrounding plasma is optimized. The global tritium breeding ratio (TBR) calculated by the 3D neutronics analysis is 1.21, and the temperature of all materials in the 3D blanket structure is below the upper limits. As indicated by the comparison of the 1D and 3D neutronics and thermal

3D marker-controlled watershed for kidney segmentation in clinical CT exams.

Science.gov (United States)

Wieclawek, Wojciech

2018-02-27

Image segmentation is an essential and non trivial task in computer vision and medical image analysis. Computed tomography (CT) is one of the most accessible medical examination techniques to visualize the interior of a patient's body. Among different computer-aided diagnostic systems, the applications dedicated to kidney segmentation represent a relatively small group. In addition, literature solutions are verified on relatively small databases. The goal of this research is to develop a novel algorithm for fully automated kidney segmentation. This approach is designed for large database analysis including both physiological and pathological cases. This study presents a 3D marker-controlled watershed transform developed and employed for fully automated CT kidney segmentation. The original and the most complex step in the current proposition is an automatic generation of 3D marker images. The final kidney segmentation step is an analysis of the labelled image obtained from marker-controlled watershed transform. It consists of morphological operations and shape analysis. The implementation is conducted in a MATLAB environment, Version 2017a, using i.a. Image Processing Toolbox. 170 clinical CT abdominal studies have been subjected to the analysis. The dataset includes normal as well as various pathological cases (agenesis, renal cysts, tumors, renal cell carcinoma, kidney cirrhosis, partial or radical nephrectomy, hematoma and nephrolithiasis). Manual and semi-automated delineations have been used as a gold standard. Wieclawek Among 67 delineated medical cases, 62 cases are 'Very good', whereas only 5 are 'Good' according to Cohen's Kappa interpretation. The segmentation results show that mean values of Sensitivity, Specificity, Dice, Jaccard, Cohen's Kappa and Accuracy are 90.29, 99.96, 91.68, 85.04, 91.62 and 99.89% respectively. All 170 medical cases (with and without outlines) have been classified by three independent medical experts as 'Very good' in 143

Comparison of post-contrast 3D-T1-MPRAGE, 3D-T1-SPACE and 3D-T2-FLAIR MR images in evaluation of meningeal abnormalities at 3-T MRI.

Science.gov (United States)

Jeevanandham, Balaji; Kalyanpur, Tejas; Gupta, Prashant; Cherian, Mathew

2017-06-01

This study was to assess the usefulness of newer three-dimensional (3D)-T 1 sampling perfection with application optimized contrast using different flip-angle evolutions (SPACE) and 3D-T 2 fluid-attenuated inversion recovery (FLAIR) sequences in evaluation of meningeal abnormalities. 78 patients who presented with high suspicion of meningeal abnormalities were evaluated using post-contrast 3D-T 2 -FLAIR, 3D-T 1 magnetization-prepared rapid gradient-echo (MPRAGE) and 3D-T 1 -SPACE sequences. The images were evaluated independently by two radiologists for cortical gyral, sulcal space, basal cisterns and dural enhancement. The diagnoses were confirmed by further investigations including histopathology. Post-contrast 3D-T 1 -SPACE and 3D-T 2 -FLAIR images yielded significantly more information than MPRAGE images (p evaluation of meningeal abnormalities and when used in combination have the maximum sensitivity for leptomeningeal abnormalities. The negative-predictive value is nearly 100%, where no leptomeningeal abnormality was detected on these sequences. Advances in knowledge: Post-contrast 3D-T 1 -SPACE and 3D-T 2 -FLAIR images are more useful than 3D-T 1 -MPRAGE images in evaluation of meningeal abnormalities.

REGISTRATION OF OVERLAPPING 3D POINT CLO UDS USING EXTRACTED LINE SEGMENTS

Directory of Open Access Journals (Sweden)

Poręba Martyna

2014-12-01

Full Text Available The registration of 3D point clouds collected from different scanner positions is necessary in order to avoid occlusions, ensure a full coverage of areas, and collect useful data for analyzing an d documenting the surrounding environment. This procedure involves three main stages: 1 choosing appropriate features, which can be reliably extracted; 2 matching conjugate primitives; 3 estimating the transformation parameters. Currently, points and spheres are most frequently chosen as the registration features. However, due to limited point cloud resolution, proper identification and precise measurement of a common point within the overlapping laser data is almost impossible. One possible solution to this problem may be a registration process based on the Iterative Closest Point (ICP algorithm or its variation. Alternatively, planar and linear feature - based registration techniques can also be applied. In this paper, we propose the use of line segments obtained from intersecting planes modelled within individual scans. Such primitives can be easily extracted even from low - density point clouds. Working with synthetic data, several existing line - based registration methods are evaluated according to their robustness to noise and the precision of the estimated transformation parameters. For the purpose of quantitative assessment, an accuracy criterion based on a modified Hausdorff distance is defined. Since a n automated matching of segments is a challenging task that influences the correctness of the transformation parameters, a correspondence - finding algorithm is developed. The tests show that our matching algorithm provides a correct pairing with an accuracy of 99 % at least, and about 8% of omitted line pairs.

D{sub s1}{sup ∗}(2860) and D{sub s3}{sup ∗}(2860): candidates for 1D charmed-strange mesons

Energy Technology Data Exchange (ETDEWEB)

Song, Qin-Tao [Nuclear Theory Group, Institute of Modern Physics, Chinese Academy of Sciences, 730000, Lanzhou (China); Research Center for Hadron and CSR Physics, Lanzhou University & Institute of Modern Physics of CAS, 730000, Lanzhou (China); University of Chinese Academy of Sciences, 100049, Beijing (China); Chen, Dian-Yong, E-mail: chendy@impcas.ac.cn [Nuclear Theory Group, Institute of Modern Physics, Chinese Academy of Sciences, 730000, Lanzhou (China); Research Center for Hadron and CSR Physics, Lanzhou University & Institute of Modern Physics of CAS, 730000, Lanzhou (China); Liu, Xiang, E-mail: xiangliu@lzu.edu.cn [Research Center for Hadron and CSR Physics, Lanzhou University & Institute of Modern Physics of CAS, 730000, Lanzhou (China); School of Physical Science and Technology, Lanzhou University, 730000, Lanzhou (China); Matsuki, Takayuki, E-mail: matsuki@tokyo-kasei.ac.jp [Tokyo Kasei University, 1-18-1 Kaga, Itabashi, 173-8602, Tokyo (Japan); Theoretical Research Division, Nishina Center, RIKEN, 351-0198, Saitama (Japan)

2015-01-27

Newly observed two charmed-strange resonances, D{sub s1}{sup ∗}(2860) and D{sub s3}{sup ∗}(2860), are investigated by calculating their Okubo–Zweig–Iizuka-allowed strong decays, which shows that they are suitable candidates for the 1{sup 3}D{sub 1} and 1{sup 3}D{sub 3} states in the charmed-strange meson family. Our study also predicts other main decay modes of D{sub s1}{sup ∗}(2860) and D{sub s3}{sup ∗}(2860), which can be accessible at the future experiment. In addition, the decay behaviors of the spin partners of D{sub s1}{sup ∗}(2860) and D{sub s3}{sup ∗}(2860), i.e., 1D(2{sup -}) and 1D{sup ′}(2{sup -}), are predicted in this work, which are still missing at present. The experimental search for the missing 1D(2{sup -}) and 1D{sup ′}(2{sup -}) charmed-strange mesons is an intriguing and challenging task for further experiments.

Facilitating coronary artery evaluation in MDCT using a 3D automatic vessel segmentation tool

International Nuclear Information System (INIS)

Fawad Khan, M.; Gurung, Jessen; Maataoui, Adel; Brehmer, Boris; Herzog, Christopher; Vogl, Thomas J.; Wesarg, Stefan; Dogan, Selami; Ackermann, Hanns; Assmus, Birgit

2006-01-01

The purpose of this study was to investigate a 3D coronary artery segmentation algorithm using 16-row MDCT data sets. Fifty patients underwent cardiac CT (Sensation 16, Siemens) and coronary angiography. Automatic and manual detection of coronary artery stenosis was performed. A 3D coronary artery segmentation algorithm (Fraunhofer Institute for Computer Graphics, Darmstadt) was used for automatic evaluation. All significant stenoses (>50%) in vessels >1.5 mm in diameter were protocoled. Each detection tool was used by one reader who was blinded to the results of the other detection method and the results of coronary angiography. Sensitivity and specificity were determined for automatic and manual detection as well as was the time for both CT-based evaluation methods. The overall sensitivity and specificity of the automatic and manual approach were 93.1 vs. 95.83% and 86.1 vs. 81.9%. The time required for automatic evaluation was significantly shorter than with the manual approach, i.e., 246.04±43.17 s for the automatic approach and 526.88±45.71 s for the manual approach (P<0.0001). In 94% of the coronary artery branches, automatic detection required less time than the manual approach. Automatic coronary vessel evaluation is feasible. It reduces the time required for cardiac CT evaluation with similar sensitivity and specificity as well as facilitates the evaluation of MDCT coronary angiography in a standardized fashion. (orig.)

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.

Outdoor Illegal Construction Identification Algorithm Based on 3D Point Cloud Segmentation

Science.gov (United States)

An, Lu; Guo, Baolong

2018-03-01

Recently, various illegal constructions occur significantly in our surroundings, which seriously restrict the orderly development of urban modernization. The 3D point cloud data technology is used to identify the illegal buildings, which could address the problem above effectively. This paper proposes an outdoor illegal construction identification algorithm based on 3D point cloud segmentation. Initially, in order to save memory space and reduce processing time, a lossless point cloud compression method based on minimum spanning tree is proposed. Then, a ground point removing method based on the multi-scale filtering is introduced to increase accuracy. Finally, building clusters on the ground can be obtained using a region growing method, as a result, the illegal construction can be marked. The effectiveness of the proposed algorithm is verified using a publicly data set collected from the International Society for Photogrammetry and Remote Sensing (ISPRS).

Using 1D theory to understand 3D stagnation of a wire-array Z pinch in the absence of radiation

Science.gov (United States)

Yu, Edmund

2015-11-01

Many high-energy-density systems implode towards the axis of symmetry, where it collides on itself, forming a hot plasma. However, experiments show these imploding plasmas develop three-dimensional (3D) structures. As a result, the plasma cannot completely dissipate its kinetic energy at stagnation, instead retaining significant 3D flow. A useful tool for understanding the effects of this residual flow is 3D simulation, but the amount and complexity of information can be daunting. To address this problem, we explore the connection between 3D simulation and one-dimensional (1D) theory. Such a connection, if it exists, is mutually beneficial: 1D theory can provide a clear picture of the underlying dynamics of 3D stagnation. On the other hand, deviations between theory and simulation suggest how 1D theory must be modified to account for 3D effects. In this work, we focus on a 3D, magnetohydrodynamic simulation of a compact wire-array Z pinch. To provide a simpler background against which to test our ideas, we artificially turn off radiation during the stagnation phase. Examination of the initial accumulation of mass on axis reveals oblique collision between jets, shock accretion, and vortex formation. Despite evidence for shock-dominated stagnation, a 1D shockless stagnation solution is more appropriate for describing the global dynamics, in that it reproduces the increase of on-axis density with time. However, the 1D solution must be modified to account for 3D effects: the flows suggest enhanced thermal transport as well as centrifugal force. Upon reaching peak compression, the stagnation transitions to a second phase, in which the high-pressure core on axis expands outward into the remaining imploding plasma. During this phase, a 1D shock solution describes the growth of the shock accretion region, as well as the decrease of on-axis density with time. However, the effect of 3D flows is still present: the on-axis temperature does not cool during expansion, which

Pharmacokinetics of 1,25(OH)(2)D(3) and 1alpha(OH)D(3) in normal and uraemic men

DEFF Research Database (Denmark)

Brandi, Lisbet; Egfjord, Martin; Olgaard, Klaus

2002-01-01

,25(OH)(2)D(3) (n=6) protocol. RESULTS: After oral administration of 1,25(OH)(2)D(3) the bioavailability of 1,25(OH)(2)D(3) was 70.6+/-5.8/72.2+/-4.8% in healthy volunteers/uraemic patients (n.s.). After i.v. administration the volume of distribution of 1,25(OH)(2)D(3) was similar, 0.49+/-0.14 vs 0...

Effect of 2,4-D on content of abscisic and 3-indoleacetic acids in corn coleoptile segments

International Nuclear Information System (INIS)

Zemskaya, V.A.; Kalibernaya, Z.V.; Verenchikov, S.P.; Rakitin, L.Yu.; Sadovskaya, V.L.

1989-01-01

The authors studied the influence of growth-stimulating (10 -4 M), growth-inhibiting (3 x 10-3 M), lethal (7.5 x 10 -3 M) concentrations of 2,4-D on content of ABA and IAA, as well as on entry and conversion of [1- 14 C]-2,4-D, in corn (Zea mays L.) coleoptile segments. Increase of ABA content was observed at 6 h after influence of a stimulating dose of 2,4-D, an inhibiting dose caused no changes of ABA content, and a lethal dose led to decline of its level. The content of IAA declined sharply at all of the studied 2,4-D concentrations. This effect was accompanied neither by intensification of IAA-oxidase activity nor by increase in the content of bound forms of IAA. Metabolism of 2,4-D was realized mainly via hydroxylation of the benzene ring with subsequent hydroxylation, as well as by means of glucose ester formation. These processes transpired most intensively in the case of a stimulating dose of 2,4-D and less intensively in the case of an inhibiting dose and especially in that of a lethal dose

Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks.

Directory of Open Access Journals (Sweden)

Johannes Stegmaier

Full Text Available Automated analysis of multi-dimensional microscopy images has become an integral part of modern research in life science. Most available algorithms that provide sufficient segmentation quality, however, are infeasible for a large amount of data due to their high complexity. In this contribution we present a fast parallelized segmentation method that is especially suited for the extraction of stained nuclei from microscopy images, e.g., of developing zebrafish embryos. The idea is to transform the input image based on gradient and normal directions in the proximity of detected seed points such that it can be handled by straightforward global thresholding like Otsu's method. We evaluate the quality of the obtained segmentation results on a set of real and simulated benchmark images in 2D and 3D and show the algorithm's superior performance compared to other state-of-the-art algorithms. We achieve an up to ten-fold decrease in processing times, allowing us to process large data sets while still providing reasonable segmentation results.

Quantitative analysis of retina layer elasticity based on automatic 3D segmentation (Conference Presentation)

Science.gov (United States)

He, Youmin; Qu, Yueqiao; Zhang, Yi; Ma, Teng; Zhu, Jiang; Miao, Yusi; Humayun, Mark; Zhou, Qifa; Chen, Zhongping

2017-02-01

Age-related macular degeneration (AMD) is an eye condition that is considered to be one of the leading causes of blindness among people over 50. Recent studies suggest that the mechanical properties in retina layers are affected during the early onset of disease. Therefore, it is necessary to identify such changes in the individual layers of the retina so as to provide useful information for disease diagnosis. In this study, we propose using an acoustic radiation force optical coherence elastography (ARF-OCE) system to dynamically excite the porcine retina and detect the vibrational displacement with phase resolved Doppler optical coherence tomography. Due to the vibrational mechanism of the tissue response, the image quality is compromised during elastogram acquisition. In order to properly analyze the images, all signals, including the trigger and control signals for excitation, as well as detection and scanning signals, are synchronized within the OCE software and are kept consistent between frames, making it possible for easy phase unwrapping and elasticity analysis. In addition, a combination of segmentation algorithms is used to accommodate the compromised image quality. An automatic 3D segmentation method has been developed to isolate and measure the relative elasticity of every individual retinal layer. Two different segmentation schemes based on random walker and dynamic programming are implemented. The algorithm has been validated using a 3D region of the porcine retina, where individual layers have been isolated and analyzed using statistical methods. The errors compared to manual segmentation will be calculated.

3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study.

Science.gov (United States)

Dolz, Jose; Desrosiers, Christian; Ben Ayed, Ismail

2018-04-15

This study investigates a 3D and fully convolutional neural network (CNN) for subcortical brain structure segmentation in MRI. 3D CNN architectures have been generally avoided due to their computational and memory requirements during inference. We address the problem via small kernels, allowing deeper architectures. We further model both local and global context by embedding intermediate-layer outputs in the final prediction, which encourages consistency between features extracted at different scales and embeds fine-grained information directly in the segmentation process. Our model is efficiently trained end-to-end on a graphics processing unit (GPU), in a single stage, exploiting the dense inference capabilities of fully CNNs. We performed comprehensive experiments over two publicly available datasets. First, we demonstrate a state-of-the-art performance on the ISBR dataset. Then, we report a large-scale multi-site evaluation over 1112 unregistered subject datasets acquired from 17 different sites (ABIDE dataset), with ages ranging from 7 to 64 years, showing that our method is robust to various acquisition protocols, demographics and clinical factors. Our method yielded segmentations that are highly consistent with a standard atlas-based approach, while running in a fraction of the time needed by atlas-based methods and avoiding registration/normalization steps. This makes it convenient for massive multi-site neuroanatomical imaging studies. To the best of our knowledge, our work is the first to study subcortical structure segmentation on such large-scale and heterogeneous data. Copyright © 2017 Elsevier Inc. All rights reserved.

Delaunay algorithm and principal component analysis for 3D visualization of mitochondrial DNA nucleoids by Biplane FPALM/dSTORM

Czech Academy of Sciences Publication Activity Database

Alán, Lukáš; Špaček, Tomáš; Ježek, Petr

2016-01-01

Roč. 45, č. 5 (2016), s. 443-461 ISSN 0175-7571 R&D Projects: GA ČR(CZ) GA13-02033S; GA MŠk(CZ) ED1.1.00/02.0109 Institutional support: RVO:67985823 Keywords : 3D object segmentation * Delaunay algorithm * principal component analysis * 3D super-resolution microscopy * nucleoids * mitochondrial DNA replication Subject RIV: BO - Biophysics Impact factor: 1.472, year: 2016

An analytical calculation of the axial density profile for 1-d slab expansion

International Nuclear Information System (INIS)

Ho, D

1999-01-01

Obtaining an analytical expression for the axial density profile can provide us with a quick and convenient way to evaluate the density evolution for targets with different densities and dimensions. In this note, we show that such an analytical expression can be obtained based on the self-similar solutions and the method of characteristics for 1-D slab expansion

ROOFN3D: DEEP LEARNING TRAINING DATA FOR 3D BUILDING RECONSTRUCTION

Directory of Open Access Journals (Sweden)

A. Wichmann

2018-05-01

Full Text Available Machine learning methods have gained in importance through the latest development of artificial intelligence and computer hardware. Particularly approaches based on deep learning have shown that they are able to provide state-of-the-art results for various tasks. However, the direct application of deep learning methods to improve the results of 3D building reconstruction is often not possible due, for example, to the lack of suitable training data. To address this issue, we present RoofN3D which provides a new 3D point cloud training dataset that can be used to train machine learning models for different tasks in the context of 3D building reconstruction. It can be used, among others, to train semantic segmentation networks or to learn the structure of buildings and the geometric model construction. Further details about RoofN3D and the developed data preparation framework, which enables the automatic derivation of training data, are described in this paper. Furthermore, we provide an overview of other available 3D point cloud training data and approaches from current literature in which solutions for the application of deep learning to unstructured and not gridded 3D point cloud data are presented.

Calculation of the energy of particles emitted by the reactions {sup 3}{sub 1}T (d,n) {sup 4}{sub 2}He, D (d,n) {sup 3}{sub 2}He and D (d,p) T; Calcul de l'energie des particules emises par les reactions {sup 3}{sub 1}T (d,n) {sup 4}{sub 2}He, D (d,n) {sup 3}{sub 2}He et D (d,p) T

Energy Technology Data Exchange (ETDEWEB)

Oria, M; Sorriaux, A [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1965-07-01

With a view to ease the work of research workers using 150 kV electrostatic accelerators, we have calculated the energy and the emission angle of particles emitted during the reactions {sub 1}{sup 3}T(d,n){sub 2}{sup 4}He, {sub 1}{sup 2}D(d,n){sub 2}{sup 3}He and {sub 1}{sup 2}D(d,p){sub 1}{sup 3}T. The results are classified in tables and arranged according to the acceleration energy of the deuterons. Since the energies considered are relatively low we have limited our study to the non-relativistic domain; this simplification results in a maximum energy variation with respect to the real energy values of 1 per cent. We give also two curves representing the variations in the total cross-sections for the reactions T (d,n){sub 2}{sup 4}He and D (d,n){sub 2}{sup 3}He. (authors) [French] De facon a faciliter la tache des experimentateurs utilisant des accelerateurs electrostatiques de 150 kV, nous avons calcule l'energie et l'angle d'emission des particules emises lors des reactions {sub 1}{sup 3}T(d,n){sub 2}{sup 4}He, {sub 1}{sup 2}D(d,n){sub 2}{sup 3}He and {sub 1}{sup 2}D(d,p){sub 1}{sup 3}T. Les resultats ont ete classes dans des tableaux, et ordonnes en fonction de l'energie d'acceleration des deuterons. Les energies considerees etant relativement peu elevees, nous avons limite notre etude au domaine non relativiste, cette simplification n'entraine qu'une variation maximale de 1 pour cent sur les valeurs reelles des energies. Nous avons joint a ce calcul deux courbes representant la variation des sections efficaces totales des reactions T (d,n){sub 2}{sup 4}He et D (d,n){sub 2}{sup 3}He. (auteurs)

Another Method of Building 2D Entropy to Realize Automatic Segmentation

International Nuclear Information System (INIS)

Zhang, Y F; Zhang, Y

2006-01-01

2D entropy formed during the process of building 2D histogram can realize automatic segmentation. Traditional method utilizes central pixel grey value and the others or all of pixels grey mean value in 4-neighbor to build 2D histogram. In fact, the change of the greyscale value between two ''invariable position vectors'' cannot represent the total characteristics among neighbour pixels very well. A new method is proposed which makes use of minimum grey value in the 4-neighbor and of maximum grey value in the 3x3 neighbour except pixels of the 4-neighbor. New method and traditional one are used in contrast to realize image automatic segmentation. The experimental results of the classical image prove the new method is effective

Resistivity structure of Sumatran Fault (Aceh segment) derived from 1-D magnetotelluric modeling

Science.gov (United States)

Nurhasan, Sutarno, D.; Bachtiar, H.; Sugiyanto, D.; Ogawa, Y.; Kimata, F.; Fitriani, D.

2012-06-01

Sumatran Fault Zone is the most active fault in Indonesia as a result of strike-slip component of Indo-Australian oblique convergence. With the length of 1900 km, Sumatran fault was divided into 20 segments starting from the southernmost Sumatra Island having small slip rate and increasing to the north end of Sumatra Island. There are several geophysical methods to analyze fault structure depending on physical parameter used in these methods, such as seismology, geodesy and electromagnetic. Magnetotelluric method which is one of geophysical methods has been widely used in mapping and sounding resistivity distribution because it does not only has the ability for detecting contras resistivity but also has a penetration range up to hundreds of kilometers. Magnetotelluric survey was carried out in Aceh region with the 12 total sites crossing Sumatran Fault on Aceh and Seulimeum segments. Two components of electric and magnetic fields were recorded during 10 hours in average with the frequency range from 320 Hz to 0,01 Hz. Analysis of the pseudosection of phase and apparent resistivity exhibit vertical low phase flanked on the west and east by high phase describing the existence of resistivity contras in this region. Having rotated the data to N45°E direction, interpretation of the result has been performed using three different methods of 1D MT modeling i.e. Bostick inversion, 1D MT inversion of TM data, and 1D MT inversion of the impedance determinant. By comparison, we concluded that the use of TM data only and the impedance determinant in 1D inversion yield the more reliable resistivity structure of the fault compare to other methods. Based on this result, it has been shown clearly that Sumatra Fault is characterized by vertical contras resistivity indicating the existence of Aceh and Seulimeum faults which has a good agreement with the geological data.

Automated 3D closed surface segmentation: application to vertebral body segmentation in CT images.

Science.gov (United States)

Liu, Shuang; Xie, Yiting; Reeves, Anthony P

2016-05-01

A fully automated segmentation algorithm, progressive surface resolution (PSR), is presented in this paper to determine the closed surface of approximately convex blob-like structures that are common in biomedical imaging. The PSR algorithm was applied to the cortical surface segmentation of 460 vertebral bodies on 46 low-dose chest CT images, which can be potentially used for automated bone mineral density measurement and compression fracture detection. The target surface is realized by a closed triangular mesh, which thereby guarantees the enclosure. The surface vertices of the triangular mesh representation are constrained along radial trajectories that are uniformly distributed in 3D angle space. The segmentation is accomplished by determining for each radial trajectory the location of its intersection with the target surface. The surface is first initialized based on an input high confidence boundary image and then resolved progressively based on a dynamic attraction map in an order of decreasing degree of evidence regarding the target surface location. For the visual evaluation, the algorithm achieved acceptable segmentation for 99.35 % vertebral bodies. Quantitative evaluation was performed on 46 vertebral bodies and achieved overall mean Dice coefficient of 0.939 (with max [Formula: see text] 0.957, min [Formula: see text] 0.906 and standard deviation [Formula: see text] 0.011) using manual annotations as the ground truth. Both visual and quantitative evaluations demonstrate encouraging performance of the PSR algorithm. This novel surface resolution strategy provides uniform angular resolution for the segmented surface with computation complexity and runtime that are linearly constrained by the total number of vertices of the triangular mesh representation.

In situ repair of bone and cartilage defects using 3D scanning and 3D printing

OpenAIRE

Li, Lan; Yu, Fei; Shi, Jianping; Shen, Sheng; Teng, Huajian; Yang, Jiquan; Wang, Xingsong; Jiang, Qing

2017-01-01

Three-dimensional (3D) printing is a rapidly emerging technology that promises to transform tissue engineering into a commercially successful biomedical industry. However, the use of robotic bioprinters alone is not sufficient for disease treatment. This study aimed to report the combined application of 3D scanning and 3D printing for treating bone and cartilage defects. Three different kinds of defect models were created to mimic three orthopedic diseases: large segmental defects of long bon...

A 3D freehand ultrasound system for multi-view reconstructions from sparse 2D scanning planes.

Science.gov (United States)

Yu, Honggang; Pattichis, Marios S; Agurto, Carla; Beth Goens, M

2011-01-20

A significant limitation of existing 3D ultrasound systems comes from the fact that the majority of them work with fixed acquisition geometries. As a result, the users have very limited control over the geometry of the 2D scanning planes. We present a low-cost and flexible ultrasound imaging system that integrates several image processing components to allow for 3D reconstructions from limited numbers of 2D image planes and multiple acoustic views. Our approach is based on a 3D freehand ultrasound system that allows users to control the 2D acquisition imaging using conventional 2D probes.For reliable performance, we develop new methods for image segmentation and robust multi-view registration. We first present a new hybrid geometric level-set approach that provides reliable segmentation performance with relatively simple initializations and minimum edge leakage. Optimization of the segmentation model parameters and its effect on performance is carefully discussed. Second, using the segmented images, a new coarse to fine automatic multi-view registration method is introduced. The approach uses a 3D Hotelling transform to initialize an optimization search. Then, the fine scale feature-based registration is performed using a robust, non-linear least squares algorithm. The robustness of the multi-view registration system allows for accurate 3D reconstructions from sparse 2D image planes. Volume measurements from multi-view 3D reconstructions are found to be consistently and significantly more accurate than measurements from single view reconstructions. The volume error of multi-view reconstruction is measured to be less than 5% of the true volume. We show that volume reconstruction accuracy is a function of the total number of 2D image planes and the number of views for calibrated phantom. In clinical in-vivo cardiac experiments, we show that volume estimates of the left ventricle from multi-view reconstructions are found to be in better agreement with clinical

Development of an automated 3D segmentation program for volume quantification of body fat distribution using CT

International Nuclear Information System (INIS)

Ohshima, Shunsuke; Yamamoto, Shuji; Yamaji, Taiki

2008-01-01

The objective of this study was to develop a computing tool for full-automatic segmentation of body fat distributions on volumetric CT images. We developed an algorithm to automatically identify the body perimeter and the inner contour that separates visceral fat from subcutaneous fat. Diaphragmatic surfaces can be extracted by model-based segmentation to match the bottom surface of the lung in CT images for determination of the upper limitation of the abdomen. The functions for quantitative evaluation of abdominal obesity or obesity-related metabolic syndrome were implemented with a prototype three-dimensional (3D) image processing workstation. The volumetric ratios of visceral fat to total fat and visceral fat to subcutaneous fat for each subject can be calculated. Additionally, color intensity mapping of subcutaneous areas and the visceral fat layer is quite obvious in understanding the risk of abdominal obesity with the 3D surface display. Preliminary results obtained have been useful in medical checkups and have contributed to improved efficiency in checking obesity throughout the whole range of the abdomen with 3D visualization and analysis. (author)

Regulation of 1,25-dihydroxyvitamin D, receptors by [3H]-1,25-dihydroxyvitamin D3 in cultured cells (T-47D): evidence for receptor upregulation

International Nuclear Information System (INIS)

Reinhardt, T.A.; Horst, R.L.

1986-01-01

The authors examined the effect of 1,25-(OH) 2 D 3 on receptor concentration in cultured cells (T-47D). Two days prior to experiment, cells were fed with RPMI 1640 + 10% serum and 24-32 hours prior to experiment the media was replaced with RPMI 1640 + 25 mM Hepes + 1% serum. [ 3 H]-1,25-(OH) 2 D 3 +/- 100-fold molar excess cold hormone was used to treat the cells. Occupied receptors were measured in freshly prepared cytosols. Total receptors were measured following a 16-hour incubation of cytosols in the presence of 0.6 nM [ 3 H]-1,25-(OH) 2 D 3 +/- 100-fold molar excess of cold hormone at 4 0 C. Treatment of cell cultures for 16-18 hours with 0.5-1.0 nM [ 3 H]-1,25-(OH) 2 D 3 resulted in a 30-40% receptor occupancy by the hormone and a 2- to 3-fold increase in total cell receptor as compared to vehicle-treated controls. Time course studies showed a rapid increase in total receptors up to 16 hours post-treatment in the face of declining receptor occupancy. Actinomycin D blocked the [ 3 H]-1,25-(OH) 2 D 3 -dependent rise in cell receptor. The physiological significance of this receptor upregulation is not known nor is it known whether upregulation results from synthesis of new receptors and/or is the result of the activation of preformed receptors by a inducible activator protein

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

International Nuclear Information System (INIS)

Muehlenbruch, Georg; Das, Marco; Hohl, Christian; Wildberger, Joachim E.; Guenther, Rolf W.; Mahnken, Andreas H.; Rinck, Daniel; Flohr, Thomas G.; Koos, Ralf; Knackstedt, Christian

2006-01-01

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.)

Development of a 3D consistent 1D neutronics model for reactor core simulation

International Nuclear Information System (INIS)

Lee, Ki Bog; Joo, Han Gyu; Cho, Byung Oh; Zee, Sung Quun

2001-02-01

In this report a 3D consistent 1D model based on nonlinear analytic nodal method is developed to reproduce the 3D results. During the derivation, the current conservation factor (CCF) is introduced which guarantees the same axial neutron currents obtained from the 1D equation as the 3D reference values. Furthermore in order to properly use 1D group constants, a new 1D group constants representation scheme employing tables for the fuel temperature, moderator density and boron concentration is developed and functionalized for the control rod tip position. To test the 1D kinetics model with CCF, several steady state and transient calculations were performed and compared with 3D reference values. The errors of K-eff values were reduced about one tenth when using CCF without significant computational overhead. And the errors of power distribution were decreased to the range of one fifth or tenth at steady state calculation. The 1D kinetics model with CCF and the 1D group constant functionalization employing tables as a function of control rod tip position can provide preciser results at the steady state and transient calculation. Thus it is expected that the 1D kinetics model derived in this report can be used in the safety analysis, reactor real time simulation coupled with system analysis code, operator support system etc.

Evaluation of right ventricular function by coronary computed tomography angiography using a novel automated 3D right ventricle volume segmentation approach: a validation study.

Science.gov (United States)

Burghard, Philipp; Plank, Fabian; Beyer, Christoph; Müller, Silvana; Dörler, Jakob; Zaruba, Marc-Michael; Pölzl, Leo; Pölzl, Gerhard; Klauser, Andrea; Rauch, Stefan; Barbieri, Fabian; Langer, Christian-Ekkehardt; Schgoer, Wilfried; Williamson, Eric E; Feuchtner, Gudrun

2018-06-04

To evaluate right ventricle (RV) function by coronary computed tomography angiography (CTA) using a novel automated three-dimensional (3D) RV volume segmentation tool in comparison with clinical reference modalities. Twenty-six patients with severe end-stage heart failure [left ventricle (LV) ejection fraction (EF) right heart invasive catheterisation (IC). Automated 3D RV volume segmentation was successful in 26 (100%) patients. Read-out time was 3 min 33 s (range, 1 min 50s-4 min 33s). RV EF by CTA was stronger correlated with right atrial pressure (RAP) by IC (r = -0.595; p = 0.006) but weaker with TAPSE (r = 0.366, p = 0.94). When comparing TAPSE with RAP by IC (r = -0.317, p = 0.231), a weak-to-moderate non-significant inverse correlation was found. Interobserver correlation was high with r = 0.96 (p right atrium (RA) and right ventricle (RV) was 196.9 ± 75.3 and 217.5 ± 76.1 HU, respectively. Measurement of RV function by CTA using a novel 3D volumetric segmentation tool is fast and reliable by applying a dedicated biphasic injection protocol. The RV EF from CTA is a closer surrogate of RAP than TAPSE by TTE. • Evaluation of RV function by cardiac CTA by using a novel 3D volume segmentation tool is fast and reliable. • A biphasic contrast agent injection protocol ensures homogenous RV contrast attenuation. • Cardiac CT is a valuable alternative modality to CMR for the evaluation of RV function.

Dynamic accommodative response to different visual stimuli (2D vs 3D) while watching television and while playing Nintendo 3DS console.

Science.gov (United States)

Oliveira, Sílvia; Jorge, Jorge; González-Méijome, José M

2012-09-01

The aim of the present study was to compare the accommodative response to the same visual content presented in two dimensions (2D) and stereoscopically in three dimensions (3D) while participants were either watching a television (TV) or Nintendo 3DS console. Twenty-two university students, with a mean age of 20.3 ± 2.0 years (mean ± S.D.), were recruited to participate in the TV experiment and fifteen, with a mean age of 20.1 ± 1.5 years took part in the Nintendo 3DS console study. The accommodative response was measured using a Grand Seiko WAM 5500 autorefractor. In the TV experiment, three conditions were used initially: the film was viewed in 2D mode (TV2D without glasses), the same sequence was watched in 2D whilst shutter-glasses were worn (TV2D with glasses) and the sequence was viewed in 3D mode (TV3D). Measurements were taken for 5 min in each condition, and these sections were sub-divided into ten 30-s segments to examine changes within the film. In addition, the accommodative response to three points of different disparity of one 3D frame was assessed for 30 s. In the Nintendo experiment, two conditions were employed - 2D viewing and stereoscopic 3D viewing. In the TV experiment no statistically significant differences were found between the accommodative response with TV2D without glasses (-0.38 ± 0.32D, mean ± S.D.) and TV3D (-0.37 ± 0.34D). Also, no differences were found between the various segments of the film, or between the accommodative response to different points of one frame (p > 0.05). A significant difference (p = 0.015) was found, however, between the TV2D with (-0.32 ± 0.32D) and without glasses (-0.38 ± 0.32D). In the Nintendo experiment the accommodative responses obtained in modes 2D (-2.57 ± 0.30D) and 3D (-2.49 ± 0.28D) were significantly different (paired t-test p = 0.03). The need to use shutter-glasses may affect the accommodative response during the viewing of displays, and the accommodative response when playing

Thermal expansion and temperature variation of elastic constants of Li(H,D) and Na(H,D) systems

International Nuclear Information System (INIS)

Islam, A.K.M.A.; Hoque, M.T.

1994-11-01

An analysis of thermal expansion of Li(H,D) systems up to melting temperature has been performed using the theory of anharmonic lattice. The study has for the first time been extended to Na(H,D) systems where very little or no data are available. The calculated lattice constants of Li(H,D) systems show quite good agreement with experiment. The success of the present calculation with Li(H,D) and room temperature lattice constant data for Na(H,D) given an indication of the reliability of the computed lattice constants and thermal expansion coefficients for Na(H,D) systems. The study also allows us to predict the hitherto unknown lattice constants of Na(H,D) crystal at 0K. The temperature dependence of elastic constants for Li(H,D) systems has also been evaluated. Comparison with measurements shows the reliability of the present calculations. (author). 45 refs, 4 figs

D Geomarketing Segmentation: a Higher Spatial Dimension Planning Perspective

Science.gov (United States)

Suhaibah, A.; Uznir, U.; Rahman, A. A.; Anton, F.; Mioc, D.

2016-09-01

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, we strongly

In situ repair of bone and cartilage defects using 3D scanning and 3D printing.

Science.gov (United States)

Li, Lan; Yu, Fei; Shi, Jianping; Shen, Sheng; Teng, Huajian; Yang, Jiquan; Wang, Xingsong; Jiang, Qing

2017-08-25

Three-dimensional (3D) printing is a rapidly emerging technology that promises to transform tissue engineering into a commercially successful biomedical industry. However, the use of robotic bioprinters alone is not sufficient for disease treatment. This study aimed to report the combined application of 3D scanning and 3D printing for treating bone and cartilage defects. Three different kinds of defect models were created to mimic three orthopedic diseases: large segmental defects of long bones, free-form fracture of femoral condyle, and International Cartilage Repair Society grade IV chondral lesion. Feasibility of in situ 3D bioprinting for these diseases was explored. The 3D digital models of samples with defects and corresponding healthy parts were obtained using high-resolution 3D scanning. The Boolean operation was used to achieve the shape of the defects, and then the target geometries were imported in a 3D bioprinter. Two kinds of photopolymerized hydrogels were synthesized as bioinks. Finally, the defects of bone and cartilage were restored perfectly in situ using 3D bioprinting. The results of this study suggested that 3D scanning and 3D bioprinting could provide another strategy for tissue engineering and regenerative medicine.

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.

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.

Conformational analysis of vitamin D 3 derivatives by molecular mechanics . Part II. 1α,25-dihydroxyvitamin D 3 and analogues

Science.gov (United States)

Mosquera, Ricardo A.; Rios, Miguel A.; Tovar, Clara A.; Maestro, Miguel

1989-10-01

The conformational analysis of vitamin D 3 derivatives, including the biologically active form 1α,25-dihydroxyvitamin D 3 (III) and several synthetic analogues: b-deoxy-1α,25-dihydroxyvitamin D 3 (IV), 3-deoxy-3α-methyl-1α,25-dihydroxyvitamin D 3 (V), 3-deoxy-3β-methyl-1α,25-dihydroxyvitamin D 3 (VI), and 3-deoxy-3,3-dimethyl-1α,25-dihydroxyvitamin D 3 (VII), has been carried out employing Allinger's molecular mechanics method. The results obtained for conformational equilibrium populations are found to be in good agreement with those provided by NMR studies. Comparison of the active form of vitamin D 3 (1α,25-dihydroxyvitamin D 3) with the other species reveals no important geometrical differences.

1D to 3D diffusion-reaction kinetics of defects in crystals

DEFF Research Database (Denmark)

Trinkaus, H.; Heinisch, H.L.; Barashev, A.V.

2002-01-01

Microstructural features evolving in crystalline solids from diffusion-reaction kinetics of mobile components depend crucially on the dimension of the underlying diffusion process which is commonly assumed to be three-dimensional (3D). In metals, irradiation-induced displacement cascades produce...... clusters of self-interstitials performing 1D diffusion. Changes between equivalent 1D diffusion paths and transversal diffusion result in diffusion-reaction kinetics between one and three dimensions. An analytical approach suggests a single-variable function (master curve) interpolating between the 1D...

Contrast-enhanced MR imaging of metastatic brain tumor at 3 Tesla. Utility of T1-weighted SPACE compared with 2D spin echo and 3D gradient echo sequence

International Nuclear Information System (INIS)

Komada, Tomohiro; Naganawa, Shinji; Ogawa, Hiroshi

2008-01-01

We evaluated the newly developed whole-brain, isotropic, 3-dimensional turbo spin-echo imaging with variable flip angle echo train (SPACE) for contrast-enhanced T 1 -weighted imaging in detecting brain metastases at 3 tesla (T). Twenty-two patients with suspected brain metastases underwent postcontrast study with SPACE, magnetization-prepared rapid gradient-echo (MP-RAGE), and 2-dimensional T 1 -weighted spin echo (2D-SE) imaging at 3 T. We quantitatively compared SPACE, MP-RAGE, and 2D-SE images by using signal-to-noise ratios (SNRs) for gray matter (GM) and white matter (WM) and contrast-to-noise ratios (CNRs) for GM-to-WM, lesion-to-GM, and lesion-to-WM. Two blinded radiologists evaluated the detection of brain metastases by segment-by-segment analysis and continuously-distributed test. The CNR between GM and WM was significantly higher on MP-RAGE images than on SPACE images (P 1 -weighted imaging. (author)

Fully digital 1-D, 2-D and 3-D multiscroll chaos as hardware pseudo random number generators

KAUST Repository

Mansingka, Abhinav S.; Radwan, Ahmed Gomaa; Salama, Khaled N.

2012-01-01

This paper introduces the first fully digital implementation of 1-D, 2-D and 3-D multiscroll chaos using the sawtooth nonlinearity in a 3rd order ODE with the Euler approximation. Systems indicate chaotic behaviour through phase space boundedness

Signal alteration of the cochlear perilymph on 3 different sequences after intratympanic Gd-DTPA administration at 3 tesla. Comparison of 3D-FLAIR, 3D-T1-weighted imaging, and 3D-CISS

International Nuclear Information System (INIS)

Yamazaki, Masahiro; Naganawa, Shinji; Kawai, Hisashi; Nihashi, Takashi; Nakashima, Tsutomu

2010-01-01

Three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) imaging after intratympanic gadolinium injection is useful for pathophysiologic and morphologic analysis of the inner ear. However, statistical analysis of differences in inner ear signal intensity among 3D-FLAIR and other sequences has not been reported. We evaluated the signal intensity of cochlear fluid on each of 3D-FLAIR, 3D-T 1 -weighted imaging (T 1 WI), and 3D-constructive interference in the steady state (CISS) to clarify the differences in contrast effect among these 3 sequences using intratympanic gadolinium injection. Twenty-one patients underwent 3D-FLAIR, 3D-T 1 WI, and 3D-CISS imaging at 3 tesla 24 hours after intratympanic injection of gadolinium. We determined regions of interest of the cochleae (C) and medulla oblongata (M) on each image, evaluated the signal intensity ratio between C and M (CM ratio), and determined the ratio of cochlear signal intensity of the injected side to that of the non-injected side (contrast value). The CM ratio of the injected side (3.00±1.31, range, 0.53 to 4.88, on 3D-FLAIR; 0.83±0.30, range, 0.36 to 1.58 on 3D-T 1 WI) was significantly higher than that of the non-injected side (0.52±0.14, range, 0.30 to 0.76 on 3D-FLAIR; 0.49±0.11, range, 0.30 to 0.71 on 3D-T 1 WI) on 3D-FLAIR and 3D-T 1 WI (P 1 WI (1.73±0.60 range, 0.98 to 3.09) (P<0.001). The 3D-FLAIR sequence is the most sensitive for observing alteration in inner ear fluid signal after intratympanic gadolinium injection. Our results warrant use of 3D-FLAIR as a sensitive imaging technique to clarify the pathological and morphological mechanisms of disorders of the inner ear. (author)

FUN3D Manual: 13.1

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.;

From medical imaging data to 3D printed anatomical models.

Directory of Open Access Journals (Sweden)

Thore M Bücking

Full Text Available Anatomical models are important training and teaching tools in the clinical environment and are routinely used in medical imaging research. Advances in segmentation algorithms and increased availability of three-dimensional (3D printers have made it possible to create cost-efficient patient-specific models without expert knowledge. We introduce a general workflow that can be used to convert volumetric medical imaging data (as generated by Computer Tomography (CT to 3D printed physical models. This process is broken up into three steps: image segmentation, mesh refinement and 3D printing. To lower the barrier to entry and provide the best options when aiming to 3D print an anatomical model from medical images, we provide an overview of relevant free and open-source image segmentation tools as well as 3D printing technologies. We demonstrate the utility of this streamlined workflow by creating models of ribs, liver, and lung using a Fused Deposition Modelling 3D printer.

Repeatability of a 3D multi-segment foot model protocol in presence of foot deformities.

Science.gov (United States)

Deschamps, Kevin; Staes, Filip; Bruyninckx, Herman; Busschots, Ellen; Matricali, Giovanni A; Spaepen, Pieter; Meyer, Christophe; Desloovere, Kaat

2012-07-01

Repeatability studies on 3D multi-segment foot models (3DMFMs) have mainly considered healthy participants which contrasts with the widespread application of these models to evaluate foot pathologies. The current study aimed at establishing the repeatability of the 3DMFM described by Leardini et al. in presence of foot deformities. Foot kinematics of eight adult participants were analyzed using a repeated-measures design including two therapists with different levels of experience. The inter-trial variability was higher compared to the kinematics of healthy subjects. Consideration of relative angles resulted in the lowest inter-session variability. The absolute 3D rotations between the Sha-Cal and Cal-Met seem to have the lowest variability in both therapists. A general trend towards higher σ(sess)/σ(trial) ratios was observed when the midfoot was involved. The current study indicates that not only relative 3D rotations and planar angles can be measured consistently in patients, also a number of absolute parameters can be consistently measured serving as basis for the decision making process. Copyright © 2012 Elsevier B.V. All rights reserved.

3-D discrete analytical ridgelet transform.

Science.gov (United States)

Helbert, David; Carré, Philippe; Andres, Eric

2006-12-01

In this paper, we propose an implementation of the 3-D Ridgelet transform: the 3-D discrete analytical Ridgelet transform (3-D DART). This transform uses the Fourier strategy for the computation of the associated 3-D discrete Radon transform. The innovative step is the definition of a discrete 3-D transform with the discrete analytical geometry theory by the construction of 3-D discrete analytical lines in the Fourier domain. We propose two types of 3-D discrete lines: 3-D discrete radial lines going through the origin defined from their orthogonal projections and 3-D planes covered with 2-D discrete line segments. These discrete analytical lines have a parameter called arithmetical thickness, allowing us to define a 3-D DART adapted to a specific application. Indeed, the 3-D DART representation is not orthogonal, It is associated with a flexible redundancy factor. The 3-D DART has a very simple forward/inverse algorithm that provides an exact reconstruction without any iterative method. In order to illustrate the potentiality of this new discrete transform, we apply the 3-D DART and its extension to the Local-DART (with smooth windowing) to the denoising of 3-D image and color video. These experimental results show that the simple thresholding of the 3-D DART coefficients is efficient.

A novel asymptotic expansion homogenization analysis for 3-D composite with relieved periodicity in the thickness direction

KAUST Repository

Nasution, Muhammad Ridlo Erdata

2014-06-01

A new asymptotic expansion homogenization analysis is proposed to analyze 3-D composite in which thermomechanical and finite thickness effects are considered. Finite thickness effect is captured by relieving periodic boundary condition at the top and bottom of unit-cell surfaces. The mathematical treatment yields that only 2-D periodicity (i.e. in in-plane directions) is taken into account. A unit-cell representing the whole thickness of 3-D composite is built to facilitate the present method. The equivalent in-plane thermomechanical properties of 3-D orthogonal interlock composites are calculated by present method, and the results are compared with those obtained by standard homogenization method (with 3-D periodicity). Young\\'s modulus and Poisson\\'s ratio obtained by present method are also compared with experiments whereby a good agreement is particularly found for the Young\\'s modulus. Localization analysis is carried out to evaluate the stress responses within the unit-cell of 3-D composites for two cases: thermal and biaxial tensile loading. Standard finite element (FE) analysis is also performed to validate the stress responses obtained by localization analysis. It is found that present method results are in a good agreement with standard FE analysis. This fact emphasizes that relieving periodicity in the thickness direction is necessary to accurately simulate the real free-traction condition in 3-D composite. © 2014 Elsevier Ltd.

A novel asymptotic expansion homogenization analysis for 3-D composite with relieved periodicity in the thickness direction

KAUST Repository

Nasution, Muhammad Ridlo Erdata; Watanabe, Naoyuki; Kondo, Atsushi; Yudhanto, Arief

2014-01-01

A new asymptotic expansion homogenization analysis is proposed to analyze 3-D composite in which thermomechanical and finite thickness effects are considered. Finite thickness effect is captured by relieving periodic boundary condition at the top and bottom of unit-cell surfaces. The mathematical treatment yields that only 2-D periodicity (i.e. in in-plane directions) is taken into account. A unit-cell representing the whole thickness of 3-D composite is built to facilitate the present method. The equivalent in-plane thermomechanical properties of 3-D orthogonal interlock composites are calculated by present method, and the results are compared with those obtained by standard homogenization method (with 3-D periodicity). Young's modulus and Poisson's ratio obtained by present method are also compared with experiments whereby a good agreement is particularly found for the Young's modulus. Localization analysis is carried out to evaluate the stress responses within the unit-cell of 3-D composites for two cases: thermal and biaxial tensile loading. Standard finite element (FE) analysis is also performed to validate the stress responses obtained by localization analysis. It is found that present method results are in a good agreement with standard FE analysis. This fact emphasizes that relieving periodicity in the thickness direction is necessary to accurately simulate the real free-traction condition in 3-D composite. © 2014 Elsevier Ltd.

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

International Nuclear Information System (INIS)

Zhou Jinghao; Kim, Sung; Jabbour, Salma; Goyal, Sharad; Haffty, Bruce; Chen, Ting; Levinson, Lydia; Metaxas, Dimitris; Yue, Ning J.

2010-01-01

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

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.

Fully digital 1-D, 2-D and 3-D multiscroll chaos as hardware pseudo random number generators

KAUST Repository

Mansingka, Abhinav S.

2012-10-07

This paper introduces the first fully digital implementation of 1-D, 2-D and 3-D multiscroll chaos using the sawtooth nonlinearity in a 3rd order ODE with the Euler approximation. Systems indicate chaotic behaviour through phase space boundedness and positive Lyapunov exponent. Low-significance bits form a PRNG and pass all tests in the NIST SP. 800-22 suite without post-processing. Real-time control of the number of scrolls allows distinct output streams with 2-D and 3-D multiscroll chaos enabling greater controllability. The proposed PRNGs are experimentally verified on a Xilinx Virtex 4 FPGA with logic utilization less than 1.25%, throughput up to 5.25 Gbits/s and up to 512 distinct output streams with low cross-correlation.

Comparison and analysis of 1D/2D/3D neutronics modeling for a fusion reactor

International Nuclear Information System (INIS)

Li, J.; Zeng, Q.; Chen, M.; Jiang, J.; Wu, Y.

2007-01-01

During the course of analyzing the characteristics for fusion reactors, the refined calculations are needed to confirm that the nuclear design requirements are met. Since the long computational time is consumed, the refined three-dimensional (3D) representation has been used primarily for establishing the baseline reference values, analyzing problems which cannot be reduced by symmetry considerations to lower dimensions, or where a high level of accuracy is desired locally. The two-dimensional (2D) or one-dimensional (1D) description leads itself readily to resolve many problems, such as the studies for the material fraction optimization, or for the blanket size optimization. The purpose of this paper is to find out the differences among different geometric descriptions, which can guide the way to approximate and simplify the computational model. The fusion power reactor named FDS-II was designed as an advanced fusion power reactor to demonstrate and validate the commercialization of fusion power by Institute of Plasma Physics, Chinese Academy of Science. In this contribution, the dual-cooled lithium lead (DLL) blanket of FDS-II was used as a reference for neutronics comparisons and analyses. The geometric descriptions include 1D concentric sphere model, 1D, 2D and 3D cylinder models. The home-developed multi-functional neutronics analysis code system VisualBUS, the Monte Carlo transport code MCNP and nuclear data library HENDL have been used for these analyses. The neutron wall loading distribution, tritium breeding ratio (TBR) and nuclear heat were calculated to evaluate the nuclear performance. The 3D calculation has been used as a comparison reference because it has the least errors in the treatment of geometry. It is suggested that the value of TBR calculated by the 1D approach should be greater than 1.3 to satisfy the practical need of tritium self-sufficiency. The distribution of nuclear heat based on the 2D and 3D models were similar since they all consider

The superiority of 3D-CISS sequence in displaying the cisternal segment of facial, vestibulocochlear nerves and their abnormal changes

Energy Technology Data Exchange (ETDEWEB)

Liang Changhu, E-mail: tigerlch@163.co [Shandong University, Shandong Medical Imaging Research Institute, CT Room, 324, Jingwu Road, Jinan, Shandong (China); Zhang Bin, E-mail: liangchangbo.student@sina.co [Liao Cheng City People' s Hospital, Dongchang Road, Liaocheng, Shandong (China); Wu Lebin, E-mail: Lebinwu518@163.co [Shandong University, Shandong Medical Imaging Research Institute, CT Room, 324, Jingwu Road, Jinan, Shandong (China); Du Yinglin, E-mail: duyinglinzhuo@sohu.co [Shandong Provincial Center for Disease Control and Prevention, Public Health Institute, 72, Jingshi Road, Jinan, Shandong (China); Wang Ximing, E-mail: wxminmg369@163.co [Shandong University, Shandong Medical Imaging Research Institute, CT Room, 324, Jingwu Road, Jinan, Shandong (China); Liu Cheng, E-mail: cacab2a@126.co [Shandong University, Shandong Medical Imaging Research Institute, CT Room, 324, Jingwu Road, Jinan, Shandong (China); Yu Fuhua, E-mail: changhu1970@163.co [Weifang Medical College, 7166, West Road Baotong Weifang, Shandong (China)

2010-06-15

Objective: To select the best imaging method for clinical otologic patients through evaluating 3D constructive interference of steady state (CISS) image quality in visualizing the facial, vestibulocochlear nerves (CN:VII-VIII) and their abnormal changes. Methods: The CN:VII-VIII as well as inner ear structures in 48 volunteers were examined using 3D-CISS and 3D turbo spin echo (TSE) sequences respectively, and displayed to the full at the reformatted and maximum intensity projection (MIP) images. The nerve identification and image quality were graded for the CN:VII-VIII as well as inner ear structures. Statistical analysis was performed using the Wilcoxin test, p < 0.05 was considered significant. In addition, 8 patients with abnormality in facial or vestibulocochlear nerves were also examined using 3D-CISS sequence. Results: The identification rates for the cisternal segment of facial, vestibulocochlear nerves and corresponding membranous labyrinth were 100%. Abnormal changes of the facial or vestibulocochlear nerves were clearly shown in 8 patients, among them 1 was caused by bilateral acoustic neurinoma, 1 by cholesteatoma at cerebellopontine angle, 1 by arachnoid cyst, 1 by neurovascular adhesion, 4 by neurovascular compression. Conclusion: With 3D-CISS sequence the fine structure of the CN:VII-VIII and corresponding membranous labyrinth can be clearly demonstrated; lesions at the site of cerebellopontine angle can also be found easily.

A 3d-3d appetizer

Energy Technology Data Exchange (ETDEWEB)

Pei, Du; Ye, Ke [Walter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena, CA, 91125 (United States)

2016-11-02

We test the 3d-3d correspondence for theories that are labeled by Lens spaces. We find a full agreement between the index of the 3d N=2 “Lens space theory” T[L(p,1)] and the partition function of complex Chern-Simons theory on L(p,1). In particular, for p=1, we show how the familiar S{sup 3} partition function of Chern-Simons theory arises from the index of a free theory. For large p, we find that the index of T[L(p,1)] becomes a constant independent of p. In addition, we study T[L(p,1)] on the squashed three-sphere S{sub b}{sup 3}. This enables us to see clearly, at the level of partition function, to what extent G{sub ℂ} complex Chern-Simons theory can be thought of as two copies of Chern-Simons theory with compact gauge group G.

3D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells.

Directory of Open Access Journals (Sweden)

Tong Luo

Full Text Available The 3D geometry of individual vascular smooth muscle cells (VSMCs, which are essential for understanding the mechanical function of blood vessels, are currently not available. This paper introduces a new 3D segmentation algorithm to determine VSMC morphology and orientation.A total of 112 VSMCs from six porcine coronary arteries were used in the analysis. A 3D semi-automatic segmentation method was developed to reconstruct individual VSMCs from cell clumps as well as to extract the 3D geometry of VSMCs. A new edge blocking model was introduced to recognize cell boundary while an edge growing was developed for optimal interpolation and edge verification. The proposed methods were designed based on Region of Interest (ROI selected by user and interactive responses of limited key edges. Enhanced cell boundary features were used to construct the cell's initial boundary for further edge growing. A unified framework of morphological parameters (dimensions and orientations was proposed for the 3D volume data. Virtual phantom was designed to validate the tilt angle measurements, while other parameters extracted from 3D segmentations were compared with manual measurements to assess the accuracy of the algorithm. The length, width and thickness of VSMCs were 62.9±14.9 μm, 4.6±0.6 μm and 6.2±1.8 μm (mean±SD. In longitudinal-circumferential plane of blood vessel, VSMCs align off the circumferential direction with two mean angles of -19.4±9.3° and 10.9±4.7°, while an out-of-plane angle (i.e., radial tilt angle was found to be 8±7.6° with median as 5.7°.A 3D segmentation algorithm was developed to reconstruct individual VSMCs of blood vessel walls based on optical image stacks. The results were validated by a virtual phantom and manual measurement. The obtained 3D geometries can be utilized in mathematical models and leads a better understanding of vascular mechanical properties and function.

3-D Whole-Core Transport Calculation with 3D/2D Rotational Plane Slicing Method

Energy Technology Data Exchange (ETDEWEB)

Yoo, Han Jong; Cho, Nam Zin [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of)

2014-10-15

Use of the method of characteristics (MOC) is very popular due to its capability of heterogeneous geometry treatment and widely used for 2-D core calculation, but direct extension of MOC to 3-D core is not so attractive due to huge calculational cost. 2-D/1-D fusion method was very successful for 3-D calculation of current generation reactor types (highly heterogeneous in radial direction but piece-wise homogeneous in axial direction). In this paper, 2-D MOC concept is extended to 3-D core calculation with little modification of an existing 2-D MOC code. The key idea is to suppose 3-D geometry as a set of many 2-D planes like a phone-directory book. Dividing 3-D structure into a large number of 2-D planes and solving each plane with a simple 2-D SN transport method would give the solution of a 3-D structure. This method was developed independently at KAIST but it is found that this concept is similar with that of 'plane tracing' in the MCCG-3D code. The method developed was tested on the 3-D C5G7 OECD/NEA benchmark problem and compared with the 2-D/1-D fusion method. Results show that the proposed method is worth investigating further. A new approach to 3-D whole-core transport calculation is described and tested. By slicing 3-D structure along characteristic planes and solving each 2-D plane problem, we can get 3-D solution. The numerical test results indicate that the new method is comparable with the 2D/1D fusion method and outperforms other existing methods. But more fair comparison should be done in similar discretization level.

3D visualisation of the middle ear and adjacent structures using reconstructed multi-slice CT datasets, correlating 3D images and virtual endoscopy to the 2D cross-sectional images

International Nuclear Information System (INIS)

Rodt, T.; Ratiu, P.; Kacher, D.F.; Anderson, M.; Jolesz, F.A.; Kikinis, R.; Becker, H.; Bartling, S.

2002-01-01

The 3D imaging of the middle ear facilitates better understanding of the patient's anatomy. Cross-sectional slices, however, often allow a more accurate evaluation of anatomical structures, as some detail may be lost through post-processing. In order to demonstrate the advantages of combining both approaches, we performed computed tomography (CT) imaging in two normal and 15 different pathological cases, and the 3D models were correlated to the cross-sectional CT slices. Reconstructed CT datasets were acquired by multi-slice CT. Post-processing was performed using the in-house software ''3D Slicer'', applying thresholding and manual segmentation. 3D models of the individual anatomical structures were generated and displayed in different colours. The display of relevant anatomical and pathological structures was evaluated in the greyscale 2D slices, 3D images, and the 2D slices showing the segmented 2D anatomy in different colours for each structure. Correlating 2D slices to the 3D models and virtual endoscopy helps to combine the advantages of each method. As generating 3D models can be extremely time-consuming, this approach can be a clinically applicable way of gaining a 3D understanding of the patient's anatomy by using models as a reference. Furthermore, it can help radiologists and otolaryngologists evaluating the 2D slices by adding the correct 3D information that would otherwise have to be mentally integrated. The method can be applied to radiological diagnosis, surgical planning, and especially, to teaching. (orig.)

The evaluation of single-view and multi-view fusion 3D echocardiography using image-driven segmentation and tracking.

Science.gov (United States)

Rajpoot, Kashif; Grau, Vicente; Noble, J Alison; Becher, Harald; Szmigielski, Cezary

2011-08-01

Real-time 3D echocardiography (RT3DE) promises a more objective and complete cardiac functional analysis by dynamic 3D image acquisition. Despite several efforts towards automation of left ventricle (LV) segmentation and tracking, these remain challenging research problems due to the poor-quality nature of acquired images usually containing missing anatomical information, speckle noise, and limited field-of-view (FOV). Recently, multi-view fusion 3D echocardiography has been introduced as acquiring multiple conventional single-view RT3DE images with small probe movements and fusing them together after alignment. This concept of multi-view fusion helps to improve image quality and anatomical information and extends the FOV. We now take this work further by comparing single-view and multi-view fused images in a systematic study. In order to better illustrate the differences, this work evaluates image quality and information content of single-view and multi-view fused images using image-driven LV endocardial segmentation and tracking. The image-driven methods were utilized to fully exploit image quality and anatomical information present in the image, thus purposely not including any high-level constraints like prior shape or motion knowledge in the analysis approaches. Experiments show that multi-view fused images are better suited for LV segmentation and tracking, while relatively more failures and errors were observed on single-view images. Copyright © 2011 Elsevier B.V. All rights reserved.

New coordination polymers from 1D chain, 2D layer to 3D framework constructed from 1,2-phenylenediacetic acid and 1,3-bis(4-pyridyl)propane flexible ligands

International Nuclear Information System (INIS)

Xin Lingyun; Liu Guangzhen; Wang Liya

2011-01-01

The hydrothermal reactions of Cd, Zn, or Cu(II) acetate salts with H 2 PHDA and BPP flexible ligands afford three new coordination polymers, including [Cd(PHDA)(BPP)(H 2 O)] n (1), [Zn(PHDA)(BPP)] n (2), and [Cu 2 (PHDA) 2 (BPP)] n (3) (H 2 PHDA=1,2-phenylenediacetic acid, BPP=1,3-bis(4-pyridyl)propane). The single-crystal X-ray diffractions reveal that all three complexes feature various metal carboxylate subunits extended further by the BPP ligands to form a diverse range of structures, displaying a remarked structural sensitivity to metal(II) cation. Complex 1 containing PHDA-bridged binuclear cadmium generates 1D double-stranded chain, complex 2 results in 2D→2D interpenetrated (4,4) grids, and complex 3 displays a 3D self-penetrated framework with 4 8 6 6 8 rob topology. In addition, fluorescent analyses show that both 1 and 2 exhibit intense blue-violet photoluminescence in the solid state. - Graphical Abstract: We show diverse supramolecular frameworks based on the same ligands (PHDA and BPP) and different metal acetate salts including 1D double-stranded chain, 2D → 2D twofold interpenetrated layer, and 3D self-penetration networks. Highlights: → Three metal(II = 2 /* ROMAN ) coordination polymers were synthesized using H 2 PHDA and BPP. → The diversity of structures show a remarked sensitivity to metal(II) center. → Complexes show the enhancement of fluorescence compared to that of free ligand.

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.

Determination of the 3d34d and 3d35s configurations of Fe V

International Nuclear Information System (INIS)

Azarov, V.I.

2001-01-01

The analysis of the spectrum of four times ionized iron, Fe V, has led to the determination of the 3d 3 4d and 3d 3 5s configurations. From 975 classified lines in the region 645-1190 A we have established 123 of 168 theoretically possible 3d 3 4d levels and 26 of 38 possible 3d 3 5s levels. The estimated accuracy of values of energy levels of these two configurations is about 0.7 cm -1 and 1.0 cm -1 , respectively. The level structure of the system of the 3d 4 , 3d 3 4s, 3d 3 4d and 3d 3 5s configurations has been theoretically interpreted and the energy parameters have been determined by a least squares fit to the observed levels. A comparison of parameters in Cr III and Fe V ions is given. (orig.)

3D pulmonary nodules detection using fast marching segmentation ...

African Journals Online (AJOL)

This paper proposes an automated computer aided diagnosis system for detection of pulmonary nodules based on three dimensional (3D) structures. Lung ... The proposed detection methodology can give the accuracy of 92%. Keywords: lung cancer; pulmonary nodule; fast marching; 3D features; random forest classifier.

Scan-rescan reproducibility of segmental aortic wall shear stress as assessed by phase-specific segmentation with 4D flow MRI in healthy volunteers.

Science.gov (United States)

van der Palen, Roel L F; Roest, Arno A W; van den Boogaard, Pieter J; de Roos, Albert; Blom, Nico A; Westenberg, Jos J M

2018-05-26

The aim was to investigate scan-rescan reproducibility and observer variability of segmental aortic 3D systolic wall shear stress (WSS) by phase-specific segmentation with 4D flow MRI in healthy volunteers. Ten healthy volunteers (age 26.5 ± 2.6 years) underwent aortic 4D flow MRI twice. Maximum 3D systolic WSS (WSSmax) and mean 3D systolic WSS (WSSmean) for five thoracic aortic segments over five systolic cardiac phases by phase-specific segmentations were calculated. Scan-rescan analysis and observer reproducibility analysis were performed. Scan-rescan data showed overall good reproducibility for WSSmean (coefficient of variation, COV 10-15%) with moderate-to-strong intraclass correlation coefficient (ICC 0.63-0.89). The variability in WSSmax was high (COV 16-31%) with moderate-to-good ICC (0.55-0.79) for different aortic segments. Intra- and interobserver reproducibility was good-to-excellent for regional aortic WSSmax (ICC ≥ 0.78; COV ≤ 17%) and strong-to-excellent for WSSmean (ICC ≥ 0.86; COV ≤ 11%). In general, ascending aortic segments showed more WSSmax/WSSmean variability compared to aortic arch or descending aortic segments for scan-rescan, intraobserver and interobserver comparison. Scan-rescan reproducibility was good for WSSmean and moderate for WSSmax for all thoracic aortic segments over multiple systolic phases in healthy volunteers. Intra/interobserver reproducibility for segmental WSS assessment was good-to-excellent. Variability of WSSmax is higher and should be taken into account in case of individual follow-up or in comparative rest-stress studies to avoid misinterpretation.

Proposal of custom made wrist orthoses based on 3D modelling and 3D printing.

Science.gov (United States)

Abreu de Souza, Mauren; Schmitz, Cristiane; Marega Pinhel, Marcelo; Palma Setti, Joao A; Nohama, Percy

2017-07-01

Accessibility to three-dimensional (3D) technologies, such as 3D scanning systems and additive manufacturing (like 3D printers), allows a variety of 3D applications. For medical applications in particular, these modalities are gaining a lot of attention enabling several opportunities for healthcare applications. The literature brings several cases applying both technologies, but none of them focus on the spreading of how this technology could benefit the health segment. This paper proposes a new methodology, which employs both 3D modelling and 3D printing for building orthoses, which could better fit the demands of different patients. Additionally, there is an opportunity for sharing expertise, as it represents a trendy in terms of the maker-movement. Therefore, as a result of the proposed approach, we present a case study based on a volunteer who needs an immobilization orthosis, which was built for exemplification of the whole process. This proposal also employs freely available 3D models and software, having a strong social impact. As a result, it enables the implementation and effective usability for a variety of built to fit solutions, hitching useful and smarter technologies for the healthcare sector.

Surgical Splint Design Influences Transverse Expansion in Segmental Maxillary Osteotomies

DEFF Research Database (Denmark)

Stokbro, Kasper; Aagaard, Esben; Torkov, Peter

2017-01-01

splint designs on achieving the planned transverse expansion in bimaxillary surgery with segmental maxillary procedures. Materials and Methods: Forty-two participants were included in a retrospective observational study. All participants had completed virtually planned bimaxillary surgery with 3-piece......Purpose: In segmental maxillary procedures, it is imperative to obtain as much of the planned expansion as possible. Lack of obtained expansion, in addition to late relapse after splint removal, can result in relapse of the posterior crossbite. This study investigated the influence of 2 surgical...... maxillary segmentation. The primary outcome variable was the transverse expansion obtained, measured as the expansion between the maxillary first molars on preoperative and postoperative cone-beam computed tomograms. The postoperative scan was performed 1 week after surgery with the splint still in place...

2D Tsallis Entropy for Image Segmentation Based on Modified Chaotic Bat Algorithm

Directory of Open Access Journals (Sweden)

Zhiwei Ye

2018-03-01

Full Text Available Image segmentation is a significant step in image analysis and computer vision. Many entropy based approaches have been presented in this topic; among them, Tsallis entropy is one of the best performing methods. However, 1D Tsallis entropy does not consider make use of the spatial correlation information within the neighborhood results might be ruined by noise. Therefore, 2D Tsallis entropy is proposed to solve the problem, and results are compared with 1D Fisher, 1D maximum entropy, 1D cross entropy, 1D Tsallis entropy, fuzzy entropy, 2D Fisher, 2D maximum entropy and 2D cross entropy. On the other hand, due to the existence of huge computational costs, meta-heuristics algorithms like genetic algorithm (GA, particle swarm optimization (PSO, ant colony optimization algorithm (ACO and differential evolution algorithm (DE are used to accelerate the 2D Tsallis entropy thresholding method. In this paper, considering 2D Tsallis entropy as a constrained optimization problem, the optimal thresholds are acquired by maximizing the objective function using a modified chaotic Bat algorithm (MCBA. The proposed algorithm has been tested on some actual and infrared images. The results are compared with that of PSO, GA, ACO and DE and demonstrate that the proposed method outperforms other approaches involved in the paper, which is a feasible and effective option for image segmentation.

Depth enhancement of S3D content and the psychological effects

Science.gov (United States)

Hirahara, Masahiro; Shiraishi, Saki; Kawai, Takashi

2012-03-01

Stereoscopic 3D (S3D) imaging technologies are widely used recently to create content for movies, TV programs, games, etc. Although S3D content differs from 2D content by the use of binocular parallax to induce depth sensation, the relationship between depth control and the user experience remains unclear. In this study, the user experience was subjectively and objectively evaluated in order to determine the effectiveness of depth control, such as an expansion or reduction or a forward or backward shift in the range of maximum parallactic angles in the cross and uncross directions (depth bracket). Four types of S3D content were used in the subjective and objective evaluations. The depth brackets of comparison stimuli were modified in order to enhance the depth sensation corresponding to the content. Interpretation Based Quality (IBQ) methodology was used for the subjective evaluation and the heart rate was measured to evaluate the physiological effect. The results of the evaluations suggest the following two points. (1) Expansion/reduction of the depth bracket affects preference and enhances positive emotions to the S3D content. (2) Expansion/reduction of the depth bracket produces above-mentioned effects more notable than shifting the cross/uncross directions.

Rigid 3D-3D registration of TOF MRA integrating vessel segmentation for quantification of recurrence volumes after coiling cerebral aneurysm

International Nuclear Information System (INIS)

Saering, Dennis; Forkert, Nils Daniel; Fiehler, Jens; Ries, Thorsten

2012-01-01

A fast and reproducible quantification of the recurrence volume of coiled aneurysms is required to enable a more timely evaluation of new coils. This paper presents two registration schemes for the semi-automatic quantification of aneurysm recurrence volumes based on baseline and follow-up 3D MRA TOF datasets. The quantification of shape changes requires a previous definition of corresponding structures in both datasets. For this, two different rigid registration methods have been developed and evaluated. Besides a state-of-the-art rigid registration method, a second approach integrating vessel segmentations is presented. After registration, the aneurysm recurrence volume can be calculated based on the difference image. The computed volumes were compared to manually extracted volumes. An evaluation based on 20 TOF MRA datasets (baseline and follow-up) of ten patients showed that both registration schemes are generally capable of providing sufficient registration results. Regarding the quantification of aneurysm recurrence volumes, the results suggest that the second segmentation-based registration method yields better results, while a reduction of the computation and interaction time is achieved at the same time. The proposed registration scheme incorporating vessel segmentation enables an improved quantification of recurrence volumes of coiled aneurysms with reduced computation and interaction time. (orig.)

A hierarchical 3D segmentation method and the definition of vertebral body coordinate systems for QCT of the lumbar spine.

Science.gov (United States)

Mastmeyer, André; Engelke, Klaus; Fuchs, Christina; Kalender, Willi A

2006-08-01

We have developed a new hierarchical 3D technique to segment the vertebral bodies in order to measure bone mineral density (BMD) with high trueness and precision in volumetric CT datasets. The hierarchical approach starts with a coarse separation of the individual vertebrae, applies a variety of techniques to segment the vertebral bodies with increasing detail and ends with the definition of an anatomic coordinate system for each vertebral body, relative to which up to 41 trabecular and cortical volumes of interest are positioned. In a pre-segmentation step constraints consisting of Boolean combinations of simple geometric shapes are determined that enclose each individual vertebral body. Bound by these constraints viscous deformable models are used to segment the main shape of the vertebral bodies. Volume growing and morphological operations then capture the fine details of the bone-soft tissue interface. In the volumes of interest bone mineral density and content are determined. In addition, in the segmented vertebral bodies geometric parameters such as volume or the length of the main axes of inertia can be measured. Intra- and inter-operator precision errors of the segmentation procedure were analyzed using existing clinical patient datasets. Results for segmented volume, BMD, and coordinate system position were below 2.0%, 0.6%, and 0.7%, respectively. Trueness was analyzed using phantom scans. The bias of the segmented volume was below 4%; for BMD it was below 1.5%. The long-term goal of this work is improved fracture prediction and patient monitoring in the field of osteoporosis. A true 3D segmentation also enables an accurate measurement of geometrical parameters that may augment the clinical value of a pure BMD analysis.

The Implications of 3D Thermal Structure on 1D Atmospheric Retrieval

Energy Technology Data Exchange (ETDEWEB)

Blecic, Jasmina; Dobbs-Dixon, Ian [NYU Abu Dhabi, Abu Dhabi (United Arab Emirates); Greene, Thomas, E-mail: jasmina@nyu.edu [NASA Ames Research Center, Space Sciece and Astrobiology Division, M.S. 245-6, Moffett Field, CA 94035 (United States)

2017-10-20

Using the atmospheric structure from a 3D global radiation-hydrodynamic simulation of HD 189733b and the open-source Bayesian Atmospheric Radiative Transfer (BART) code, we investigate the difference between the secondary-eclipse temperature structure produced with a 3D simulation and the best-fit 1D retrieved model. Synthetic data are generated by integrating the 3D models over the Spitzer , the Hubble Space Telescope ( HST ), and the James Web Space Telescope ( JWST ) bandpasses, covering the wavelength range between 1 and 11 μ m where most spectroscopically active species have pronounced features. Using the data from different observing instruments, we present detailed comparisons between the temperature–pressure profiles recovered by BART and those from the 3D simulations. We calculate several averages of the 3D thermal structure and explore which particular thermal profile matches the retrieved temperature structure. We implement two temperature parameterizations that are commonly used in retrieval to investigate different thermal profile shapes. To assess which part of the thermal structure is best constrained by the data, we generate contribution functions for our theoretical model and each of our retrieved models. Our conclusions are strongly affected by the spectral resolution of the instruments included, their wavelength coverage, and the number of data points combined. We also see some limitations in each of the temperature parametrizations, as they are not able to fully match the complex curvatures that are usually produced in hydrodynamic simulations. The results show that our 1D retrieval is recovering a temperature and pressure profile that most closely matches the arithmetic average of the 3D thermal structure. When we use a higher resolution, more data points, and a parametrized temperature profile that allows more flexibility in the middle part of the atmosphere, we find a better match between the retrieved temperature and pressure profile and

The Implications of 3D Thermal Structure on 1D Atmospheric Retrieval

Science.gov (United States)

Blecic, Jasmina; Dobbs-Dixon, Ian; Greene, Thomas

2017-10-01

Using the atmospheric structure from a 3D global radiation-hydrodynamic simulation of HD 189733b and the open-source Bayesian Atmospheric Radiative Transfer (BART) code, we investigate the difference between the secondary-eclipse temperature structure produced with a 3D simulation and the best-fit 1D retrieved model. Synthetic data are generated by integrating the 3D models over the Spitzer, the Hubble Space Telescope (HST), and the James Web Space Telescope (JWST) bandpasses, covering the wavelength range between 1 and 11 μm where most spectroscopically active species have pronounced features. Using the data from different observing instruments, we present detailed comparisons between the temperature-pressure profiles recovered by BART and those from the 3D simulations. We calculate several averages of the 3D thermal structure and explore which particular thermal profile matches the retrieved temperature structure. We implement two temperature parameterizations that are commonly used in retrieval to investigate different thermal profile shapes. To assess which part of the thermal structure is best constrained by the data, we generate contribution functions for our theoretical model and each of our retrieved models. Our conclusions are strongly affected by the spectral resolution of the instruments included, their wavelength coverage, and the number of data points combined. We also see some limitations in each of the temperature parametrizations, as they are not able to fully match the complex curvatures that are usually produced in hydrodynamic simulations. The results show that our 1D retrieval is recovering a temperature and pressure profile that most closely matches the arithmetic average of the 3D thermal structure. When we use a higher resolution, more data points, and a parametrized temperature profile that allows more flexibility in the middle part of the atmosphere, we find a better match between the retrieved temperature and pressure profile and the

Analysis of 3-D images

Science.gov (United States)

Wani, M. Arif; Batchelor, Bruce G.

1992-03-01

Deriving generalized representation of 3-D objects for analysis and recognition is a very difficult task. Three types of representations based on type of an object is used in this paper. Objects which have well-defined geometrical shapes are segmented by using a fast edge region based segmentation technique. The segmented image is represented by plan and elevation of each part of the object if the object parts are symmetrical about their central axis. The plan and elevation concept enables representing and analyzing such objects quickly and efficiently. The second type of representation is used for objects having parts which are not symmetrical about their central axis. The segmented surface patches of such objects are represented by the 3-D boundary and the surface features of each segmented surface. Finally, the third type of representation is used for objects which don't have well-defined geometrical shapes (for example a loaf of bread). These objects are represented and analyzed from its features which are derived using a multiscale contour based technique. Anisotropic Gaussian smoothing technique is introduced to segment the contours at various scales of smoothing. A new merging technique is used which enables getting the current best estimate of break points at each scale. This new technique enables elimination of loss of accuracy of localization effects at coarser scales without using scale space tracking approach.

Magnegtic Resonance Imaging of Cranial Nerve Ⅴ～Ⅷ:Comparison of 3D-CISS and 3D-SPACE Sequences%磁共振3D-SPACE序列与3D-CISS序列对Ⅴ～Ⅷ颅神经成像的对照性研究

Institute of Scientific and Technical Information of China (English)

杜春华; 吴飞云; 祝因苏; 张伟; 刘波; 杨正强

2012-01-01

目的 通过MR可变翻转角的三维快速自旋回波(3D sampling perfection with application optimized contrasts using different flip angle evolutions,3 D-SPACE)序列与三维稳态进动结构相干(3D constructive interference in steady state,3D-CISS)序列对Ⅴ～Ⅷ颅神经成像质量进行比较,优化颅神经MRI序列.方法 对40例受检者用3D-SPACE序列与3D-CISS序列对Ⅴ～Ⅷ颅神经行MRI,同时行多平面重组(MPR),并对两种序列的图像显示情况进行比较.结果 3D-SPACE序列和3D-CISS序列均能显示三叉神经脑池段、外展神经脑池段、面神经脑池段、内听道段、前庭神经以及蜗神经脑池段;对Ⅴ～Ⅷ颅神经细微结构的显示,除三叉神经脑池段两种序列差异无统计学意义外,其余颅神经3 D-SPACE序列均优于3D-CISS序列,差异有统计学意义(P＜0.05)；3D-SPACE序列扫描时间比3D-CISS序列扫描时间短.结论 3D-SPACE序列对Ⅴ～Ⅷ颅神经成像质量优于3D-CISS,且扫描时间更短,因此3D-SPACE序列是目前显示Ⅴ～Ⅷ颅神经的较好方法.%Objective We compared the imaging quality of 3D sampling perfection with application optimized contrasts using different flip angle evolutions (SPACE) and 3D constructive interference in steady state (CISS) ,to optimize the Ⅴ ~ Ⅷ cranial nerve magnetic resonance ( MR) imaging. Methods Forty persons performed continuous 0. 5mm thick MRI of cranial nerve Ⅴ ~ Ⅷ with 3D SPACE , 3D CISS, and MPR reconstruction. The imaging quality of 3D SPACE and 3D CISS were compared. Results There was no statistically significant difference between the 3D SPACE and 3D CISS sequences in identification of the cistemal segment of trigeminal nerve, abducens nerve, the cisternal segment and canalicular segment of facial nerve, vestibular and cochlear nerve. Except trigeminal nerve, 3D SPACE has significantly higher quality than 3D-CISS in display details of other cranial nerves. Conclusion Continuous thin-slice MR

Nonenhanced magnetic resonance angiography (MRA) of the calf arteries at 3 Tesla: intraindividual comparison of 3D flow-dependent subtractive MRA and 2D flow-independent non-subtractive MRA

Energy Technology Data Exchange (ETDEWEB)

Knobloch, Gesine; Lauff, Marie-Teres; Hirsch, Sebastian; Hamm, Bernd; Wagner, Moritz [Charite - Universitaetsmedizin Berlin, Department of Radiology, Berlin (Germany); Schwenke, Carsten [SCO:SSiS Statistical Consulting, Berlin (Germany)

2016-12-15

To prospectively compare 3D flow-dependent subtractive MRA vs. 2D flow-independent non-subtractive MRA for assessment of the calf arteries at 3 Tesla. Forty-two patients with peripheral arterial occlusive disease underwent nonenhanced MRA of calf arteries at 3 Tesla with 3D flow-dependent subtractive MRA (fast spin echo sequence; 3D-FSE-MRA) and 2D flow-independent non-subtractive MRA (balanced steady-state-free-precession sequence; 2D-bSSFP-MRA). Moreover, all patients underwent contrast-enhanced MRA (CE-MRA) as standard-of-reference. Two readers performed a per-segment evaluation for image quality (4 = excellent to 0 = non-diagnostic) and severity of stenosis. Image quality scores of 2D-bSSFP-MRA were significantly higher compared to 3D-FSE-MRA (medians across readers: 4 vs. 3; p < 0.0001) with lower rates of non-diagnostic vessel segments on 2D-bSSFP-MRA (reader 1: <1 % vs. 15 %; reader 2: 1 % vs. 29 %; p < 0.05). Diagnostic performance of 2D-bSSFP-MRA and 3D-FSE-MRA across readers showed sensitivities of 89 % (214/240) vs. 70 % (168/240), p = 0.0153; specificities: 91 % (840/926) vs. 63 % (585/926), p < 0.0001; and diagnostic accuracies of 90 % (1054/1166) vs. 65 % (753/1166), p < 0.0001. 2D flow-independent non-subtractive MRA (2D-bSSFP-MRA) is a robust nonenhanced MRA technique for assessment of the calf arteries at 3 Tesla with significantly higher image quality and diagnostic accuracy compared to 3D flow-dependent subtractive MRA (3D-FSE-MRA). (orig.)

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

Documentation of archaeological excavation sites with conventional methods and tools such as hand drawings, measuring tape and archaeological notes is time consuming. This process is prone to human errors and the quality of the documentation depends on the qualification of the archaeologist on site. Use of modern technology and methods in 3D surveying and 3D robotics facilitate and improve this process. Computer-aided systems and databases improve the documentation quality and increase the speed of data acquisition. 3D laser scanning is the state of the art in modelling archaeological excavation sites, historical sites and even entire cities or landscapes. Modern laser scanners are capable of data acquisition of up to 1 million points per second. This provides a very detailed 3D point cloud of the environment. 3D point clouds and 3D models of an excavation site provide a better representation of the environment for the archaeologist and for documentation. The point cloud can be used both for further studies on the excavation and for the presentation of results. This paper introduces a Computer aided system for labelling archaeological excavations in 3D (CASTLE3D). Consisting of a set of tools for recording and georeferencing the 3D data from an excavation site, CASTLE3D is a novel documentation approach in industrial archaeology. It provides a 2D and 3D visualisation of the data and an easy-to-use interface that enables the archaeologist to select regions of interest and to interact with the data in both representations. The 2D visualisation and a 3D orthogonal view of the data provide cuts of the environment that resemble the traditional hand drawings. The 3D perspective view gives a realistic view of the environment. CASTLE3D is designed as an easy-to-use on-site semantic mapping tool for archaeologists. Each project contains a predefined set of semantic information that can be used to label findings in the data. Multiple regions of interest can be joined under

New Directions in 3D Medical Modeling: 3D-Printing Anatomy and Functions in Neurosurgical Planning

Science.gov (United States)

Árnadóttir, Íris; Gíslason, Magnús; Ólafsson, Ingvar

2017-01-01

This paper illustrates the feasibility and utility of combining cranial anatomy and brain function on the same 3D-printed model, as evidenced by a neurosurgical planning case study of a 29-year-old female patient with a low-grade frontal-lobe glioma. We herein report the rapid prototyping methodology utilized in conjunction with surgical navigation to prepare and plan a complex neurosurgery. The method introduced here combines CT and MRI images with DTI tractography, while using various image segmentation protocols to 3D model the skull base, tumor, and five eloquent fiber tracts. This 3D model is rapid-prototyped and coregistered with patient images and a reported surgical navigation system, establishing a clear link between the printed model and surgical navigation. This methodology highlights the potential for advanced neurosurgical preparation, which can begin before the patient enters the operation theatre. Moreover, the work presented here demonstrates the workflow developed at the National University Hospital of Iceland, Landspitali, focusing on the processes of anatomy segmentation, fiber tract extrapolation, MRI/CT registration, and 3D printing. Furthermore, we present a qualitative and quantitative assessment for fiber tract generation in a case study where these processes are applied in the preparation of brain tumor resection surgery. PMID:29065569

New Directions in 3D Medical Modeling: 3D-Printing Anatomy and Functions in Neurosurgical Planning

Directory of Open Access Journals (Sweden)

Paolo Gargiulo

2017-01-01

Full Text Available This paper illustrates the feasibility and utility of combining cranial anatomy and brain function on the same 3D-printed model, as evidenced by a neurosurgical planning case study of a 29-year-old female patient with a low-grade frontal-lobe glioma. We herein report the rapid prototyping methodology utilized in conjunction with surgical navigation to prepare and plan a complex neurosurgery. The method introduced here combines CT and MRI images with DTI tractography, while using various image segmentation protocols to 3D model the skull base, tumor, and five eloquent fiber tracts. This 3D model is rapid-prototyped and coregistered with patient images and a reported surgical navigation system, establishing a clear link between the printed model and surgical navigation. This methodology highlights the potential for advanced neurosurgical preparation, which can begin before the patient enters the operation theatre. Moreover, the work presented here demonstrates the workflow developed at the National University Hospital of Iceland, Landspitali, focusing on the processes of anatomy segmentation, fiber tract extrapolation, MRI/CT registration, and 3D printing. Furthermore, we present a qualitative and quantitative assessment for fiber tract generation in a case study where these processes are applied in the preparation of brain tumor resection surgery.

A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging

International Nuclear Information System (INIS)

Martin, Spencer; Rodrigues, George; Gaede, Stewart; Brophy, Mark; Barron, John L; Beauchemin, Steven S; Palma, David; Louie, Alexander V; Yu, Edward; Yaremko, Brian; Ahmad, Belal

2015-01-01

This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51  ±  1.92) to (97.27  ±  0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development. (paper)

A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging

Science.gov (United States)

Martin, Spencer; Brophy, Mark; Palma, David; Louie, Alexander V.; Yu, Edward; Yaremko, Brian; Ahmad, Belal; Barron, John L.; Beauchemin, Steven S.; Rodrigues, George; Gaede, Stewart

2015-02-01

This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51  ±  1.92) to (97.27  ±  0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development.

Vascular Structure Identification in Intraoperative 3D Contrast-Enhanced Ultrasound Data

Directory of Open Access Journals (Sweden)

Elisee Ilunga-Mbuyamba

2016-04-01

Full Text Available In this paper, a method of vascular structure identification in intraoperative 3D Contrast-Enhanced Ultrasound (CEUS data is presented. Ultrasound imaging is commonly used in brain tumor surgery to investigate in real time the current status of cerebral structures. The use of an ultrasound contrast agent enables to highlight tumor tissue, but also surrounding blood vessels. However, these structures can be used as landmarks to estimate and correct the brain shift. This work proposes an alternative method for extracting small vascular segments close to the tumor as landmark. The patient image dataset involved in brain tumor operations includes preoperative contrast T1MR (cT1MR data and 3D intraoperative contrast enhanced ultrasound data acquired before (3D-iCEUS s t a r t and after (3D-iCEUS e n d tumor resection. Based on rigid registration techniques, a preselected vascular segment in cT1MR is searched in 3D-iCEUS s t a r t and 3D-iCEUS e n d data. The method was validated by using three similarity measures (Normalized Gradient Field, Normalized Mutual Information and Normalized Cross Correlation. Tests were performed on data obtained from ten patients overcoming a brain tumor operation and it succeeded in nine cases. Despite the small size of the vascular structures, the artifacts in the ultrasound images and the brain tissue deformations, blood vessels were successfully identified.

Human Body 3D Posture Estimation Using Significant Points and Two Cameras

Science.gov (United States)

Juang, Chia-Feng; Chen, Teng-Chang; Du, Wei-Chin

2014-01-01

This paper proposes a three-dimensional (3D) human posture estimation system that locates 3D significant body points based on 2D body contours extracted from two cameras without using any depth sensors. The 3D significant body points that are located by this system include the head, the center of the body, the tips of the feet, the tips of the hands, the elbows, and the knees. First, a linear support vector machine- (SVM-) based segmentation method is proposed to distinguish the human body from the background in red, green, and blue (RGB) color space. The SVM-based segmentation method uses not only normalized color differences but also included angle between pixels in the current frame and the background in order to reduce shadow influence. After segmentation, 2D significant points in each of the two extracted images are located. A significant point volume matching (SPVM) method is then proposed to reconstruct the 3D significant body point locations by using 2D posture estimation results. Experimental results show that the proposed SVM-based segmentation method shows better performance than other gray level- and RGB-based segmentation approaches. This paper also shows the effectiveness of the 3D posture estimation results in different postures. PMID:24883422

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

International Nuclear Information System (INIS)

Reutter, B.W.; Klein, G.J.; Brennan, K.M.; Huesman, R.H.

1996-01-01

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

From 2D to 3D: The morphology, proliferation and differentiation of MC3T3-E1 on silk fibroin/chitosan matrices.

Science.gov (United States)

Li, Da-Wei; He, Feng-Li; He, Jin; Deng, Xudong; Liu, Ya-Li; Liu, Yang-Yang; Ye, Ya-Jing; Yin, Da-Chuan

2017-12-15

It has been widely accepted that cell culture in two-dimensional (2D) conditions may not be able to represent growth in three-dimensional (3D) conditions. Systematic comparisons between 2D and 3D cell cultures are needed to appropriately use the existing 2D results. In this work, we conducted a comparative study between 2D and 3D cell cultures of MC3T3-E1 using the same type of material (a mixture of silk fibroin (SF) and chitosan (CS)). Our results showed 3D SF/CS scaffold exhibited different effects on cell culture compared with the 2D cases. 1) The cells grown in 3D scaffold showed multiple morphologies. 2) The proliferation of cells in 3D scaffold was long-term and sustainable. 3) Cell differentiation occurred throughout the entire 3D scaffold. The results showed that cell culture in 3D SF/CS scaffold exhibited different features than 2D cases and 3D SF/CS scaffold could be a promising material for 3D cell culture. Copyright © 2017 Elsevier Ltd. All rights reserved.

1,25-Dihydroxyvitamin D3 (1,25(OH)2D3) Signaling Capacity and the Epithelial-Mesenchymal Transition in Non-Small Cell Lung Cancer (NSCLC): Implications for Use of 1,25(OH)2D3 in NSCLC Treatment

International Nuclear Information System (INIS)

Upadhyay, Santosh Kumar; Verone, Alissa; Shoemaker, Suzanne; Qin, Maochun; Liu, Song; Campbell, Moray; Hershberger, Pamela A.

2013-01-01

1,25-dihydroxyvitamin D 3 (1,25(OH) 2 D 3 ) exerts anti-proliferative activity by binding to the vitamin D receptor (VDR) and regulating gene expression. We previously reported that non-small cell lung cancer (NSCLC) cells which harbor epidermal growth factor receptor (EGFR) mutations display elevated VDR expression (VDR high ) and are vitamin D-sensitive. Conversely, those with K-ras mutations are VDR low and vitamin D-refractory. Because EGFR mutations are found predominately in NSCLC cells with an epithelial phenotype and K-ras mutations are more common in cells with a mesenchymal phenotype, we investigated the relationship between vitamin D signaling capacity and the epithelial mesenchymal transition (EMT). Using NSCLC cell lines and publically available lung cancer cell line microarray data, we identified a relationship between VDR expression, 1,25(OH) 2 D 3 sensitivity, and EMT phenotype. Further, we discovered that 1,25(OH) 2 D 3 induces E-cadherin and decreases EMT-related molecules SNAIL, ZEB1, and vimentin in NSCLC cells. 1,25(OH) 2 D 3 -mediated changes in gene expression are associated with a significant decrease in cell migration and maintenance of epithelial morphology. These data indicate that 1,25(OH) 2 D 3 opposes EMT in NSCLC cells. Because EMT is associated with increased migration, invasion, and chemoresistance, our data imply that 1,25(OH) 2 D 3 may prevent lung cancer progression in a molecularly defined subset of NSCLC patients

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

Science.gov (United States)

2013-01-01

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. PMID:23938087

FIJI Macro 3D ART VeSElecT: 3D Automated Reconstruction Tool for Vesicle Structures of Electron Tomograms.

Directory of Open Access Journals (Sweden)

Kristin Verena Kaltdorf

2017-01-01

Full Text Available Automatic image reconstruction is critical to cope with steadily increasing data from advanced microscopy. We describe here the Fiji macro 3D ART VeSElecT which we developed to study synaptic vesicles in electron tomograms. We apply this tool to quantify vesicle properties (i in embryonic Danio rerio 4 and 8 days past fertilization (dpf and (ii to compare Caenorhabditis elegans N2 neuromuscular junctions (NMJ wild-type and its septin mutant (unc-59(e261. We demonstrate development-specific and mutant-specific changes in synaptic vesicle pools in both models. We confirm the functionality of our macro by applying our 3D ART VeSElecT on zebrafish NMJ showing smaller vesicles in 8 dpf embryos then 4 dpf, which was validated by manual reconstruction of the vesicle pool. Furthermore, we analyze the impact of C. elegans septin mutant unc-59(e261 on vesicle pool formation and vesicle size. Automated vesicle registration and characterization was implemented in Fiji as two macros (registration and measurement. This flexible arrangement allows in particular reducing false positives by an optional manual revision step. Preprocessing and contrast enhancement work on image-stacks of 1nm/pixel in x and y direction. Semi-automated cell selection was integrated. 3D ART VeSElecT removes interfering components, detects vesicles by 3D segmentation and calculates vesicle volume and diameter (spherical approximation, inner/outer diameter. Results are collected in color using the RoiManager plugin including the possibility of manual removal of non-matching confounder vesicles. Detailed evaluation considered performance (detected vesicles and specificity (true vesicles as well as precision and recall. We furthermore show gain in segmentation and morphological filtering compared to learning based methods and a large time gain compared to manual segmentation. 3D ART VeSElecT shows small error rates and its speed gain can be up to 68 times faster in comparison to manual

Left-ventricle segmentation in real-time 3D echocardiography using a hybrid active shape model and optimal graph search approach

Science.gov (United States)

Zhang, Honghai; Abiose, Ademola K.; Campbell, Dwayne N.; Sonka, Milan; Martins, James B.; Wahle, Andreas

2010-03-01

Quantitative analysis of the left ventricular shape and motion patterns associated with left ventricular mechanical dyssynchrony (LVMD) is essential for diagnosis and treatment planning in congestive heart failure. Real-time 3D echocardiography (RT3DE) used for LVMD analysis is frequently limited by heavy speckle noise or partially incomplete data, thus a segmentation method utilizing learned global shape knowledge is beneficial. In this study, the endocardial surface of the left ventricle (LV) is segmented using a hybrid approach combining active shape model (ASM) with optimal graph search. The latter is used to achieve landmark refinement in the ASM framework. Optimal graph search translates the 3D segmentation into the detection of a minimum-cost closed set in a graph and can produce a globally optimal result. Various information-gradient, intensity distributions, and regional-property terms-are used to define the costs for the graph search. The developed method was tested on 44 RT3DE datasets acquired from 26 LVMD patients. The segmentation accuracy was assessed by surface positioning error and volume overlap measured for the whole LV as well as 16 standard LV regions. The segmentation produced very good results that were not achievable using ASM or graph search alone.

Anisotropic Diffusion based Brain MRI Segmentation and 3D Reconstruction

OpenAIRE

M. Arfan Jaffar; Sultan Zia; Ghaznafar Latif; AnwarM. Mirza; Irfan Mehmood; Naveed Ejaz; Sung Wook Baik

2012-01-01

In medical field visualization of the organs is very imperative for accurate diagnosis and treatment of any disease. Brain tumor diagnosis and surgery also required impressive 3D visualization of the brain to the radiologist. Detection and 3D reconstruction of brain tumors from MRI is a computationally time consuming and error-prone task. Proposed system detects and presents a 3D visualization model of the brain and tumor inside which greatly helps the radiologist to effectively diagnose and ...

WE-AB-204-03: A Novel 3D Printed Phantom for 4D PET/CT Imaging and SIB Radiotherapy Verification

International Nuclear Information System (INIS)

Soultan, D; Murphy, J; Moiseenko, V; Cervino, L; Gill, B

2015-01-01

Purpose: To construct and test a 3D printed phantom designed to mimic variable PET tracer uptake seen in lung tumor volumes. To assess segmentation accuracy of sub-volumes of the phantom following 4D PET/CT scanning with ideal and patient-specific respiratory motion. To plan, deliver and verify delivery of PET-driven, gated, simultaneous integrated boost (SIB) radiotherapy plans. Methods: A set of phantoms and inserts were designed and manufactured for a realistic representation of lung cancer gated radiotherapy steps from 4D PET/CT scanning to dose delivery. A cylindrical phantom (40x 120 mm) holds inserts for PET/CT scanning. The novel 3D printed insert dedicated to 4D PET/CT mimics high PET tracer uptake in the core and lower uptake in the periphery. This insert is a variable density porous cylinder (22.12×70 mm), ABS-P430 thermoplastic, 3D printed by uPrint SE Plus with inner void volume (5.5×42 mm). The square pores (1.8×1.8 mm2 each) fill 50% of outer volume, resulting in a 2:1 SUV ratio of PET-tracer in the void volume with respect to porous volume. A matching in size cylindrical phantom is dedicated to validate gated radiotherapy. It contains eight peripheral holes matching the location of the porous part of the 3D printed insert, and one central hole. These holes accommodate adaptors for Farmer-type ion chamber and cells vials. Results: End-to-end test were performed from 4D PET/CT scanning to transferring data to the planning system and target volume delineation. 4D PET/CT scans were acquired of the phantom with different respiratory motion patterns and gating windows. A measured 2:1 18F-FDG SUV ratio between inner void and outer volume matched the 3D printed design. Conclusion: The novel 3D printed phantom mimics variable PET tracer uptake typical of tumors. Obtained 4D PET/CT scans are suitable for segmentation, treatment planning and delivery in SIB gated treatments of NSCLC

Efficient Semi-Automatic 3D Segmentation for Neuron Tracing in Electron Microscopy Images

Science.gov (United States)

Jones, Cory; Liu, Ting; Cohan, Nathaniel Wood; Ellisman, Mark; Tasdizen, Tolga

2015-01-01

0.1. Background In the area of connectomics, there is a significant gap between the time required for data acquisition and dense reconstruction of the neural processes contained in the same dataset. Automatic methods are able to eliminate this timing gap, but the state-of-the-art accuracy so far is insufficient for use without user corrections. If completed naively, this process of correction can be tedious and time consuming. 0.2. New Method We present a new semi-automatic method that can be used to perform 3D segmentation of neurites in EM image stacks. It utilizes an automatic method that creates a hierarchical structure for recommended merges of superpixels. The user is then guided through each predicted region to quickly identify errors and establish correct links. 0.3. Results We tested our method on three datasets with both novice and expert users. Accuracy and timing were compared with published automatic, semi-automatic, and manual results. 0.4. Comparison with Existing Methods Post-automatic correction methods have also been used in [1] and [2]. These methods do not provide navigation or suggestions in the manner we present. Other semi-automatic methods require user input prior to the automatic segmentation such as [3] and [4] and are inherently different than our method. 0.5. Conclusion Using this method on the three datasets, novice users achieved accuracy exceeding state-of-the-art automatic results, and expert users achieved accuracy on par with full manual labeling but with a 70% time improvement when compared with other examples in publication. PMID:25769273

A facile route for 3D aerogels from nanostructured 1D and 2D materials

Science.gov (United States)

Jung, Sung Mi; Jung, Hyun Young; Dresselhaus, Mildred S.; Jung, Yung Joon; Kong, Jing

2012-01-01

Aerogels have numerous applications due to their high surface area and low densities. However, creating aerogels from a large variety of materials has remained an outstanding challenge. Here, we report a new methodology to enable aerogel production with a wide range of materials. The method is based on the assembly of anisotropic nano-objects (one-dimensional (1D) nanotubes, nanowires, or two-dimensional (2D) nanosheets) into a cross-linking network from their colloidal suspensions at the transition from the semi-dilute to the isotropic concentrated regime. The resultant aerogels have highly porous and ultrafine three-dimensional (3D) networks consisting of 1D (Ag, Si, MnO2, single-walled carbon nanotubes (SWNTs)) and 2D materials (MoS2, graphene, h-BN) with high surface areas, low densities, and high electrical conductivities. This method opens up a facile route for aerogel production with a wide variety of materials and tremendous opportunities for bio-scaffold, energy storage, thermoelectric, catalysis, and hydrogen storage applications. PMID:23152940

Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting

Science.gov (United States)

Hopp, T.; Zapf, M.; Ruiter, N. V.

2014-03-01

An essential processing step for comparison of Ultrasound Computer Tomography images to other modalities, as well as for the use in further image processing, is to segment the breast from the background. In this work we present a (semi-) automated 3D segmentation method which is based on the detection of the breast boundary in coronal slice images and a subsequent surface fitting. The method was evaluated using a software phantom and in-vivo data. The fully automatically processed phantom results showed that a segmentation of approx. 10% of the slices of a dataset is sufficient to recover the overall breast shape. Application to 16 in-vivo datasets was performed successfully using semi-automated processing, i.e. using a graphical user interface for manual corrections of the automated breast boundary detection. The processing time for the segmentation of an in-vivo dataset could be significantly reduced by a factor of four compared to a fully manual segmentation. Comparison to manually segmented images identified a smoother surface for the semi-automated segmentation with an average of 11% of differing voxels and an average surface deviation of 2mm. Limitations of the edge detection may be overcome by future updates of the KIT USCT system, allowing a fully-automated usage of our segmentation approach.

Applying microCT and 3D visualization to Jurassic silicified conifer seed cones: A virtual advantage over thin-sectioning1

Science.gov (United States)

Gee, Carole T.

2013-01-01

• Premise of the study: As an alternative to conventional thin-sectioning, which destroys fossil material, high-resolution X-ray computed tomography (also called microtomography or microCT) integrated with scientific visualization, three-dimensional (3D) image segmentation, size analysis, and computer animation is explored as a nondestructive method of imaging the internal anatomy of 150-million-year-old conifer seed cones from the Late Jurassic Morrison Formation, USA, and of recent and other fossil cones. • Methods: MicroCT was carried out on cones using a General Electric phoenix v|tome|x s 240D, and resulting projections were processed with visualization software to produce image stacks of serial single sections for two-dimensional (2D) visualization, 3D segmented reconstructions with targeted structures in color, and computer animations. • Results: If preserved in differing densities, microCT produced images of internal fossil tissues that showed important characters such as seed phyllotaxy or number of seeds per cone scale. Color segmentation of deeply embedded seeds highlighted the arrangement of seeds in spirals. MicroCT of recent cones was even more effective. • Conclusions: This is the first paper on microCT integrated with 3D segmentation and computer animation applied to silicified seed cones, which resulted in excellent 2D serial sections and segmented 3D reconstructions, revealing features requisite to cone identification and understanding of strobilus construction. PMID:25202495

Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach.

Science.gov (United States)

Valverde, Sergi; Cabezas, Mariano; Roura, Eloy; González-Villà, Sandra; Pareto, Deborah; Vilanova, Joan C; Ramió-Torrentà, Lluís; Rovira, Àlex; Oliver, Arnau; Lladó, Xavier

2017-07-15

In this paper, we present a novel automated method for White Matter (WM) lesion segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a cascade of two 3D patch-wise convolutional neural networks (CNN). The first network is trained to be more sensitive revealing possible candidate lesion voxels while the second network is trained to reduce the number of misclassified voxels coming from the first network. This cascaded CNN architecture tends to learn well from a small (n≤35) set of labeled data of the same MRI contrast, which can be very interesting in practice, given the difficulty to obtain manual label annotations and the large amount of available unlabeled Magnetic Resonance Imaging (MRI) data. We evaluate the accuracy of the proposed method on the public MS lesion segmentation challenge MICCAI2008 dataset, comparing it with respect to other state-of-the-art MS lesion segmentation tools. Furthermore, the proposed method is also evaluated on two private MS clinical datasets, where the performance of our method is also compared with different recent public available state-of-the-art MS lesion segmentation methods. At the time of writing this paper, our method is the best ranked approach on the MICCAI2008 challenge, outperforming the rest of 60 participant methods when using all the available input modalities (T1-w, T2-w and FLAIR), while still in the top-rank (3rd position) when using only T1-w and FLAIR modalities. On clinical MS data, our approach exhibits a significant increase in the accuracy segmenting of WM lesions when compared with the rest of evaluated methods, highly correlating (r≥0.97) also with the expected lesion volume. Copyright © 2017 Elsevier Inc. All rights reserved.

17 CFR 240.15c3-1d - Satisfactory Subordination Agreements (Appendix D to 17 CFR 240.15c3-1).

Science.gov (United States)

2010-04-01

... 17 Commodity and Securities Exchanges 3 2010-04-01 2010-04-01 false Satisfactory Subordination...-Counter Markets § 240.15c3-1d Satisfactory Subordination Agreements (Appendix D to 17 CFR 240.15c3-1). (a) Introduction. (1) This Appendix sets forth minimum and non-exclusive requirements for satisfactory...

3D printing of intracranial artery stenosis based on the source images of magnetic resonance angiograph.

Science.gov (United States)

Xu, Wei-Hai; Liu, Jia; Li, Ming-Li; Sun, Zhao-Yong; Chen, Jie; Wu, Jian-Huang

2014-08-01

Three dimensional (3D) printing techniques for brain diseases have not been widely studied. We attempted to 'print' the segments of intracranial arteries based on magnetic resonance imaging. Three dimensional magnetic resonance angiography (MRA) was performed on two patients with middle cerebral artery (MCA) stenosis. Using scale-adaptive vascular modeling, 3D vascular models were constructed from the MRA source images. The magnified (ten times) regions of interest (ROI) of the stenotic segments were selected and fabricated by a 3D printer with a resolution of 30 µm. A survey to 8 clinicians was performed to evaluate the accuracy of 3D printing results as compared with MRA findings (4 grades, grade 1: consistent with MRA and provide additional visual information; grade 2: consistent with MRA; grade 3: not consistent with MRA; grade 4: not consistent with MRA and provide probable misleading information). If a 3D printing vessel segment was ideally matched to the MRA findings (grade 2 or 1), a successful 3D printing was defined. Seven responders marked "grade 1" to 3D printing results, while one marked "grade 4". Therefore, 87.5% of the clinicians considered the 3D printing were successful. Our pilot study confirms the feasibility of using 3D printing technique in the research field of intracranial artery diseases. Further investigations are warranted to optimize this technique and translate it into clinical practice.

2D to 3D conversion implemented in different hardware

Science.gov (United States)

Ramos-Diaz, Eduardo; Gonzalez-Huitron, Victor; Ponomaryov, Volodymyr I.; Hernandez-Fragoso, Araceli

2015-02-01

Conversion of available 2D data for release in 3D content is a hot topic for providers and for success of the 3D applications, in general. It naturally completely relies on virtual view synthesis of a second view given by original 2D video. Disparity map (DM) estimation is a central task in 3D generation but still follows a very difficult problem for rendering novel images precisely. There exist different approaches in DM reconstruction, among them manually and semiautomatic methods that can produce high quality DMs but they demonstrate hard time consuming and are computationally expensive. In this paper, several hardware implementations of designed frameworks for an automatic 3D color video generation based on 2D real video sequence are proposed. The novel framework includes simultaneous processing of stereo pairs using the following blocks: CIE L*a*b* color space conversions, stereo matching via pyramidal scheme, color segmentation by k-means on an a*b* color plane, and adaptive post-filtering, DM estimation using stereo matching between left and right images (or neighboring frames in a video), adaptive post-filtering, and finally, the anaglyph 3D scene generation. Novel technique has been implemented on DSP TMS320DM648, Matlab's Simulink module over a PC with Windows 7, and using graphic card (NVIDIA Quadro K2000) demonstrating that the proposed approach can be applied in real-time processing mode. The time values needed, mean Similarity Structural Index Measure (SSIM) and Bad Matching Pixels (B) values for different hardware implementations (GPU, Single CPU, and DSP) are exposed in this paper.

3D Assessment of Features Associated With Transvalvular Aortic Regurgitation After TAVR: A Real-Time 3D TEE Study.

Science.gov (United States)

Shibayama, Kentaro; Mihara, Hirotsugu; Jilaihawi, Hasan; Berdejo, Javier; Harada, Kenji; Itabashi, Yuji; Siegel, Robert; Makkar, Raj R; Shiota, Takahiro

2016-02-01

This study of 3-dimensional (3D) transesophageal echocardiography (TEE) aimed to demonstrate features associated with transvalvular aortic regurgitation (AR) after transcatheter aortic valve replacement (TAVR) and to confirm the fact that a gap between the native aortic annulus and prosthesis is associated with paravalvular AR. The mechanism of AR after TAVR, particularly that of transvalvular AR, has not been evaluated adequately. All patients with severe aortic stenosis who underwent TAVR with the Sapien device (Edwards Lifesciences, Irvine, California) had 3D TEE of the pre-procedural native aortic annulus and the post-procedural prosthetic valve. In the 201 patients studied, the total AR was mild in 67 patients (33%), moderate in 21 patients (10%), and severe in no patients. There were 20 patients with transvalvular AR and 82 patients with paravalvular AR. Fourteen patients had both transvalvular and paravalvular AR. Patients with transvalvular AR had larger prosthetic expansion (p prosthetic shape at the prosthetic commissure level (p prosthetic commissures in relation to the native commissures, than the patients without transvalvular AR. Age (odds ratio [OR]: 1.05; 95% confidence interval [CI]: 1.01 to 1.09; p 3D TEE successfully demonstrated the features associated with transvalvular AR, such as large prosthetic expansion, elliptical prosthetic shape, and anti-anatomical position of prosthesis. Additionally, effective area oversizing was associated with paravalvular AR. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

3D morphological measurement of whole slide histological vasculature reconstructions

Science.gov (United States)

Xu, Yiwen; Pickering, J. G.; Nong, Zengxuan; Ward, Aaron D.

2016-03-01

Properties of the microvasculature that contribute to tissue perfusion can be assessed using immunohistochemistry on 2D histology sections. However, the vasculature is inherently 3D and the ability to measure and visualize the vessel wall components in 3D will aid in detecting focal pathologies. Our objectives were (1) to develop a method for 3D measurement and visualization of microvasculature in 3D, (2) to compare the normal and regenerated post-ischemia mouse hind limb microvasculature, and (3) to compare the 2D and 3D vessel morphology measures. Vessels were stained for smooth muscle using 3,3'-Diaminobenzidine (DAB) immunostain for both normal (n = 6 mice) and regenerated vasculature (n = 5 mice). 2D vessel segmentations were reconstructed into 3D using landmark based registration. No substantial bias was found in the 2D measurements relative to 3D, but larger differences were observed for individual vessels oriented non-orthogonally to the plane of sectioning. A larger value of area, perimeter, and vessel wall thickness was found in the normal vasculature as compared to the regenerated vasculature, for both the 2D and 3D measurements (p pathologies on a whole slide level.

Hepatitis B virus subgenotypes D1 and D3 are prevalent in Pakistan

Directory of Open Access Journals (Sweden)

Chakravarty Runu

2009-01-01

Full Text Available Abstract Background As the hepatitis B genotyping is important for assessing its clinical implications and geographical distribution, the sub-genotypes have been found useful for determination of specific genomic markers related to hepatocarcinogenesis. In Pakistan, there is no reported data on molecular evolutionary analysis of HBV. A study was, therefore, much needed to evaluate the spectra of mutations present in the strains prevalent here. Findings to confirm specificity of PCR typing, phylogenetic analysis of the pre-S1 region and the divergence was studied through 13 sequences of 362 bp (accession number EF432765 – EF432777. A total of 315 serum samples, selected from HBsAg positive patients representing the major ethnic groups, residing in Karachi, Sindh were tested for genotyping. Genotype D (219/315 was found to be the most prevalent (70% amongst our patients. The rest of the genotypes A and a mixture of A and D (AD were distributed as 20%, and 10% respectively. Phylogenetic tree demonstrated clustering of 11 samples with subgenotype D1 sequences and the remaining two strains on a branch within D3 samples. All samples intermixed with strains from other countries and were found to be closely related to Indian, Iranian and Egyptian HBV strains with 98.7 – 99.0% homology. Conclusion This study confirms the predominance of genotype D in southeastern Asia and presence of subgenotypes DI and D3 in the Pakistani infected patients. More studies are required to investigate the reason for fewer inclusions of D3 compared to the D1 in Pakistani HBV strains.

An Ensemble of 2D Convolutional Neural Networks for Tumor Segmentation

DEFF Research Database (Denmark)

Lyksborg, Mark; Puonti, Oula; Agn, Mikael

2015-01-01

Accurate tumor segmentation plays an important role in radiosurgery planning and the assessment of radiotherapy treatment efficacy. In this paper we propose a method combining an ensemble of 2D convolutional neural networks for doing a volumetric segmentation of magnetic resonance images....... The segmentation is done in three steps; first the full tumor region, is segmented from the background by a voxel-wise merging of the decisions of three networks learned from three orthogonal planes, next the segmentation is refined using a cellular automaton-based seed growing method known as growcut. Finally......, within-tumor sub-regions are segmented using an additional ensemble of networks trained for the task. We demonstrate the method on the MICCAI Brain Tumor Segmentation Challenge dataset of 2014, and show improved segmentation accuracy compared to an axially trained 2D network and an ensemble segmentation...

1,5-Anhydro-D-fructose from D-fructose

DEFF Research Database (Denmark)

Dekany, Gyula; Lundt, Inge; Niedermaier, Fabian

2007-01-01

1,5-Anhydro-D-fructose was efficiently prepared from D-fructose via regiospecific 1,5-anhydro ring formation of 2,3-O-isopropylidene-1-O-methyl(tolyl)sulfonyl-D-fructopyranose and subsequent deprotection.......1,5-Anhydro-D-fructose was efficiently prepared from D-fructose via regiospecific 1,5-anhydro ring formation of 2,3-O-isopropylidene-1-O-methyl(tolyl)sulfonyl-D-fructopyranose and subsequent deprotection....

Hematopoietic Stem and Progenitor Cell Expansion in Contact with Mesenchymal Stromal Cells in a Hanging Drop Model Uncovers Disadvantages of 3D Culture.

Science.gov (United States)

Schmal, Olga; Seifert, Jan; Schäffer, Tilman E; Walter, Christina B; Aicher, Wilhelm K; Klein, Gerd

2016-01-01

Efficient ex vivo expansion of hematopoietic stem cells with a concomitant preservation of stemness and self-renewal potential is still an unresolved ambition. Increased numbers of methods approaching this issue using three-dimensional (3D) cultures were reported. Here, we describe a simplified 3D hanging drop model for the coculture of cord blood-derived CD34(+) hematopoietic stem and progenitor cells (HSPCs) with bone marrow-derived mesenchymal stromal cells (MSCs). When seeded as a mixed cell suspension, MSCs segregated into tight spheroids. Despite the high expression of niche-specific extracellular matrix components by spheroid-forming MSCs, HSPCs did not migrate into the spheroids in the initial phase of coculture, indicating strong homotypic interactions of MSCs. After one week, however, HSPC attachment increased considerably, leading to spheroid collapse as demonstrated by electron microscopy and immunofluorescence staining. In terms of HSPC proliferation, the conventional 2D coculture system was superior to the hanging drop model. Furthermore, expansion of primitive hematopoietic progenitors was more favored in 2D than in 3D, as analyzed in colony-forming assays. Conclusively, our data demonstrate that MSCs, when arranged with a spread (monolayer) shape, exhibit better HSPC supportive qualities than spheroid-forming MSCs. Therefore, 3D systems are not necessarily superior to traditional 2D culture in this regard.

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.

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)

Soultan, D; Murphy, J; James, C; Hoh, C; Moiseenko, V; Cervino, L; Gill, B

2015-01-01

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

Factorising the 3D topologically twisted index

Science.gov (United States)

Cabo-Bizet, Alejandro

2017-04-01

We explore the path integration — upon the contour of hermitian (non-auxliary) field configurations — of topologically twisted N=2 Chern-Simons-matter theory (TTCSM) on {S}_2 times a segment. In this way, we obtain the formula for the 3D topologically twisted index, first as a convolution of TTCSM on {S}_2 times halves of {S}_1 , second as TTCSM on {S}_2 times {S}_1 — with a puncture, — and third as TTCSM on {S}_2× {S}_1 . In contradistinction to the first two cases, in the third case, the vector multiplet auxiliary field D is constrained to be anti-hermitian.

MRI segmentation by active contours model, 3D reconstruction, and visualization

Science.gov (United States)

Lopez-Hernandez, Juan M.; Velasquez-Aguilar, J. Guadalupe

2005-02-01

The advances in 3D data modelling methods are becoming increasingly popular in the areas of biology, chemistry and medical applications. The Nuclear Magnetic Resonance Imaging (NMRI) technique has progressed at a spectacular rate over the past few years, its uses have been spread over many applications throughout the body in both anatomical and functional investigations. In this paper we present the application of Zernike polynomials for 3D mesh model of the head using the contour acquired of cross-sectional slices by active contour model extraction and we propose the visualization with OpenGL 3D Graphics of the 2D-3D (slice-surface) information for the diagnostic aid in medical applications.

Functional selectivity of allosteric interactions within G protein-coupled receptor oligomers: the dopamine D1-D3 receptor heterotetramer.

Science.gov (United States)

Guitart, Xavier; Navarro, Gemma; Moreno, Estefania; Yano, Hideaki; Cai, Ning-Sheng; Sánchez-Soto, Marta; Kumar-Barodia, Sandeep; Naidu, Yamini T; Mallol, Josefa; Cortés, Antoni; Lluís, Carme; Canela, Enric I; Casadó, Vicent; McCormick, Peter J; Ferré, Sergi

2014-10-01

The dopamine D1 receptor-D3 receptor (D1R-D3R) heteromer is being considered as a potential therapeutic target for neuropsychiatric disorders. Previous studies suggested that this heteromer could be involved in the ability of D3R agonists to potentiate locomotor activation induced by D1R agonists. It has also been postulated that its overexpression plays a role in L-dopa-induced dyskinesia and in drug addiction. However, little is known about its biochemical properties. By combining bioluminescence resonance energy transfer, bimolecular complementation techniques, and cell-signaling experiments in transfected cells, evidence was obtained for a tetrameric stoichiometry of the D1R-D3R heteromer, constituted by two interacting D1R and D3R homodimers coupled to Gs and Gi proteins, respectively. Coactivation of both receptors led to the canonical negative interaction at the level of adenylyl cyclase signaling, to a strong recruitment of β-arrestin-1, and to a positive cross talk of D1R and D3R agonists at the level of mitogen-activated protein kinase (MAPK) signaling. Furthermore, D1R or D3R antagonists counteracted β-arrestin-1 recruitment and MAPK activation induced by D3R and D1R agonists, respectively (cross-antagonism). Positive cross talk and cross-antagonism at the MAPK level were counteracted by specific synthetic peptides with amino acid sequences corresponding to D1R transmembrane (TM) domains TM5 and TM6, which also selectively modified the quaternary structure of the D1R-D3R heteromer, as demonstrated by complementation of hemiproteins of yellow fluorescence protein fused to D1R and D3R. These results demonstrate functional selectivity of allosteric modulations within the D1R-D3R heteromer, which can be involved with the reported behavioral synergism of D1R and D3R agonists. U.S. Government work not protected by U.S. copyright.

Functional Selectivity of Allosteric Interactions within G Protein–Coupled Receptor Oligomers: The Dopamine D1-D3 Receptor Heterotetramer

Science.gov (United States)

Guitart, Xavier; Navarro, Gemma; Moreno, Estefania; Yano, Hideaki; Cai, Ning-Sheng; Sánchez-Soto, Marta; Kumar-Barodia, Sandeep; Naidu, Yamini T.; Mallol, Josefa; Cortés, Antoni; Lluís, Carme; Canela, Enric I.; Casadó, Vicent; McCormick, Peter J.

2014-01-01

The dopamine D1 receptor–D3 receptor (D1R-D3R) heteromer is being considered as a potential therapeutic target for neuropsychiatric disorders. Previous studies suggested that this heteromer could be involved in the ability of D3R agonists to potentiate locomotor activation induced by D1R agonists. It has also been postulated that its overexpression plays a role in L-dopa–induced dyskinesia and in drug addiction. However, little is known about its biochemical properties. By combining bioluminescence resonance energy transfer, bimolecular complementation techniques, and cell-signaling experiments in transfected cells, evidence was obtained for a tetrameric stoichiometry of the D1R–D3R heteromer, constituted by two interacting D1R and D3R homodimers coupled to Gs and Gi proteins, respectively. Coactivation of both receptors led to the canonical negative interaction at the level of adenylyl cyclase signaling, to a strong recruitment of β-arrestin-1, and to a positive cross talk of D1R and D3R agonists at the level of mitogen-activated protein kinase (MAPK) signaling. Furthermore, D1R or D3R antagonists counteracted β-arrestin-1 recruitment and MAPK activation induced by D3R and D1R agonists, respectively (cross-antagonism). Positive cross talk and cross-antagonism at the MAPK level were counteracted by specific synthetic peptides with amino acid sequences corresponding to D1R transmembrane (TM) domains TM5 and TM6, which also selectively modified the quaternary structure of the D1R-D3R heteromer, as demonstrated by complementation of hemiproteins of yellow fluorescence protein fused to D1R and D3R. These results demonstrate functional selectivity of allosteric modulations within the D1R-D3R heteromer, which can be involved with the reported behavioral synergism of D1R and D3R agonists. PMID:25097189

Acute D2/D3 dopaminergic agonism but chronic D2/D3 antagonism prevents NMDA antagonist neurotoxicity.

Science.gov (United States)

Farber, Nuri B; Nemmers, Brian; Noguchi, Kevin K

2006-09-15

Antagonists of the N-methyl-D-aspartate (NMDA) glutamate receptor, most likely by producing disinhibtion in complex circuits, acutely produce psychosis and cognitive disturbances in humans, and neurotoxicity in rodents. Studies examining NMDA Receptor Hypofunction (NRHypo) neurotoxicity in animals, therefore, may provide insights into the pathophysiology of psychotic disorders. Dopaminergic D2 and/or D3 agents can modify psychosis over days to weeks, suggesting involvement of these transmitter system(s). We studied the ability of D2/D3 agonists and antagonists to modify NRHypo neurotoxicity both after a one-time acute exposure and after chronic daily exposure. Here we report that D2/D3 dopamine agonists, probably via D3 receptors, prevent NRHypo neurotoxicity when given acutely. The protective effect with D2/D3 agonists is not seen after chronic daily dosing. In contrast, the antipsychotic haloperidol does not affect NRHypo neurotoxicity when given acutely at D2/D3 doses. However, after chronic daily dosing of 1, 3, or 5 weeks, haloperidol does prevent NRHypo neurotoxicity with longer durations producing greater protection. Understanding the changes that occur in the NRHypo circuit after chronic exposure to dopaminergic agents could provide important clues into the pathophysiology of psychotic disorders.

A Spatial Reference Grid for Real-Time Autonomous Underwater Modeling using 3-D Sonar

Energy Technology Data Exchange (ETDEWEB)

Auran, P.G.

1996-12-31

The offshore industry has recognized the need for intelligent underwater robotic vehicles. This doctoral thesis deals with autonomous underwater vehicles (AUVs) and concentrates on a data representation for real-time image formation and analysis. Its main objective is to develop a 3-D image representation suitable for autonomous perception objectives underwater, assuming active sonar as the main sensor for perception. The main contributions are: (1) A dynamical image representation for 3-D range data, (2) A basic electronic circuit and software system for 3-D sonar sampling and amplitude thresholding, (3) A model for target reliability, (4) An efficient connected components algorithm for 3-D segmentation, (5) A method for extracting general 3-D geometrical representations from segmented echo clusters, (6) Experimental results of planar and curved target modeling. 142 refs., 120 figs., 10 tabs.

Ds1*(2860) and Ds3*(2860): candidates for 1D charmed-strange mesons

International Nuclear Information System (INIS)

Song, Qin-Tao; Chen, Dian-Yong; Liu, Xiang; Matsuki, Takayuki

2015-01-01

Newly observed two charmed-strange resonances, D s1 * (2860) and D s3 * (2860), are investigated by calculating their Okubo-Zweig-Iizuka-allowed strong decays, which shows that they are suitable candidates for the 1 3 D 1 and 1 3 D 3 states in the charmed-strange meson family. Our study also predicts other main decay modes of D s1 * (2860) and D s3 * (2860), which can be accessible at the future experiment. In addition, the decay behaviors of the spin partners of D s1 * (2860) and D s3 * (2860), i.e., 1D(2 - ) and 1D'(2 - ), are predicted in this work, which are still missing at present. The experimental search for the missing 1D(2 - ) and 1D'(2 - ) charmed-strange mesons is an intriguing and challenging task for further experiments. (orig.)

The vitamin D analogue ED71 but Not 1,25(OH2D3 targets HIF1α protein in osteoclasts.

Directory of Open Access Journals (Sweden)

Yuiko Sato

Full Text Available Although both an active form of the vitamin D metabolite, 1,25(OH2D3, and the vitamin D analogue, ED71 have been used to treat osteoporosis, anti-bone resorbing activity is reportedly seen only in ED71- but not in 1,25(OH2D3 -treated patients. In addition, how ED71 inhibits osteoclast activity in patients has not been fully characterized. Recently, HIF1α expression in osteoclasts was demonstrated to be required for development of post-menopausal osteoporosis. Here we show that ED71 but not 1,25(OH2D3, suppress HIF1α protein expression in osteoclasts in vitro. We found that 1,25(OH2D3 or ED71 function in osteoclasts requires the vitamin D receptor (VDR. ED71 was significantly less effective in inhibiting M-CSF and RANKL-stimulated osteoclastogenesis than was 1,25(OH2D3 in vitro. Downregulation of c-Fos protein and induction of Ifnβ mRNA in osteoclasts, both of which reportedly block osteoclastogenesis induced by 1,25(OH2D3 in vitro, were both significantly higher following treatment with 1,25(OH2D3 than with ED71. Thus, suppression of HIF1α protein activity in osteoclasts in vitro, which is more efficiently achieved by ED71 rather than by 1,25(OH2D3, could be a reliable read-out in either developing or screening reagents targeting osteoporosis.

Measurement of the spin-forbidden decay rate (3s3d)1D2¿(3s3p)3 P2,1 in 24Mg

DEFF Research Database (Denmark)

Therkildsen, K. T.; Jensen, Brian Bak; Ryder, C. P.

2009-01-01

We have measured the spin-forbidden decay rate from (3s3d)D12¿(3s3p)P32,1 in M24g atoms trapped in a magneto-optical trap. The total decay rate, summing up both exit channels (3s3p)P31 and (3s3p)P32 , yields 196±10s-1 in excellent agreement with resent relativistic many-body calculations of Porse...

A Marked Poisson Process Driven Latent Shape Model for 3D Segmentation of Reflectance Confocal Microscopy Image Stacks of Human Skin

Science.gov (United States)

Ghanta, Sindhu; Jordan, Michael I.; Kose, Kivanc; Brooks, Dana H.; Rajadhyaksha, Milind; Dy, Jennifer G.

2016-01-01

Segmenting objects of interest from 3D datasets is a common problem encountered in biological data. Small field of view and intrinsic biological variability combined with optically subtle changes of intensity, resolution and low contrast in images make the task of segmentation difficult, especially for microscopy of unstained living or freshly excised thick tissues. Incorporating shape information in addition to the appearance of the object of interest can often help improve segmentation performance. However, shapes of objects in tissue can be highly variable and design of a flexible shape model that encompasses these variations is challenging. To address such complex segmentation problems, we propose a unified probabilistic framework that can incorporate the uncertainty associated with complex shapes, variable appearance and unknown locations. The driving application which inspired the development of this framework is a biologically important segmentation problem: the task of automatically detecting and segmenting the dermal-epidermal junction (DEJ) in 3D reflectance confocal microscopy (RCM) images of human skin. RCM imaging allows noninvasive observation of cellular, nuclear and morphological detail. The DEJ is an important morphological feature as it is where disorder, disease and cancer usually start. Detecting the DEJ is challenging because it is a 2D surface in a 3D volume which has strong but highly variable number of irregularly spaced and variably shaped “peaks and valleys”. In addition, RCM imaging resolution, contrast and intensity vary with depth. Thus a prior model needs to incorporate the intrinsic structure while allowing variability in essentially all its parameters. We propose a model which can incorporate objects of interest with complex shapes and variable appearance in an unsupervised setting by utilizing domain knowledge to build appropriate priors of the model. Our novel strategy to model this structure combines a spatial Poisson process

"3D fusion" echocardiography improves 3D left ventricular assessment: comparison with 2D contrast echocardiography.

Science.gov (United States)

Augustine, Daniel; Yaqub, Mohammad; Szmigielski, Cezary; Lima, Eduardo; Petersen, Steffen E; Becher, Harald; Noble, J Alison; Leeson, Paul

2015-02-01

Three-dimensional fusion echocardiography (3DFE) is a novel postprocessing approach that utilizes imaging data acquired from multiple 3D acquisitions. We assessed image quality, endocardial border definition, and cardiac wall motion in patients using 3DFE compared to standard 3D images (3D) and results obtained with contrast echocardiography (2DC). Twenty-four patients (mean age 66.9 ± 13 years, 17 males, 7 females) undergoing 2DC had three, noncontrast, 3D apical volumes acquired at rest. Images were fused using an automated image fusion approach. Quality of the 3DFE was compared to both 3D and 2DC based on contrast-to-noise ratio (CNR) and endocardial border definition. We then compared clinical wall-motion score index (WMSI) calculated from 3DFE and 3D to those obtained from 2DC images. Fused 3D volumes had significantly improved CNR (8.92 ± 1.35 vs. 6.59 ± 1.19, P echocardiography (1.06 ± 0.09 vs. 1.07 ± 0.15, P = 0.69), whereas unfused images produced significantly more variable results (1.19 ± 0.30). This was confirmed by a better intraclass correlation coefficient (ICC 0.72; 95% CI 0.32-0.88) relative to comparisons with unfused images (ICC 0.56; 95% CI 0.02-0.81). 3DFE significantly improves left ventricular image quality compared to unfused 3D in a patient population and allows noncontrast assessment of wall motion that approaches that achieved with 2D contrast echocardiography. © 2014, Wiley Periodicals, Inc.

Analysis of linear measurements on 3D surface models using CBCT data segmentation obtained by automatic standard pre-set thresholds in two segmentation software programs: an in vitro study.

Science.gov (United States)

Poleti, Marcelo Lupion; Fernandes, Thais Maria Freire; Pagin, Otávio; Moretti, Marcela Rodrigues; Rubira-Bullen, Izabel Regina Fischer

2016-01-01

The aim of this in vitro study was to evaluate the reliability and accuracy of linear measurements on three-dimensional (3D) surface models obtained by standard pre-set thresholds in two segmentation software programs. Ten mandibles with 17 silica markers were scanned for 0.3-mm voxels in the i-CAT Classic (Imaging Sciences International, Hatfield, PA, USA). Twenty linear measurements were carried out by two observers two times on the 3D surface models: the Dolphin Imaging 11.5 (Dolphin Imaging & Management Solutions, Chatsworth, CA, USA), using two filters(Translucent and Solid-1), and in the InVesalius 3.0.0 (Centre for Information Technology Renato Archer, Campinas, SP, Brazil). The physical measurements were made by another observer two times using a digital caliper on the dry mandibles. Excellent intra- and inter-observer reliability for the markers, physical measurements, and 3D surface models were found (intra-class correlation coefficient (ICC) and Pearson's r ≥ 0.91). The linear measurements on 3D surface models by Dolphin and InVesalius software programs were accurate (Dolphin Solid-1 > InVesalius > Dolphin Translucent). The highest absolute and percentage errors were obtained for the variable R1-R1 (1.37 mm) and MF-AC (2.53 %) in the Dolphin Translucent and InVesalius software, respectively. Linear measurements on 3D surface models obtained by standard pre-set thresholds in the Dolphin and InVesalius software programs are reliable and accurate compared with physical measurements. Studies that evaluate the reliability and accuracy of the 3D models are necessary to ensure error predictability and to establish diagnosis, treatment plan, and prognosis in a more realistic way.

[Reconstruction assisted by 3D printing in maxillofacial surgery].

Science.gov (United States)

Ernoult, C; Bouletreau, P; Meyer, C; Aubry, S; Breton, P; Bachelet, J-T

2015-04-01

3-dimensional models (3D) appeared in the medical field 20 years ago. The recent development of consumer 3D printers explains the renewed interest in this technology. We describe the technical and practical modalities of this surgical tool, illustrated by concrete examples. The OsiriX(®) software (version 5.8.5, Geneva, Switzerland) was used for 3D surface reconstruction of the area of interest, the generation and export of ".stl" file. The NetFabb(®) software (Basic version 5.1.1, Lupburg, Germany) provided the preparation of ".stl" file. The 3D-printer was an Up plus 2 Easy 120(®) (PP3DP, Beijing Technology Co. TierTime Ltd., Chine). The printer used fused deposition modeling. The softwar Up!(®) allowed the 3d impression as required. The first case illustrated the value of 3D printing in the upper (frontal sinus and orbital roof). The second case concerned the preconfiguration of the osteosynthesis material for a complex fracture of the midface through the "mirroring" system. The third case showed the conformation of a prereconstruction for segmental mandibulectomy. Current 3D-printers are easy to use and represent a promising solution for medical prototyping. The 3D printing will quickly become undeniable because of its advantages: information sharing, simulation, surgical guides, pedagogy. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

The 3-dimensional core model DYN3D

Energy Technology Data Exchange (ETDEWEB)

Grundmann, U.; Mittag, S.; Rohde, U.

1999-01-01

Analyzing the safety margins in transients and accidents of nuclear reactors 3-dimensional models of the core were used to avoid conservative assumptions needed for point kinetics or 1-dimensional models. Therefore, the 3D code DYN3D has been developed for the analysis of reactivity initiated accidents (RIA) in thermal nuclear reactors. The power distributions are calculated with the help of nodal expansion methods (NEM) for hexagonal and Cartesian geometry. The fuel rod model and the thermohydraulic part provide fuel temperatures, coolant temperatures and densities as well as boron concentrations for the calculation of feedback effects on the basis of cross section libraries generated by cell codes. Safety relevant parameters like maximum fuel and cladding temperatures, critical heat flux and degree of cladding oxidation are estimated. DYN3D can analyze RIA initiated by moved control rods and/or perturbations of the coolant flow. Stationary and transient boundary conditions for the coolant flow, the core inlet temperatures and boron concentrations at the core inlet have to be given. For analyzing more complex transients the code DYN3D is coupled with the plant model ATHLET of the GRS. The extensive validation work accomplished for DYN3D is presented in several examples. Some applications of the code are described. (orig.) [Deutsch] Die Verwendung 3-dimensionaler Kernmodelle zur Untersuchung der Sicherheitsreserven bei Uebergangsprozessen und Stoerfaellen in Kernreaktoren vermeidet konservative Annahmen, die bei der Benutzung des Punktmodells oder 1-dimensionaler Modelle erforderlich sind. Aus diesen Gruenden wurde das 3-dimensionale Rechenprogramm DYN3D fuer die Untersuchung von Reaktivitaetsstoerfaellen in thermischen Reaktoren entwickelt. Die Leistungsverteilung wird mit nodalen Methoden fuer hexagonale oder kartesische Geometrie berechnet. Das Brennstabmodell und der thermohydraulische Teil von DYN3D liefert die Brennstofftemperaturen, Kuehlmitteltemperaturen

Dopamine D1 and D3 receptor polypharmacology as a potential treatment approach for substance use disorder.

Science.gov (United States)

Galaj, Ewa; Ewing, Scott; Ranaldi, Robert

2018-06-01

In the search for efficacious pharmacotherapies to treat cocaine addiction much attention has been given to agents targeting dopamine D1 or D3 receptors because of the involvement of these receptors in drug-related behaviors. D1-like and D3 receptor partial agonists and antagonists have been shown to reduce drug reward, reinstatement of drug seeking and conditioned place preference in rodents and non-human primates. However, translation of these encouraging results to clinical settings has been limited due to a number of factors including toxicity, poor pharmacokinetic properties and extrapyramidal and sedative side effects. This review highlights the role of D1 and D3 receptors in drug reward and seeking, the discovery of D1-D3 heteromers and their potential as targets in the treatment of addiction. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Stability and accuracy of 3D neutron transport simulations using the 2D/1D method in MPACT

International Nuclear Information System (INIS)

Collins, Benjamin; Stimpson, Shane; Kelley, Blake W.; Young, Mitchell T.H.; Kochunas, Brendan; Graham, Aaron; Larsen, Edward W.; Downar, Thomas; Godfrey, Andrew

2016-01-01

A consistent “2D/1D” neutron transport method is derived from the 3D Boltzmann transport equation, to calculate fuel-pin-resolved neutron fluxes for realistic full-core Pressurized Water Reactor (PWR) problems. The 2D/1D method employs the Method of Characteristics to discretize the radial variables and a lower order transport solution to discretize the axial variable. This paper describes the theory of the 2D/1D method and its implementation in the MPACT code, which has become the whole-core deterministic neutron transport solver for the Consortium for Advanced Simulations of Light Water Reactors (CASL) core simulator VERA-CS. Several applications have been performed on both leadership-class and industry-class computing clusters. Results are presented for whole-core solutions of the Watts Bar Nuclear Power Station Unit 1 and compared to both continuous-energy Monte Carlo results and plant data.

Stability and accuracy of 3D neutron transport simulations using the 2D/1D method in MPACT

Energy Technology Data Exchange (ETDEWEB)

Collins, Benjamin, E-mail: collinsbs@ornl.gov [Oak Ridge National Laboratory, One Bethel Valley Rd., Oak Ridge, TN 37831 (United States); Stimpson, Shane, E-mail: stimpsonsg@ornl.gov [Oak Ridge National Laboratory, One Bethel Valley Rd., Oak Ridge, TN 37831 (United States); Kelley, Blake W., E-mail: kelleybl@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Young, Mitchell T.H., E-mail: youngmit@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Kochunas, Brendan, E-mail: bkochuna@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Graham, Aaron, E-mail: aarograh@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Larsen, Edward W., E-mail: edlarsen@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Downar, Thomas, E-mail: downar@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Godfrey, Andrew, E-mail: godfreyat@ornl.gov [Oak Ridge National Laboratory, One Bethel Valley Rd., Oak Ridge, TN 37831 (United States)

2016-12-01

A consistent “2D/1D” neutron transport method is derived from the 3D Boltzmann transport equation, to calculate fuel-pin-resolved neutron fluxes for realistic full-core Pressurized Water Reactor (PWR) problems. The 2D/1D method employs the Method of Characteristics to discretize the radial variables and a lower order transport solution to discretize the axial variable. This paper describes the theory of the 2D/1D method and its implementation in the MPACT code, which has become the whole-core deterministic neutron transport solver for the Consortium for Advanced Simulations of Light Water Reactors (CASL) core simulator VERA-CS. Several applications have been performed on both leadership-class and industry-class computing clusters. Results are presented for whole-core solutions of the Watts Bar Nuclear Power Station Unit 1 and compared to both continuous-energy Monte Carlo results and plant data.

Final Hazard Categorization for the Remediation of the 118-D-1, 118-D-2, 118-D-3, 118-H-1, 118-H-2 and 118-H-3 Solid Waste Burial Grounds

Energy Technology Data Exchange (ETDEWEB)

K. L. Vialetti

2008-05-20

This report presents the final hazard categorization for the remediation of the 118-D-1, 118-D-2, and 118-D-3 Burial Grounds located within the 100-D/DR Area of the Hanford Site and the 118-H-1, 118-H-2, and 118-H-3 Burial Grounds located within the 100-H Area of the Hanford Site.