Weighted hybrid technique for recommender system

Science.gov (United States)

Suriati, S.; Dwiastuti, Meisyarah; Tulus, T.

2017-12-01

Recommender system becomes very popular and has important role in an information system or webpages nowadays. A recommender system tries to make a prediction of which item a user may like based on his activity on the system. There are some familiar techniques to build a recommender system, such as content-based filtering and collaborative filtering. Content-based filtering does not involve opinions from human to make the prediction, while collaborative filtering does, so collaborative filtering can predict more accurately. However, collaborative filtering cannot give prediction to items which have never been rated by any user. In order to cover the drawbacks of each approach with the advantages of other approach, both approaches can be combined with an approach known as hybrid technique. Hybrid technique used in this work is weighted technique in which the prediction score is combination linear of scores gained by techniques that are combined.The purpose of this work is to show how an approach of weighted hybrid technique combining content-based filtering and item-based collaborative filtering can work in a movie recommender system and to show the performance comparison when both approachare combined and when each approach works alone. There are three experiments done in this work, combining both techniques with different parameters. The result shows that the weighted hybrid technique that is done in this work does not really boost the performance up, but it helps to give prediction score for unrated movies that are impossible to be recommended by only using collaborative filtering.

Comparative Study of Retinal Vessel Segmentation Based on Global Thresholding Techniques

Directory of Open Access Journals (Sweden)

Temitope Mapayi

2015-01-01

Full Text Available Due to noise from uneven contrast and illumination during acquisition process of retinal fundus images, the use of efficient preprocessing techniques is highly desirable to produce good retinal vessel segmentation results. This paper develops and compares the performance of different vessel segmentation techniques based on global thresholding using phase congruency and contrast limited adaptive histogram equalization (CLAHE for the preprocessing of the retinal images. The results obtained show that the combination of preprocessing technique, global thresholding, and postprocessing techniques must be carefully chosen to achieve a good segmentation performance.

IMAGE SEGMENTATION BASED ON MARKOV RANDOM FIELD AND WATERSHED TECHNIQUES

Institute of Scientific and Technical Information of China (English)

纳瑟; 刘重庆

2002-01-01

This paper presented a method that incorporates Markov Random Field(MRF), watershed segmentation and merging techniques for performing image segmentation and edge detection tasks. MRF is used to obtain an initial estimate of x regions in the image under process where in MRF model, gray level x, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The process needs an initial segmented result. An initial segmentation is got based on K-means clustering technique and the minimum distance, then the region process in modeled by MRF to obtain an image contains different intensity regions. Starting from this we calculate the gradient values of that image and then employ a watershed technique. When using MRF method it obtains an image that has different intensity regions and has all the edge and region information, then it improves the segmentation result by superimpose closed and an accurate boundary of each region using watershed algorithm. After all pixels of the segmented regions have been processed, a map of primitive region with edges is generated. Finally, a merge process based on averaged mean values is employed. The final segmentation and edge detection result is one closed boundary per actual region in the image.

Lung Segmentation Refinement based on Optimal Surface Finding Utilizing a Hybrid Desktop/Virtual Reality User Interface

Science.gov (United States)

Sun, Shanhui; Sonka, Milan; Beichel, Reinhard R.

2013-01-01

Recently, the optimal surface finding (OSF) and layered optimal graph image segmentation of multiple objects and surfaces (LOGISMOS) approaches have been reported with applications to medical image segmentation tasks. While providing high levels of performance, these approaches may locally fail in the presence of pathology or other local challenges. Due to the image data variability, finding a suitable cost function that would be applicable to all image locations may not be feasible. This paper presents a new interactive refinement approach for correcting local segmentation errors in the automated OSF-based segmentation. A hybrid desktop/virtual reality user interface was developed for efficient interaction with the segmentations utilizing state-of-the-art stereoscopic visualization technology and advanced interaction techniques. The user interface allows a natural and interactive manipulation on 3-D surfaces. The approach was evaluated on 30 test cases from 18 CT lung datasets, which showed local segmentation errors after employing an automated OSF-based lung segmentation. The performed experiments exhibited significant increase in performance in terms of mean absolute surface distance errors (2.54 ± 0.75 mm prior to refinement vs. 1.11 ± 0.43 mm post-refinement, p ≪ 0.001). Speed of the interactions is one of the most important aspects leading to the acceptance or rejection of the approach by users expecting real-time interaction experience. The average algorithm computing time per refinement iteration was 150 ms, and the average total user interaction time required for reaching complete operator satisfaction per case was about 2 min. This time was mostly spent on human-controlled manipulation of the object to identify whether additional refinement was necessary and to approve the final segmentation result. The reported principle is generally applicable to segmentation problems beyond lung segmentation in CT scans as long as the underlying segmentation

Lung segmentation refinement based on optimal surface finding utilizing a hybrid desktop/virtual reality user interface.

Science.gov (United States)

Sun, Shanhui; Sonka, Milan; Beichel, Reinhard R

2013-01-01

Recently, the optimal surface finding (OSF) and layered optimal graph image segmentation of multiple objects and surfaces (LOGISMOS) approaches have been reported with applications to medical image segmentation tasks. While providing high levels of performance, these approaches may locally fail in the presence of pathology or other local challenges. Due to the image data variability, finding a suitable cost function that would be applicable to all image locations may not be feasible. This paper presents a new interactive refinement approach for correcting local segmentation errors in the automated OSF-based segmentation. A hybrid desktop/virtual reality user interface was developed for efficient interaction with the segmentations utilizing state-of-the-art stereoscopic visualization technology and advanced interaction techniques. The user interface allows a natural and interactive manipulation of 3-D surfaces. The approach was evaluated on 30 test cases from 18 CT lung datasets, which showed local segmentation errors after employing an automated OSF-based lung segmentation. The performed experiments exhibited significant increase in performance in terms of mean absolute surface distance errors (2.54±0.75 mm prior to refinement vs. 1.11±0.43 mm post-refinement, p≪0.001). Speed of the interactions is one of the most important aspects leading to the acceptance or rejection of the approach by users expecting real-time interaction experience. The average algorithm computing time per refinement iteration was 150 ms, and the average total user interaction time required for reaching complete operator satisfaction was about 2 min per case. This time was mostly spent on human-controlled manipulation of the object to identify whether additional refinement was necessary and to approve the final segmentation result. The reported principle is generally applicable to segmentation problems beyond lung segmentation in CT scans as long as the underlying segmentation utilizes the

Techniques on semiautomatic segmentation using the Adobe Photoshop

Science.gov (United States)

Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae

2005-04-01

The purpose of this research is to enable anybody to semiautomatically segment the anatomical structures in the MRIs, CTs, and other medical images on the personal computer. The segmented images are used for making three-dimensional images, which are helpful in medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was MR scanned to make 557 MRIs, which were transferred to a personal computer. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL; successively, manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a likewise manner, 11 anatomical structures in the 8,500 anatomcial images were segmented. Also, 12 brain and 10 heart anatomical structures in anatomical images were segmented. Proper segmentation was verified by making and examining the coronal, sagittal, and three-dimensional images from the segmented images. During semiautomatic segmentation on Adobe Photoshop, suitable algorithm could be used, the extent of automatization could be regulated, convenient user interface could be used, and software bugs rarely occurred. The techniques of semiautomatic segmentation using Adobe Photoshop are expected to be widely used for segmentation of the anatomical structures in various medical images.

Retinal Vessels Segmentation Techniques and Algorithms: A Survey

Directory of Open Access Journals (Sweden)

Jasem Almotiri

2018-01-01

Full Text Available Retinal vessels identification and localization aim to separate the different retinal vasculature structure tissues, either wide or narrow ones, from the fundus image background and other retinal anatomical structures such as optic disc, macula, and abnormal lesions. Retinal vessels identification studies are attracting more and more attention in recent years due to non-invasive fundus imaging and the crucial information contained in vasculature structure which is helpful for the detection and diagnosis of a variety of retinal pathologies included but not limited to: Diabetic Retinopathy (DR, glaucoma, hypertension, and Age-related Macular Degeneration (AMD. With the development of almost two decades, the innovative approaches applying computer-aided techniques for segmenting retinal vessels are becoming more and more crucial and coming closer to routine clinical applications. The purpose of this paper is to provide a comprehensive overview for retinal vessels segmentation techniques. Firstly, a brief introduction to retinal fundus photography and imaging modalities of retinal images is given. Then, the preprocessing operations and the state of the art methods of retinal vessels identification are introduced. Moreover, the evaluation and validation of the results of retinal vessels segmentation are discussed. Finally, an objective assessment is presented and future developments and trends are addressed for retinal vessels identification techniques.

Segmental Refinement: A Multigrid Technique for Data Locality

KAUST Repository

Adams, Mark F.; Brown, Jed; Knepley, Matt; Samtaney, Ravi

2016-01-01

We investigate a domain decomposed multigrid technique, termed segmental refinement, for solving general nonlinear elliptic boundary value problems. We extend the method first proposed in 1994 by analytically and experimentally investigating its complexity. We confirm that communication of traditional parallel multigrid is eliminated on fine grids, with modest amounts of extra work and storage, while maintaining the asymptotic exactness of full multigrid. We observe an accuracy dependence on the segmental refinement subdomain size, which was not considered in the original analysis. We present a communication complexity analysis that quantifies the communication costs ameliorated by segmental refinement and report performance results with up to 64K cores on a Cray XC30.

Segmental Refinement: A Multigrid Technique for Data Locality

KAUST Repository

Adams, Mark F.

2016-08-04

We investigate a domain decomposed multigrid technique, termed segmental refinement, for solving general nonlinear elliptic boundary value problems. We extend the method first proposed in 1994 by analytically and experimentally investigating its complexity. We confirm that communication of traditional parallel multigrid is eliminated on fine grids, with modest amounts of extra work and storage, while maintaining the asymptotic exactness of full multigrid. We observe an accuracy dependence on the segmental refinement subdomain size, which was not considered in the original analysis. We present a communication complexity analysis that quantifies the communication costs ameliorated by segmental refinement and report performance results with up to 64K cores on a Cray XC30.

Immobilization of Mo(IV) complex in hybrid matrix obtained via sol-gel technique

Energy Technology Data Exchange (ETDEWEB)

Marques, C.; Sousa, A.M.; Freire, C.; Neves, I.C.; Fonseca, A.M.; Silva, C.J.R

2003-10-06

A molybdenum(IV) complex, trans-bis-[1,2-bis(diphenylphosphino)ethane]-fluoro-(diazopropano) -molybdenum tetraphenylborate, [MoF(DIAZO)(dppe){sub 2}][BPh{sub 4}], was prepared and immobilized in a hybrid matrix synthesized by the sol-gel process. The host matrix, designated as U(500), is an organic-inorganic network material, classed as ureasil, that combines a reticulated siliceous backbone linked by short polyether-based segments. Urea bridges make the link between these two components, and the polymerization of silicate substituted terminal groups generates the inorganic network. The free Mo(IV) complex and all new materials were characterized by spectroscopic techniques (FT-IR and UV-Vis) and thermal analysis (DSC). The ionic conductivity of the resulting material was also studied. The results indicate that immobilized Mo(IV) complex has kept its solid-state structure, although there is evidence of inter-molecular interactions between the Mo(IV) complex and some groups/atoms of the hybrid host matrix.

Improved helicopter aeromechanical stability analysis using segmented constrained layer damping and hybrid optimization

Science.gov (United States)

Liu, Qiang; Chattopadhyay, Aditi

2000-06-01

Aeromechanical stability plays a critical role in helicopter design and lead-lag damping is crucial to this design. In this paper, the use of segmented constrained damping layer (SCL) treatment and composite tailoring is investigated for improved rotor aeromechanical stability using formal optimization technique. The principal load-carrying member in the rotor blade is represented by a composite box beam, of arbitrary thickness, with surface bonded SCLs. A comprehensive theory is used to model the smart box beam. A ground resonance analysis model and an air resonance analysis model are implemented in the rotor blade built around the composite box beam with SCLs. The Pitt-Peters dynamic inflow model is used in air resonance analysis under hover condition. A hybrid optimization technique is used to investigate the optimum design of the composite box beam with surface bonded SCLs for improved damping characteristics. Parameters such as stacking sequence of the composite laminates and placement of SCLs are used as design variables. Detailed numerical studies are presented for aeromechanical stability analysis. It is shown that optimum blade design yields significant increase in rotor lead-lag regressive modal damping compared to the initial system.

Protaper--hybrid technique.

Science.gov (United States)

Simon, Stephane; Lumley, Philip; Tomson, Phillip; Pertot, Wilhelm-Joseph; Machtou, Pierre

2008-03-01

Crown down preparation is the most known and described technique since the introduction of Nickel Titanium (NiTi) rotary instruments in endodontics. This technique gives good results but has limitations, such as not addressing the initial anatomy of oval or dumb-bell shaped canals. The specific design of the Protaper instruments allows use of them with a different technique and, specifically, with a brushing motion in the body of the canal. The recent introduction of hand Protaper files has expanded the range of application of this system, especially in curved canals. The 'hybrid technique', using rotary and hand files, and the advantages of the combination of both instruments, are clearly described in this article. Used with this technique, the Protaper is a very safe system to use, and more controllable, for both inexperienced and experienced practitioners alike, than other systems. To understand the precautions needed with rotary files, and how to use them to preserve the anatomy of the canal and get a tapered shaping, even in severely curved canals.

Segmentation Technique for Image Indexing and Retrieval on Discrete Cosines Domain

Directory of Open Access Journals (Sweden)

Suhendro Yusuf Irianto

2013-03-01

Full Text Available This paper uses region growing segmentation technique to segment the Discrete Cosines (DC  image. The problem of content Based image retrieval (CBIR is the luck of accuracy in matching between image query and image in the database as it matches object and background in the same time.   This the reason previous CBIR techniques inaccurate and time consuming. The CBIR   based on the segmented region proposed in this work  separates object from background as CBIR need only match the object not the background.  By using region growing technique on DC image, it reduces the number of image       regions.    The proposed of recursive region growing is not new technique but its application on DC images to build    indexing keys is quite new and not yet presented by many     authors. The experimental results show  that the proposed methods on   segmented images present good precision which are higher than 0.60 on all classes . It can be concluded that  region growing segmented based CBIR more efficient    compare to DC images  in term of their precision 0.59 and 0.75, respectively. Moreover,  DC based CBIR  can save time and simplify algorithm compare to DCT images.

Segmented arch or continuous arch technique? A rational approach

Directory of Open Access Journals (Sweden)

Sergei Godeiro Fernandes Rabelo Caldas

2014-04-01

Full Text Available This study aims at revising the biomechanical principles of the segmented archwire technique as well as describing the clinical conditions in which the rational use of scientific biomechanics is essential to optimize orthodontic treatment and reduce the side effects produced by the straight wire technique.

Hybrid soft computing approaches research and applications

CERN Document Server

Dutta, Paramartha; Chakraborty, Susanta

2016-01-01

The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

Segmentation techniques for extracting humans from thermal images

CSIR Research Space (South Africa)

Dickens, JS

2011-11-01

Full Text Available A pedestrian detection system for underground mine vehicles is being developed that requires the segmentation of people from thermal images in underground mine tunnels. A number of thresholding techniques are outlined and their performance on a...

Hybrid of Fuzzy Logic and Random Walker Method for Medical Image Segmentation

OpenAIRE

Jasdeep Kaur; Manish Mahajan

2015-01-01

The procedure of partitioning an image into various segments to reform an image into somewhat that is more significant and easier to analyze, defined as image segmentation. In real world applications, noisy images exits and there could be some measurement errors too. These factors affect the quality of segmentation, which is of major concern in medical fields where decisions about patients’ treatment are based on information extracted from radiological images. Several algorithms and technique...

Comparison of atlas-based techniques for whole-body bone segmentation

DEFF Research Database (Denmark)

Arabi, Hossein; Zaidi, Habib

2017-01-01

out in terms of estimating bone extraction accuracy from whole-body MRI using standard metrics, such as Dice similarity (DSC) and relative volume difference (RVD) considering bony structures obtained from intensity thresholding of the reference CT images as the ground truth. Considering the Dice....../MRI. To this end, a variety of atlas-based segmentation strategies commonly used in medical image segmentation and pseudo-CT generation were implemented and evaluated in terms of whole-body bone segmentation accuracy. Bone segmentation was performed on 23 whole-body CT/MR image pairs via leave-one-out cross...... validation procedure. The evaluated segmentation techniques include: (i) intensity averaging (IA), (ii) majority voting (MV), (iii) global and (iv) local (voxel-wise) weighting atlas fusion frameworks implemented utilizing normalized mutual information (NMI), normalized cross-correlation (NCC) and mean...

Hybridized centroid technique for 3D Molodensky-Badekas ...

African Journals Online (AJOL)

In view of this, the present study developed and tested two new hybrid centroid techniques known as the harmonic-quadratic mean and arithmetic-quadratic mean centroids. The proposed hybrid approaches were compared with the geometric mean, harmonic mean, median, quadratic mean and arithmetic mean. In addition ...

Atlas-based segmentation technique incorporating inter-observer delineation uncertainty for whole breast

International Nuclear Information System (INIS)

Bell, L R; Pogson, E M; Metcalfe, P; Holloway, L; Dowling, J A

2017-01-01

Accurate, efficient auto-segmentation methods are essential for the clinical efficacy of adaptive radiotherapy delivered with highly conformal techniques. Current atlas based auto-segmentation techniques are adequate in this respect, however fail to account for inter-observer variation. An atlas-based segmentation method that incorporates inter-observer variation is proposed. This method is validated for a whole breast radiotherapy cohort containing 28 CT datasets with CTVs delineated by eight observers. To optimise atlas accuracy, the cohort was divided into categories by mean body mass index and laterality, with atlas’ generated for each in a leave-one-out approach. Observer CTVs were merged and thresholded to generate an auto-segmentation model representing both inter-observer and inter-patient differences. For each category, the atlas was registered to the left-out dataset to enable propagation of the auto-segmentation from atlas space. Auto-segmentation time was recorded. The segmentation was compared to the gold-standard contour using the dice similarity coefficient (DSC) and mean absolute surface distance (MASD). Comparison with the smallest and largest CTV was also made. This atlas-based auto-segmentation method incorporating inter-observer variation was shown to be efficient (<4min) and accurate for whole breast radiotherapy, with good agreement (DSC>0.7, MASD <9.3mm) between the auto-segmented contours and CTV volumes. (paper)

Segmental Refinement: A Multigrid Technique for Data Locality

Energy Technology Data Exchange (ETDEWEB)

Adams, Mark [Columbia Univ., New York, NY (United States). Applied Physics and Applied Mathematics Dept.; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2014-10-27

We investigate a technique - segmental refinement (SR) - proposed by Brandt in the 1970s as a low memory multigrid method. The technique is attractive for modern computer architectures because it provides high data locality, minimizes network communication, is amenable to loop fusion, and is naturally highly parallel and asynchronous. The network communication minimization property was recognized by Brandt and Diskin in 1994; we continue this work by developing a segmental refinement method for a finite volume discretization of the 3D Laplacian on massively parallel computers. An understanding of the asymptotic complexities, required to maintain textbook multigrid efficiency, are explored experimentally with a simple SR method. A two-level memory model is developed to compare the asymptotic communication complexity of a proposed SR method with traditional parallel multigrid. Performance and scalability are evaluated with a Cray XC30 with up to 64K cores. We achieve modest improvement in scalability from traditional parallel multigrid with a simple SR implementation.

Bonding techniques for hybrid active pixel sensors (HAPS)

Energy Technology Data Exchange (ETDEWEB)

Bigas, M. [Centre Nacional de Microelectronica, CNM-IMB (CSIC), Campus Universitat Autonoma de Barcelona, 08193 Bellaterra, Barcelona (Spain)]. E-mail: Marc.Bigas@cnm.es; Cabruja, E. [Centre Nacional de Microelectronica, CNM-IMB (CSIC), Campus Universitat Autonoma de Barcelona, 08193 Bellaterra, Barcelona (Spain)]. E-mail: Enric.Cabruja@cnm.es; Lozano, M. [Centre Nacional de Microelectronica, CNM-IMB (CSIC), Campus Universitat Autonoma de Barcelona, 08193 Bellaterra, Barcelona (Spain)

2007-05-01

A hybrid active pixel sensor (HAPS) consists of an array of sensing elements which is connected to an electronic read-out unit. The most used way to connect these two different devices is bump bonding. This interconnection technique is very suitable for these systems because it allows a very fine pitch and a high number of I/Os. However, there are other interconnection techniques available such as direct bonding. This paper, as a continuation of a review [M. Lozano, E. Cabruja, A. Collado, J. Santander, M. Ullan, Nucl. Instr. and Meth. A 473 (1-2) (2001) 95-101] published in 2001, presents an update of the different advanced bonding techniques available for manufacturing a hybrid active pixel detector.

Using wavelet denoising and mathematical morphology in the segmentation technique applied to blood cells images

OpenAIRE

Boix García, Macarena; Cantó Colomina, Begoña

2013-01-01

Accurate image segmentation is used in medical diagnosis since this technique is a noninvasive pre-processing step for biomedical treatment. In this work we present an efficient segmentation method for medical image analysis. In particular, with this method blood cells can be segmented. For that, we combine the wavelet transform with morphological operations. Moreover, the wavelet thresholding technique is used to eliminate the noise and prepare the image for suitable segmentation. In wavelet...

Region-based Image Segmentation by Watershed Partition and DCT Energy Compaction

Directory of Open Access Journals (Sweden)

Chi-Man Pun

2012-02-01

Full Text Available An image segmentation approach by improved watershed partition and DCT energy compaction has been proposed in this paper. The proposed energy compaction, which expresses the local texture of an image area, is derived by exploiting the discrete cosine transform. The algorithm is a hybrid segmentation technique which is composed of three stages. First, the watershed transform is utilized by preprocessing techniques: edge detection and marker in order to partition the image in to several small disjoint patches, while the region size, mean and variance features are used to calculate region cost for combination. Then in the second merging stage the DCT transform is used for energy compaction which is a criterion for texture comparison and region merging. Finally the image can be segmented into several partitions. The experimental results show that the proposed approach achieved very good segmentation robustness and efficiency, when compared to other state of the art image segmentation algorithms and human segmentation results.

Status of the segment interconnect, cable segment ancillary logic, and the cable segment hybrid driver projects

International Nuclear Information System (INIS)

Swoboda, C.; Barsotti, E.; Chappa, S.; Downing, R.; Goeransson, G.; Lensy, D.; Moore, G.; Rotolo, C.; Urish, J.

1985-01-01

The FASTBUS Segment Interconnect (SI) provides a communication path between two otherwise independent, asynchronous bus segments. In particular, the Segment Interconnect links a backplane crate segment to a cable segment. All standard FASTBUS address and data transactions can be passed through the SI or any number of SIs and segments in a path. Thus systems of arbitrary connection complexity can be formed, allowing simultaneous independent processing, yet still permitting devices associated with one segment to be accessed from others. The model S1 Segment Interconnect and the Cable Segment Ancillary Logic covered in this report comply with all the mandatory features stated in the FASTBUS specification document DOE/ER-0189. A block diagram of the SI is shown

Treatment of critical lower limb ischemia using a hybrid technique

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Ricardo Wagner da Costa Moreira

2014-09-01

Full Text Available Critical ischemia of a lower limb is a condition that threatens its viability and must be treated promptly to avoid major amputation. Revascularization is the most effective treatment method and is performed using surgical or endovascular techniques. For patients with thoracoabdominal aortic aneurysms, combining these two approaches into a "hybrid technique" makes it possible to treat patients who could not be adequately treated by either technique in isolation. We report on a case of lower limb critical ischemia treated using a combination of surgery and endovascular techniques, in an application of the hybrid technique in a different arterial bed.

A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology.

Science.gov (United States)

Kumar, Neeraj; Verma, Ruchika; Sharma, Sanuj; Bhargava, Surabhi; Vahadane, Abhishek; Sethi, Amit

2017-07-01

Nuclear segmentation in digital microscopic tissue images can enable extraction of high-quality features for nuclear morphometrics and other analysis in computational pathology. Conventional image processing techniques, such as Otsu thresholding and watershed segmentation, do not work effectively on challenging cases, such as chromatin-sparse and crowded nuclei. In contrast, machine learning-based segmentation can generalize across various nuclear appearances. However, training machine learning algorithms requires data sets of images, in which a vast number of nuclei have been annotated. Publicly accessible and annotated data sets, along with widely agreed upon metrics to compare techniques, have catalyzed tremendous innovation and progress on other image classification problems, particularly in object recognition. Inspired by their success, we introduce a large publicly accessible data set of hematoxylin and eosin (H&E)-stained tissue images with more than 21000 painstakingly annotated nuclear boundaries, whose quality was validated by a medical doctor. Because our data set is taken from multiple hospitals and includes a diversity of nuclear appearances from several patients, disease states, and organs, techniques trained on it are likely to generalize well and work right out-of-the-box on other H&E-stained images. We also propose a new metric to evaluate nuclear segmentation results that penalizes object- and pixel-level errors in a unified manner, unlike previous metrics that penalize only one type of error. We also propose a segmentation technique based on deep learning that lays a special emphasis on identifying the nuclear boundaries, including those between the touching or overlapping nuclei, and works well on a diverse set of test images.

Unsupervised color image segmentation using a lattice algebra clustering technique

Science.gov (United States)

Urcid, Gonzalo; Ritter, Gerhard X.

2011-08-01

In this paper we introduce a lattice algebra clustering technique for segmenting digital images in the Red-Green- Blue (RGB) color space. The proposed technique is a two step procedure. Given an input color image, the first step determines the finite set of its extreme pixel vectors within the color cube by means of the scaled min-W and max-M lattice auto-associative memory matrices, including the minimum and maximum vector bounds. In the second step, maximal rectangular boxes enclosing each extreme color pixel are found using the Chebychev distance between color pixels; afterwards, clustering is performed by assigning each image pixel to its corresponding maximal box. The two steps in our proposed method are completely unsupervised or autonomous. Illustrative examples are provided to demonstrate the color segmentation results including a brief numerical comparison with two other non-maximal variations of the same clustering technique.

Whole-body bone segmentation from MRI for PET/MRI attenuation correction using shape-based averaging

DEFF Research Database (Denmark)

Arabi, Hossein; Zaidi, H.

2016-01-01

Purpose: The authors evaluate the performance of shape-based averaging (SBA) technique for whole-body bone segmentation from MRI in the context of MRI-guided attenuation correction (MRAC) in hybrid PET/MRI. To enhance the performance of the SBA scheme, the authors propose to combine it with stati......Purpose: The authors evaluate the performance of shape-based averaging (SBA) technique for whole-body bone segmentation from MRI in the context of MRI-guided attenuation correction (MRAC) in hybrid PET/MRI. To enhance the performance of the SBA scheme, the authors propose to combine...... it with statistical atlas fusion techniques. Moreover, a fast and efficient shape comparisonbased atlas selection scheme was developed and incorporated into the SBA method. Methods: Clinical studies consisting of PET/CT and MR images of 21 patients were used to assess the performance of the SBA method. In addition...... voting (MV) atlas fusion scheme was also evaluated as a conventional and commonly used method. MRI-guided attenuation maps were generated using the different segmentation methods. Thereafter, quantitative analysis of PET attenuation correction was performed using CT-based attenuation correction...

A Hybrid Approach for Improving Image Segmentation: Application to Phenotyping of Wheat Leaves.

Directory of Open Access Journals (Sweden)

Joshua Chopin

Full Text Available In this article we propose a novel tool that takes an initial segmented image and returns a more accurate segmentation that accurately captures sharp features such as leaf tips, twists and axils. Our algorithm utilizes basic a-priori information about the shape of plant leaves and local image orientations to fit active contour models to important plant features that have been missed during the initial segmentation. We compare the performance of our approach with three state-of-the-art segmentation techniques, using three error metrics. The results show that leaf tips are detected with roughly one half of the original error, segmentation accuracy is almost always improved and more than half of the leaf breakages are corrected.

Segmented and sectional orthodontic technique: Review and case report

Directory of Open Access Journals (Sweden)

Tarek El-Bialy

2013-01-01

Full Text Available Friction in orthodontics has been blamed for many orthodontic-related problems in the literature. Much research as well as research and development by numerous companies have attempted to minimize friction in orthodontics. The aim of the present study was to critically review friction in orthodontics and present frictionless mechanics as well as differentiate between segmented arch mechanics (frictionless technique as compared to sectional arch mechanics. Comparison of the two techniques will be presented and cases treated by either technique are presented and critically reviewed regarding treatment outcome and anchorage preservation/loss.

Hybride textuelle Strukturen und hybride textuelle Einheiten. Ein Beitrag zur Theorie der Wörterbuchform

Directory of Open Access Journals (Sweden)

Herbert Ernst Wiegand

2011-10-01

Full Text Available

ZUSAMMENFASSUNG: In diesem Beitrag wird die Bildung, Darstellung und Leistung von hybriden textuellen Strukturen, die akzessive Einträge aufweisen, am Beispiel von Wörterbuchartikeln behandelt sowie erklärt, welche Eigenschaften hybride textuelle Einheiten haben. Ein Wörterbuchartikel eines Printwörterbuchs weist immer dann neben einer hierarchischen reinen eine hierarchische hybride Textkonstituentenstruktur auf, wenn in ihm mindestens ein funktionaler Angabezusatz auftritt, z.B. ein oben oder unten erweiternder oder ein binnenerweiternder. Da funktionale Angabezusätze Textsegmente mit Angabefunktion aber ohne Textkonstituentenstatus sind, werden sie durch nichtfunktionale Segmentation ermittelt, so dass neben funktionalen auch nichtfunktionale Textsegmente gegeben sind, die dann bei der Strukturbildung in die Trägermengen eingehen, so dass die Trägermengen aller hybriden hierarchischen Strukturen elementenheterogen, während die Trägermengen aller hierarchischen reinen Strukturen elementenhomogen sind. In den Strukturgraphen für hierarchische hybride Artikelstrukturen sind dann die Knoten für diejenigen Textsegmente, die den Hybridstatus der Strukturen bewirken, entweder durch Pfeilkanten für die textarchitektonischen oberhalb/unterhalb-Relationen mit den Knoten für die Textkonstituenten verbunden, so dass die Strukturgraphen architektonisch angereichert sind, oder durch besonders markierte Kanten, die die Knoten für die nichtfunktionalen Textsegmente und die für die binnenerweiternden funktionalen Angabezusätze mit den Knoten für die Textkonstituenten verbinden. Zu jedem Typ von hierarchischer reiner Artikelstruktur gehören mehrere Typen von hybriden Artikelstrukturen; entsprechendes gilt für hierarchische reine Angabestrukturen. Nur eine Auswahl aus den Typologien der hybriden Artikel- und Angabestrukturen wird behandelt sowie eine kleine Auswahl von hybriden textuellen Einheiten, die kriteriale Eigenschaften von zwei

A novel hybrid surface micromachined segmented mirror for large aperture laser applications

Science.gov (United States)

Li, Jie; Chen, Haiqing; Yu, Hongbin

2006-07-01

A novel hybrid surface micromachined segmented mirror array is described. This device is capable of scaling to large apertures for correcting time-varying aberrations in laser applications. Each mirror is composed of bottom electrode, support part, and mirror plate, in which a T-shaped beam structure is used to support the mirror plate. It can provide mirror with vertical movement and rotation around two horizontal axes. The test results show that the maximum deflection along the vertical direction of the mirror plate is 2 microns, while the rotation angles around x and y axes are +-2.3 deg. and +-1.45 deg., respectively.

Segmentation Techniques for Expanding a Library Instruction Market: Evaluating and Brainstorming.

Science.gov (United States)

Warren, Rebecca; Hayes, Sherman; Gunter, Donna

2001-01-01

Describes a two-part segmentation technique applied to an instruction program for an academic library during a strategic planning process. Discusses a brainstorming technique used to create a list of existing and potential audiences, and then describes a follow-up review session that evaluated the past years' efforts. (Author/LRW)

A Segmental Approach with SWT Technique for Denoising the EOG Signal

Directory of Open Access Journals (Sweden)

Naga Rajesh

2015-01-01

Full Text Available The Electrooculogram (EOG signal is often contaminated with artifacts and power-line while recording. It is very much essential to denoise the EOG signal for quality diagnosis. The present study deals with denoising of noisy EOG signals using Stationary Wavelet Transformation (SWT technique by two different approaches, namely, increasing segments of the EOG signal and different equal segments of the EOG signal. For performing the segmental denoising analysis, an EOG signal is simulated and added with controlled noise powers of 5 dB, 10 dB, 15 dB, 20 dB, and 25 dB so as to obtain five different noisy EOG signals. The results obtained after denoising them are extremely encouraging. Root Mean Square Error (RMSE values between reference EOG signal and EOG signals with noise powers of 5 dB, 10 dB, and 15 dB are very less when compared with 20 dB and 25 dB noise powers. The findings suggest that the SWT technique can be used to denoise the noisy EOG signal with optimum noise powers ranging from 5 dB to 15 dB. This technique might be useful in quality diagnosis of various neurological or eye disorders.

An Innovative Technique to Assess Spontaneous Baroreflex Sensitivity with Short Data Segments: Multiple Trigonometric Regressive Spectral Analysis.

Science.gov (United States)

Li, Kai; Rüdiger, Heinz; Haase, Rocco; Ziemssen, Tjalf

2018-01-01

Objective: As the multiple trigonometric regressive spectral (MTRS) analysis is extraordinary in its ability to analyze short local data segments down to 12 s, we wanted to evaluate the impact of the data segment settings by applying the technique of MTRS analysis for baroreflex sensitivity (BRS) estimation using a standardized data pool. Methods: Spectral and baroreflex analyses were performed on the EuroBaVar dataset (42 recordings, including lying and standing positions). For this analysis, the technique of MTRS was used. We used different global and local data segment lengths, and chose the global data segments from different positions. Three global data segments of 1 and 2 min and three local data segments of 12, 20, and 30 s were used in MTRS analysis for BRS. Results: All the BRS-values calculated on the three global data segments were highly correlated, both in the supine and standing positions; the different global data segments provided similar BRS estimations. When using different local data segments, all the BRS-values were also highly correlated. However, in the supine position, using short local data segments of 12 s overestimated BRS compared with those using 20 and 30 s. In the standing position, the BRS estimations using different local data segments were comparable. There was no proportional bias for the comparisons between different BRS estimations. Conclusion: We demonstrate that BRS estimation by the MTRS technique is stable when using different global data segments, and MTRS is extraordinary in its ability to evaluate BRS in even short local data segments (20 and 30 s). Because of the non-stationary character of most biosignals, the MTRS technique would be preferable for BRS analysis especially in conditions when only short stationary data segments are available or when dynamic changes of BRS should be monitored.

Effect of hybrid iterative reconstruction technique on quantitative and qualitative image analysis at 256-slice prospective gating cardiac CT

International Nuclear Information System (INIS)

Utsunomiya, Daisuke; Weigold, W. Guy; Weissman, Gaby; Taylor, Allen J.

2012-01-01

To evaluate the effect of hybrid iterative reconstruction on qualitative and quantitative parameters at 256-slice cardiac CT. Prospective cardiac CT images from 20 patients were analysed. Paired image sets were created using 3 reconstructions, i.e. filtered back projection (FBP) and moderate- and high-level iterative reconstructions. Quantitative parameters including CT-attenuation, noise, and contrast-to-noise ratio (CNR) were determined in both proximal- and distal coronary segments. Image quality was graded on a 4-point scale. Coronary CT attenuation values were similar for FBP, moderate- and high-level iterative reconstruction at 293 ± 74-, 290 ± 75-, and 283 ± 78 Hounsfield units (HU), respectively. CNR was significantly higher with moderate- and high-level iterative reconstructions (10.9 ± 3.5 and 18.4 ± 6.2, respectively) than FBP (8.2 ± 2.5) as was the visual grading of proximal vessels. Visualisation of distal vessels was better with high-level iterative reconstruction than FBP. The mean number of assessable segments among 289 segments was 245, 260, and 267 for FBP, moderate- and high-level iterative reconstruction, respectively; the difference between FBP and high-level iterative reconstruction was significant. Interobserver agreement was significantly higher for moderate- and high-level iterative reconstruction than FBP. Cardiac CT using hybrid iterative reconstruction yields higher CNR and better image quality than FBP. circle Cardiac CT helps clinicians to assess patients with coronary artery disease circle Hybrid iterative reconstruction provides improved cardiac CT image quality circle Hybrid iterative reconstruction improves the number of assessable coronary segments circle Hybrid iterative reconstruction improves interobserver agreement on cardiac CT. (orig.)

Speaker segmentation and clustering

OpenAIRE

Kotti, M; Moschou, V; Kotropoulos, C

2008-01-01

07.08.13 KB. Ok to add the accepted version to Spiral, Elsevier says ok whlile mandate not enforced. This survey focuses on two challenging speech processing topics, namely: speaker segmentation and speaker clustering. Speaker segmentation aims at finding speaker change points in an audio stream, whereas speaker clustering aims at grouping speech segments based on speaker characteristics. Model-based, metric-based, and hybrid speaker segmentation algorithms are reviewed. Concerning speaker...

A hybrid perturbation-Galerkin technique for partial differential equations

Science.gov (United States)

Geer, James F.; Anderson, Carl M.

1990-01-01

A two-step hybrid perturbation-Galerkin technique for improving the usefulness of perturbation solutions to partial differential equations which contain a parameter is presented and discussed. In the first step of the method, the leading terms in the asymptotic expansion(s) of the solution about one or more values of the perturbation parameter are obtained using standard perturbation methods. In the second step, the perturbation functions obtained in the first step are used as trial functions in a Bubnov-Galerkin approximation. This semi-analytical, semi-numerical hybrid technique appears to overcome some of the drawbacks of the perturbation and Galerkin methods when they are applied by themselves, while combining some of the good features of each. The technique is illustrated first by a simple example. It is then applied to the problem of determining the flow of a slightly compressible fluid past a circular cylinder and to the problem of determining the shape of a free surface due to a sink above the surface. Solutions obtained by the hybrid method are compared with other approximate solutions, and its possible application to certain problems associated with domain decomposition is discussed.

Techniques of DNA hybridization detect small numbers of mycobacteria with no cross-hybridization with non-mycobacterial respiratory organisms

International Nuclear Information System (INIS)

Shoemaker, S.A.; Fisher, J.H.; Scoggin, C.H.

1985-01-01

The traditional methods used in identifying mycobacteria, such as acid-fast bacillus stains and culture, are often time-consuming, insensitive, and nonspecific. As part of an ongoing program to improve diagnosis and characterization of mycobacteria, the authors have found that deoxyribonucleic acid (DNA) hybridization techniques using isotopically labeled, single-stranded, total DNA can be used to detect as little as 10(-4) micrograms of Mycobacterium tuberculosis (MTb) DNA. This amount of DNA represents approximately 2 X 10(4) genomes. They have also shown the MTb DNA is sufficiently different from the DNA of non-mycobacterial microorganisms such that cross-hybridization with MTb DNA does not occur under the hybridization conditions employed. The authors speculate that DNA hybridization techniques may allow the rapid, sensitive, and specific identification of mycobacteria

New hybrid technique for impulsive noise suppression in OFDM systems

International Nuclear Information System (INIS)

Mirza, A.; Zeb, A.; Sheikh, S.A.

2017-01-01

In this paper, a new hybrid technique employing RS (Reed Solomon) coding and adaptive filter for impulsive noise suppression in OFDM (Orthogonal Frequency Division Multiplexing) systems is presented. Adaptive filter creates a more accurate estimate of the original OFDM signal after impulsive noise cancellation. The residual impulsive noise is further mitigated by RS decoder in the second stage of proposed technique. Three members of adaptive filters family i.e. NLMS (Normalized Least Mean Square) algorithm, RLS (Recursive Least Square) algorithm and Bhagyashri algorithm are tested with RS decoder in the proposed hybrid technique. Furthermore, the results in terms of steady state MSE (Mean Square Error) reduction, BER (Bit Error Rate) improvement and SNR (Signal to Noise Ratio) enhancement confirm the effectiveness of the proposed dual faceted technique when compared with the recently reported techniques in literature. (author)

Robust segmentation and retrieval of environmental sounds

Science.gov (United States)

Wichern, Gordon

The proliferation of mobile computing has provided much of the world with the ability to record any sound of interest, or possibly every sound heard in a lifetime. The technology to continuously record the auditory world has applications in surveillance, biological monitoring of non-human animal sounds, and urban planning. Unfortunately, the ability to record anything has led to an audio data deluge, where there are more recordings than time to listen. Thus, access to these archives depends on efficient techniques for segmentation (determining where sound events begin and end), indexing (storing sufficient information with each event to distinguish it from other events), and retrieval (searching for and finding desired events). While many such techniques have been developed for speech and music sounds, the environmental and natural sounds that compose the majority of our aural world are often overlooked. The process of analyzing audio signals typically begins with the process of acoustic feature extraction where a frame of raw audio (e.g., 50 milliseconds) is converted into a feature vector summarizing the audio content. In this dissertation, a dynamic Bayesian network (DBN) is used to monitor changes in acoustic features in order to determine the segmentation of continuously recorded audio signals. Experiments demonstrate effective segmentation performance on test sets of environmental sounds recorded in both indoor and outdoor environments. Once segmented, every sound event is indexed with a probabilistic model, summarizing the evolution of acoustic features over the course of the event. Indexed sound events are then retrieved from the database using different query modalities. Two important query types are sound queries (query-by-example) and semantic queries (query-by-text). By treating each sound event and semantic concept in the database as a node in an undirected graph, a hybrid (content/semantic) network structure is developed. This hybrid network can

Constrained Optimization Based on Hybrid Evolutionary Algorithm and Adaptive Constraint-Handling Technique

DEFF Research Database (Denmark)

Wang, Yong; Cai, Zixing; Zhou, Yuren

2009-01-01

A novel approach to deal with numerical and engineering constrained optimization problems, which incorporates a hybrid evolutionary algorithm and an adaptive constraint-handling technique, is presented in this paper. The hybrid evolutionary algorithm simultaneously uses simplex crossover and two...... mutation operators to generate the offspring population. Additionally, the adaptive constraint-handling technique consists of three main situations. In detail, at each situation, one constraint-handling mechanism is designed based on current population state. Experiments on 13 benchmark test functions...... and four well-known constrained design problems verify the effectiveness and efficiency of the proposed method. The experimental results show that integrating the hybrid evolutionary algorithm with the adaptive constraint-handling technique is beneficial, and the proposed method achieves competitive...

Using wavelet denoising and mathematical morphology in the segmentation technique applied to blood cells images.

Science.gov (United States)

Boix, Macarena; Cantó, Begoña

2013-04-01

Accurate image segmentation is used in medical diagnosis since this technique is a noninvasive pre-processing step for biomedical treatment. In this work we present an efficient segmentation method for medical image analysis. In particular, with this method blood cells can be segmented. For that, we combine the wavelet transform with morphological operations. Moreover, the wavelet thresholding technique is used to eliminate the noise and prepare the image for suitable segmentation. In wavelet denoising we determine the best wavelet that shows a segmentation with the largest area in the cell. We study different wavelet families and we conclude that the wavelet db1 is the best and it can serve for posterior works on blood pathologies. The proposed method generates goods results when it is applied on several images. Finally, the proposed algorithm made in MatLab environment is verified for a selected blood cells.

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

Science.gov (United States)

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

2013-09-01

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

Hybrid chemical and nondestructive-analysis technique

International Nuclear Information System (INIS)

Hsue, S.T.; Marsh, S.F.; Marks, T.

1982-01-01

A hybrid chemical/NDA technique has been applied at the Los Alamos National Laboratory to the assay of plutonium in ion-exchange effluents. Typical effluent solutions contain low concentrations of plutonium and high concentrations of americium. A simple trioctylphosphine oxide (TOPO) separation can remove 99.9% of the americium. The organic phase that contains the separated plutonium can be accurately assayed by monitoring the uranium L x-ray intensities

Hybrid Technique of Lamellar Keratoplasty (DMEK-S

Directory of Open Access Journals (Sweden)

Pavel Studeny

2013-01-01

Full Text Available Purpose: To evaluate the outcomes of the hybrid technique of posterior lamellar keratoplasty (DMEK-S. Materials and Methods: 71 eyes of 55 patients enrolled in a single-center study underwent posterior lamellar keratoplasty with a hybrid lamella DMEK-S implanted using a solution implantation technique, owing to endothelial dysfunction. The outcome measures studied were visual acuity and endothelial cell density. Results: The rate of endothelial cell loss caused by surgery was 43.8%. During followups, we observed the stabilization of postoperative findings, or at minimum a very low rate of corneal endothelial cell loss. The UCDVA and BCDVA dramatically improved postoperatively. The rebubbling rate in our group of patients was 61.9%. We replaced the lamella due to its failure or malfunction in 17 patients (23.9%. Conclusion: In summary, DMEK-S combines the advantages of DSEK/DSAEK and DMEK. The central zone of bare Descemet’s membrane and endothelium allows for very good visual outcomes, and the peripheral rim allows for better manipulation of the lamella during implantation. It is an effective method of treating the endothelial dysfunction of various etiologies, but the high complication rate needs to be addressed before widespread implementation of the technique in the future.

High performance technique for database applicationsusing a hybrid GPU/CPU platform

KAUST Repository

Zidan, Mohammed A.

2012-07-28

Many database applications, such as sequence comparing, sequence searching, and sequence matching, etc, process large database sequences. we introduce a novel and efficient technique to improve the performance of database applica- tions by using a Hybrid GPU/CPU platform. In particular, our technique solves the problem of the low efficiency result- ing from running short-length sequences in a database on a GPU. To verify our technique, we applied it to the widely used Smith-Waterman algorithm. The experimental results show that our Hybrid GPU/CPU technique improves the average performance by a factor of 2.2, and improves the peak performance by a factor of 2.8 when compared to earlier implementations. Copyright © 2011 by ASME.

Highly segmented large-area hybrid photodiodes with bialkali photocathodes and enclosed VLSI readout electronics

CERN Document Server

Braem, André; Filthaut, Frank; Go, A; Joram, C; Weilhammer, Peter; Wicht, P; Dulinski, W; Séguinot, Jacques; Wenzel, H; Ypsilantis, Thomas

2000-01-01

We report on the principles, design, fabrication, and operation of a highly segmented, large-area hybrid photodiode, which is being developed in the framework of the LHCb RICH project. The device consists of a cylindrical, 127 mm diameter vacuum envelope capped with a spherical borosilicate UV-glass entrance window, with an active-to-total-area fraction of 81A fountain-focusing electron optics is used to demagnify the image onto a 50 mm diameter silicon sensor, containing 2048 pads of size 1*1 mm/sup 2/. (10 refs).

Hybride textuelle Strukturen und hybride textuelle Einheiten. Ein ...

African Journals Online (AJOL)

carrying set of all hybrid hierarchical structures are element-heterogeneous whilst the structure- carrying set of all ... grams of hierarchical hybrid article structures, the nodes for those text segments that establish the hybrid status of .... der; d ∈ ArtA ⊣ G|WAr (= Artikelangabe, anhand derer das Genus (= G) und zugleich die ...

A segmented Hybrid Photon Detector with integrated auto-triggering front-end electronics for a PET scanner

CERN Document Server

Chesi, Enrico Guido; Joram, C; Mathot, S; Séguinot, Jacques; Weilhammer, P; Ciocia, F; De Leo, R; Nappi, E; Vilardi, I; Argentieri, A; Corsi, F; Dragone, A; Pasqua, D

2006-01-01

We describe the design, fabrication and test results of a segmented Hybrid Photon Detector with integrated auto-triggering front-end electronics. Both the photodetector and its VLSI readout electronics are custom designed and have been tailored to the requirements of a recently proposed novel geometrical concept of a Positron Emission Tomograph. Emphasis is put on the PET specific features of the device. The detector has been fabricated in the photocathode facility at CERN.

Segmentation of knee injury swelling on infrared images

Science.gov (United States)

Puentes, John; Langet, Hélène; Herry, Christophe; Frize, Monique

2011-03-01

Interpretation of medical infrared images is complex due to thermal noise, absence of texture, and small temperature differences in pathological zones. Acute inflammatory response is a characteristic symptom of some knee injuries like anterior cruciate ligament sprains, muscle or tendons strains, and meniscus tear. Whereas artificial coloring of the original grey level images may allow to visually assess the extent inflammation in the area, their automated segmentation remains a challenging problem. This paper presents a hybrid segmentation algorithm to evaluate the extent of inflammation after knee injury, in terms of temperature variations and surface shape. It is based on the intersection of rapid color segmentation and homogeneous region segmentation, to which a Laplacian of a Gaussian filter is applied. While rapid color segmentation enables to properly detect the observed core of swollen area, homogeneous region segmentation identifies possible inflammation zones, combining homogeneous grey level and hue area segmentation. The hybrid segmentation algorithm compares the potential inflammation regions partially detected by each method to identify overlapping areas. Noise filtering and edge segmentation are then applied to common zones in order to segment the swelling surfaces of the injury. Experimental results on images of a patient with anterior cruciate ligament sprain show the improved performance of the hybrid algorithm with respect to its separated components. The main contribution of this work is a meaningful automatic segmentation of abnormal skin temperature variations on infrared thermography images of knee injury swelling.

Segmentation of Brain Lesions in MRI and CT Scan Images: A Hybrid Approach Using k-Means Clustering and Image Morphology

Science.gov (United States)

Agrawal, Ritu; Sharma, Manisha; Singh, Bikesh Kumar

2018-04-01

Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.

SU-E-T-16: A Hybrid VMAT/IMRT Technique for the Treatment of Nasopharyngeal Carcinoma

International Nuclear Information System (INIS)

Zhao, N; Yang, R; Wang, J

2014-01-01

Purpose: To investigate a Hybrid VMAT/IMRT technique which combines volumetric modulated arc therapy (VMAT) and intensity modulated radiation therapy (IMRT) for nasopharyngeal carcinoma (NPC). Methods: 2 full arcs VMAT, 9-field IMRT and Hybrid VMAT/IMRT plans were created for 10 patients with NPC. The Hybrid VMAT/IMRT technique consisted of 1 full VMAT arc and 7 IMRT fields. The dose distribution of planning target volume (PTV) and organs at risk (OARs) for Hybrid VMAT/IMRT was compared with IMRT and VMAT. The monitor units (MUs) were also evaluated. Results: The Hybrid VMAT/IMRT technique significantly improved target dose homogeneity compared with IMRT and VMAT for PTV70 and PTV54. For PTV70 and PTV60, the Hybrid VMAT/IMRT technique significantly improved target dose conformity compared with IMRT (0.62 vs 0.47; p<0.05 and 0.64 vs 0.58; p<0.05, respectively) and VMAT (0.62 vs 0.43; p<0.05 and 0.64 vs 0.6; p<0.05, respectively). The near maximum dose (D2%) of temporomandibular joint (TMJ), temporal lobe and mandible for Hybrid plans were 5.5%, 7.9% and 5.2% lower than IMRT plans (p<0.05). The mean dose of TMJ, temporal lobe, mandible and unspecified tissue for Hybrid plans were 12.8%, 11.4%, 4.2% and 4.1% lower than IMRT plans (p<0.05). The mean dose of right parotid, mandible and unspecified tissue for Hybrid plans were 3.3%, 2.4% and 3.1% lower than VMAT plans (p<0.05). The mean MUs needed for IMRT, VMAT and Hybrid plans were 2256, 507 and 1394, respectively. Conclusion: Hybrid VMAT/IMRT technique significantly improved the target dose homogeneity and conformity compared with IMRT and VMAT and reduced the dose of OARs and unspecified tissue compared with IMRT with fewer MUs. Compared with VMAT, Hybrid VMAT/IMRT technique can better protect parotid gland, mandible and unspecified tissue. Ruijie Yang was funded by the grant project: National Natural Science Foundation of China (No. 81071237). Other authors have no competing interest for this work

SU-E-T-16: A Hybrid VMAT/IMRT Technique for the Treatment of Nasopharyngeal Carcinoma

Energy Technology Data Exchange (ETDEWEB)

Zhao, N; Yang, R; Wang, J [Peking University Third Hospital, Beijing, Beijing (China)

2014-06-01

Purpose: To investigate a Hybrid VMAT/IMRT technique which combines volumetric modulated arc therapy (VMAT) and intensity modulated radiation therapy (IMRT) for nasopharyngeal carcinoma (NPC). Methods: 2 full arcs VMAT, 9-field IMRT and Hybrid VMAT/IMRT plans were created for 10 patients with NPC. The Hybrid VMAT/IMRT technique consisted of 1 full VMAT arc and 7 IMRT fields. The dose distribution of planning target volume (PTV) and organs at risk (OARs) for Hybrid VMAT/IMRT was compared with IMRT and VMAT. The monitor units (MUs) were also evaluated. Results: The Hybrid VMAT/IMRT technique significantly improved target dose homogeneity compared with IMRT and VMAT for PTV70 and PTV54. For PTV70 and PTV60, the Hybrid VMAT/IMRT technique significantly improved target dose conformity compared with IMRT (0.62 vs 0.47; p<0.05 and 0.64 vs 0.58; p<0.05, respectively) and VMAT (0.62 vs 0.43; p<0.05 and 0.64 vs 0.6; p<0.05, respectively). The near maximum dose (D2%) of temporomandibular joint (TMJ), temporal lobe and mandible for Hybrid plans were 5.5%, 7.9% and 5.2% lower than IMRT plans (p<0.05). The mean dose of TMJ, temporal lobe, mandible and unspecified tissue for Hybrid plans were 12.8%, 11.4%, 4.2% and 4.1% lower than IMRT plans (p<0.05). The mean dose of right parotid, mandible and unspecified tissue for Hybrid plans were 3.3%, 2.4% and 3.1% lower than VMAT plans (p<0.05). The mean MUs needed for IMRT, VMAT and Hybrid plans were 2256, 507 and 1394, respectively. Conclusion: Hybrid VMAT/IMRT technique significantly improved the target dose homogeneity and conformity compared with IMRT and VMAT and reduced the dose of OARs and unspecified tissue compared with IMRT with fewer MUs. Compared with VMAT, Hybrid VMAT/IMRT technique can better protect parotid gland, mandible and unspecified tissue. Ruijie Yang was funded by the grant project: National Natural Science Foundation of China (No. 81071237). Other authors have no competing interest for this work.

Color image Segmentation using automatic thresholding techniques

International Nuclear Information System (INIS)

Harrabi, R.; Ben Braiek, E.

2011-01-01

In this paper, entropy and between-class variance based thresholding methods for color images segmentation are studied. The maximization of the between-class variance (MVI) and the entropy (ME) have been used as a criterion functions to determine an optimal threshold to segment images into nearly homogenous regions. Segmentation results from the two methods are validated and the segmentation sensitivity for the test data available is evaluated, and a comparative study between these methods in different color spaces is presented. The experimental results demonstrate the superiority of the MVI method for color image segmentation.

Contrast-Enhanced MR Angiography (CEMRA) in Peripheral Arterial Occlusive Disease (PAOD): conventional moving table technique versus hybrid technique; Kontrastverstaerkte MR-Angiographie (CEMRA) bei peripherer AVK (pAVK): konventionelle Tischverschiebetechnik versus Hybrid-Technik

Energy Technology Data Exchange (ETDEWEB)

Kalle, T. von; Gerlach, A.; Hatopp, A.; Klinger, S.; Prodehl, P.; Arlat, I.P. [Katharinenhospital, Stuttgart (Germany). Radiologisches Inst.

2004-01-01

Patients and Methods: 80 patients (males n = 60, females n = 20, median age = 70 years, diabetics n = 27) with PAOD were examined with a 1,5T system (40 mT/m) using a dedicated phased array peripheral vascular coil. Protocol A consisted of a single injection of Gd-BOPTA with consecutive craniocaudal image acquisition and protocol B of two injections, with the first injection of Gd-BOPTA followed by image acquisition of the popliteocrural and pedal segments and the second injection followed by acquiring the aortoiliac and femoral segments (hybrid technique). The evaluation of the arterial system was directed to the iliac, femoral, popliteocrural and pedal arteries. Results: The visualization of the entire aortopedal vascular system was of diagnostically good or satisfactory quality in 16 of 40 patients using protocol A and in 29 of 40 patients using protocol B (iliac 40 vs. 37, femoral 40 vs. 40, popliteocrural 35 vs. 37, pedal 16 vs. 29); without the pedal station the number increased to 35 of 40 patients for both protocols. The reason of diagnostic limitations was an arteriovenous overlap in 24 of 80 cases, with 19 of 40 cases for protocol A and 5 of 40 for protocol B, located exclusively in the cruropedal region. Conclusion: Moving table hybrid CEMRA is superior to conventional technique in craniocaudal direction by producing less venous overlap of arteries and is especially more suitable for the diagnostic evaluation of the cruropedal region. (orig.) [German] Patienten und Methodik: Untersucht wurden 80 Patienten (maennl. n = 60, weibl. n = 20, mittl. Alter 70 J., Diabetiker n = 27) mit pAVK an einem 1,5-Tesla-Geraet (40 mT/m) mit dedizierter Phased-Array-Oberflaechen-Gefaessspule. Protokoll A beinhaltete eine Kontrastmittel-Injektion (Gd-BOPTA) mit konsekutiver kraniokaudaler Bildakquisition. In Protokoll B erfolgte die Akquisition zunaechst der Unterschenkel- und Fussetage mittels einer ersten, anschliessend der Abdomen-Becken- und Oberschenkeletage mittels

A hybrid method for airway segmentation and automated measurement of bronchial wall thickness on CT.

Science.gov (United States)

Xu, Ziyue; Bagci, Ulas; Foster, Brent; Mansoor, Awais; Udupa, Jayaram K; Mollura, Daniel J

2015-08-01

Inflammatory and infectious lung diseases commonly involve bronchial airway structures and morphology, and these abnormalities are often analyzed non-invasively through high resolution computed tomography (CT) scans. Assessing airway wall surfaces and the lumen are of great importance for diagnosing pulmonary diseases. However, obtaining high accuracy from a complete 3-D airway tree structure can be quite challenging. The airway tree structure has spiculated shapes with multiple branches and bifurcation points as opposed to solid single organ or tumor segmentation tasks in other applications, hence, it is complex for manual segmentation as compared with other tasks. For computerized methods, a fundamental challenge in airway tree segmentation is the highly variable intensity levels in the lumen area, which often causes a segmentation method to leak into adjacent lung parenchyma through blurred airway walls or soft boundaries. Moreover, outer wall definition can be difficult due to similar intensities of the airway walls and nearby structures such as vessels. In this paper, we propose a computational framework to accurately quantify airways through (i) a novel hybrid approach for precise segmentation of the lumen, and (ii) two novel methods (a spatially constrained Markov random walk method (pseudo 3-D) and a relative fuzzy connectedness method (3-D)) to estimate the airway wall thickness. We evaluate the performance of our proposed methods in comparison with mostly used algorithms using human chest CT images. Our results demonstrate that, on publicly available data sets and using standard evaluation criteria, the proposed airway segmentation method is accurate and efficient as compared with the state-of-the-art methods, and the airway wall estimation algorithms identified the inner and outer airway surfaces more accurately than the most widely applied methods, namely full width at half maximum and phase congruency. Copyright © 2015. Published by Elsevier B.V.

Triplex in-situ hybridization

Science.gov (United States)

Fresco, Jacques R.; Johnson, Marion D.

2002-01-01

Disclosed are methods for detecting in situ the presence of a target sequence in a substantially double-stranded nucleic acid segment, which comprises: a) contacting in situ under conditions suitable for hybridization a substantially double-stranded nucleic acid segment with a detectable third strand, said third strand being capable of hybridizing to at least a portion of the target sequence to form a triple-stranded structure, if said target sequence is present; and b) detecting whether hybridization between the third strand and the target sequence has occured.

PEAK-TO-AVERAGE POWER RATIO REDUCTION USING CODING AND HYBRID TECHNIQUES FOR OFDM SYSTEM

OpenAIRE

Bahubali K. Shiragapur; Uday Wali

2016-01-01

In this article, the research work investigated is based on an error correction coding techniques are used to reduce the undesirable Peak-to-Average Power Ratio (PAPR) quantity. The Golay Code (24, 12), Reed-Muller code (16, 11), Hamming code (7, 4) and Hybrid technique (Combination of Signal Scrambling and Signal Distortion) proposed by us are used as proposed coding techniques, the simulation results shows that performance of Hybrid technique, reduces PAPR significantly as compared to Conve...

STUDY OF IMAGE SEGMENTATION TECHNIQUES ON RETINAL IMAGES FOR HEALTH CARE MANAGEMENT WITH FAST COMPUTING

Directory of Open Access Journals (Sweden)

Srikanth Prabhu

2012-02-01

Full Text Available The role of segmentation in image processing is to separate foreground from background. In this process, the features become clearly visible when appropriate filters are applied on the image. In this paper emphasis has been laid on segmentation of biometric retinal images to filter out the vessels explicitly for evaluating the bifurcation points and features for diabetic retinopathy. Segmentation on images is performed by calculating ridges or morphology. Ridges are those areas in the images where there is sharp contrast in features. Morphology targets the features using structuring elements. Structuring elements are of different shapes like disk, line which is used for extracting features of those shapes. When segmentation was performed on retinal images problems were encountered during image pre-processing stage. Also edge detection techniques have been deployed to find out the contours of the retinal images. After the segmentation has been performed, it has been seen that artifacts of the retinal images have been minimal when ridge based segmentation technique was deployed. In the field of Health Care Management, image segmentation has an important role to play as it determines whether a person is normal or having any disease specially diabetes. During the process of segmentation, diseased features are classified as diseased one’s or artifacts. The problem comes when artifacts are classified as diseased ones. This results in misclassification which has been discussed in the analysis Section. We have achieved fast computing with better performance, in terms of speed for non-repeating features, when compared to repeating features.

Parallel and Efficient Sensitivity Analysis of Microscopy Image Segmentation Workflows in Hybrid Systems.

Science.gov (United States)

Barreiros, Willian; Teodoro, George; Kurc, Tahsin; Kong, Jun; Melo, Alba C M A; Saltz, Joel

2017-09-01

We investigate efficient sensitivity analysis (SA) of algorithms that segment and classify image features in a large dataset of high-resolution images. Algorithm SA is the process of evaluating variations of methods and parameter values to quantify differences in the output. A SA can be very compute demanding because it requires re-processing the input dataset several times with different parameters to assess variations in output. In this work, we introduce strategies to efficiently speed up SA via runtime optimizations targeting distributed hybrid systems and reuse of computations from runs with different parameters. We evaluate our approach using a cancer image analysis workflow on a hybrid cluster with 256 nodes, each with an Intel Phi and a dual socket CPU. The SA attained a parallel efficiency of over 90% on 256 nodes. The cooperative execution using the CPUs and the Phi available in each node with smart task assignment strategies resulted in an additional speedup of about 2×. Finally, multi-level computation reuse lead to an additional speedup of up to 2.46× on the parallel version. The level of performance attained with the proposed optimizations will allow the use of SA in large-scale studies.

A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

Science.gov (United States)

Kobayashi, Takahisa; Simon, Donald L.

2001-01-01

In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

High performance technique for database applicationsusing a hybrid GPU/CPU platform

KAUST Repository

Zidan, Mohammed A.; Bonny, Talal; Salama, Khaled N.

2012-01-01

Hybrid GPU/CPU platform. In particular, our technique solves the problem of the low efficiency result- ing from running short-length sequences in a database on a GPU. To verify our technique, we applied it to the widely used Smith-Waterman algorithm

Superpixel-based segmentation of glottal area from videolaryngoscopy images

Science.gov (United States)

Turkmen, H. Irem; Albayrak, Abdulkadir; Karsligil, M. Elif; Kocak, Ismail

2017-11-01

Segmentation of the glottal area with high accuracy is one of the major challenges for the development of systems for computer-aided diagnosis of vocal-fold disorders. We propose a hybrid model combining conventional methods with a superpixel-based segmentation approach. We first employed a superpixel algorithm to reveal the glottal area by eliminating the local variances of pixels caused by bleedings, blood vessels, and light reflections from mucosa. Then, the glottal area was detected by exploiting a seeded region-growing algorithm in a fully automatic manner. The experiments were conducted on videolaryngoscopy images obtained from both patients having pathologic vocal folds as well as healthy subjects. Finally, the proposed hybrid approach was compared with conventional region-growing and active-contour model-based glottal area segmentation algorithms. The performance of the proposed method was evaluated in terms of segmentation accuracy and elapsed time. The F-measure, true negative rate, and dice coefficients of the hybrid method were calculated as 82%, 93%, and 82%, respectively, which are superior to the state-of-art glottal-area segmentation methods. The proposed hybrid model achieved high success rates and robustness, making it suitable for developing a computer-aided diagnosis system that can be used in clinical routines.

Prosthetic component segmentation with blur compensation: a fast method for 3D fluoroscopy.

Science.gov (United States)

Tarroni, Giacomo; Tersi, Luca; Corsi, Cristiana; Stagni, Rita

2012-06-01

A new method for prosthetic component segmentation from fluoroscopic images is presented. The hybrid approach we propose combines diffusion filtering, region growing and level-set techniques without exploiting any a priori knowledge of the analyzed geometry. The method was evaluated on a synthetic dataset including 270 images of knee and hip prosthesis merged to real fluoroscopic data simulating different conditions of blurring and illumination gradient. The performance of the method was assessed by comparing estimated contours to references using different metrics. Results showed that the segmentation procedure is fast, accurate, independent on the operator as well as on the specific geometrical characteristics of the prosthetic component, and able to compensate for amount of blurring and illumination gradient. Importantly, the method allows a strong reduction of required user interaction time when compared to traditional segmentation techniques. Its effectiveness and robustness in different image conditions, together with simplicity and fast implementation, make this prosthetic component segmentation procedure promising and suitable for multiple clinical applications including assessment of in vivo joint kinematics in a variety of cases.

A hybrid segmentation approach for geographic atrophy in fundus auto-fluorescence images for diagnosis of age-related macular degeneration.

Science.gov (United States)

Lee, Noah; Laine, Andrew F; Smith, R Theodore

2007-01-01

Fundus auto-fluorescence (FAF) images with hypo-fluorescence indicate geographic atrophy (GA) of the retinal pigment epithelium (RPE) in age-related macular degeneration (AMD). Manual quantification of GA is time consuming and prone to inter- and intra-observer variability. Automatic quantification is important for determining disease progression and facilitating clinical diagnosis of AMD. In this paper we describe a hybrid segmentation method for GA quantification by identifying hypo-fluorescent GA regions from other interfering retinal vessel structures. First, we employ background illumination correction exploiting a non-linear adaptive smoothing operator. Then, we use the level set framework to perform segmentation of hypo-fluorescent areas. Finally, we present an energy function combining morphological scale-space analysis with a geometric model-based approach to perform segmentation refinement of false positive hypo- fluorescent areas due to interfering retinal structures. The clinically apparent areas of hypo-fluorescence were drawn by an expert grader and compared on a pixel by pixel basis to our segmentation results. The mean sensitivity and specificity of the ROC analysis were 0.89 and 0.98%.

A Hybrid Hierarchical Approach for Brain Tissue Segmentation by Combining Brain Atlas and Least Square Support Vector Machine

Science.gov (United States)

Kasiri, Keyvan; Kazemi, Kamran; Dehghani, Mohammad Javad; Helfroush, Mohammad Sadegh

2013-01-01

In this paper, we present a new semi-automatic brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (LS-SVM). The method consists of three steps. In the first two steps, the skull is removed and the cerebrospinal fluid (CSF) is extracted. These two steps are performed using the toolbox FMRIB's automated segmentation tool integrated in the FSL software (FSL-FAST) developed in Oxford Centre for functional MRI of the brain (FMRIB). Then, in the third step, the LS-SVM is used to segment grey matter (GM) and white matter (WM). The training samples for LS-SVM are selected from the registered brain atlas. The voxel intensities and spatial positions are selected as the two feature groups for training and test. SVM as a powerful discriminator is able to handle nonlinear classification problems; however, it cannot provide posterior probability. Thus, we use a sigmoid function to map the SVM output into probabilities. The proposed method is used to segment CSF, GM and WM from the simulated magnetic resonance imaging (MRI) using Brainweb MRI simulator and real data provided by Internet Brain Segmentation Repository. The semi-automatically segmented brain tissues were evaluated by comparing to the corresponding ground truth. The Dice and Jaccard similarity coefficients, sensitivity and specificity were calculated for the quantitative validation of the results. The quantitative results show that the proposed method segments brain tissues accurately with respect to corresponding ground truth. PMID:24696800

Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

Energy Technology Data Exchange (ETDEWEB)

Gan, Yangzhou; Zhao, Qunfei [Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240 (China); Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn; Hu, Ying [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and The Chinese University of Hong Kong, Shenzhen 518055 (China); Xiong, Jing, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 510855 (China); Zhang, Jianwei [TAMS, Department of Informatics, University of Hamburg, Hamburg 22527 (Germany)

2015-01-15

Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0

Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

International Nuclear Information System (INIS)

Gan, Yangzhou; Zhao, Qunfei; Xia, Zeyang; Hu, Ying; Xiong, Jing; Zhang, Jianwei

2015-01-01

Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm 3 ) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm 3 , 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm 3 , 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0.28 ± 0.03 mm

Simultaneous tomographic reconstruction and segmentation with class priors

DEFF Research Database (Denmark)

Romanov, Mikhail; Dahl, Anders Bjorholm; Dong, Yiqiu

2015-01-01

are combined to produce a reconstruction that is identical to the segmentation. We consider instead a hybrid approach that simultaneously produces both a reconstructed image and segmentation. We incorporate priors about the desired classes of the segmentation through a Hidden Markov Measure Field Model, and we...

A new user-assisted segmentation and tracking technique for an object-based video editing system

Science.gov (United States)

Yu, Hong Y.; Hong, Sung-Hoon; Lee, Mike M.; Choi, Jae-Gark

2004-03-01

This paper presents a semi-automatic segmentation method which can be used to generate video object plane (VOP) for object based coding scheme and multimedia authoring environment. Semi-automatic segmentation can be considered as a user-assisted segmentation technique. A user can initially mark objects of interest around the object boundaries and then the user-guided and selected objects are continuously separated from the unselected areas through time evolution in the image sequences. The proposed segmentation method consists of two processing steps: partially manual intra-frame segmentation and fully automatic inter-frame segmentation. The intra-frame segmentation incorporates user-assistance to define the meaningful complete visual object of interest to be segmentation and decides precise object boundary. The inter-frame segmentation involves boundary and region tracking to obtain temporal coherence of moving object based on the object boundary information of previous frame. The proposed method shows stable efficient results that could be suitable for many digital video applications such as multimedia contents authoring, content based coding and indexing. Based on these results, we have developed objects based video editing system with several convenient editing functions.

Detection of plant leaf diseases using image segmentation and soft computing techniques

Directory of Open Access Journals (Sweden)

Vijai Singh

2017-03-01

Full Text Available Agricultural productivity is something on which economy highly depends. This is the one of the reasons that disease detection in plants plays an important role in agriculture field, as having disease in plants are quite natural. If proper care is not taken in this area then it causes serious effects on plants and due to which respective product quality, quantity or productivity is affected. For instance a disease named little leaf disease is a hazardous disease found in pine trees in United States. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself it detects the symptoms of diseases i.e. when they appear on plant leaves. This paper presents an algorithm for image segmentation technique which is used for automatic detection and classification of plant leaf diseases. It also covers survey on different diseases classification techniques that can be used for plant leaf disease detection. Image segmentation, which is an important aspect for disease detection in plant leaf disease, is done by using genetic algorithm.

An Overview of Techniques for Cardiac Left Ventricle Segmentation on Short-Axis MRI

Directory of Open Access Journals (Sweden)

Krasnobaev Arseny

2016-01-01

Full Text Available Nowadays, heart diseases are the leading cause of death. Left ventricle segmentation of a human heart in magnetic resonance images (MRI is a crucial step in both cardiac diseases diagnostics and heart internal structure reconstruction. It allows estimating such important parameters as ejection faction, left ventricle myocardium mass, stroke volume, etc. In addition, left ventricle segmentation helps to construct the personalized heart computational models in order to conduct the numerical simulations. At present, the fully automated cardiac segmentation methods still do not meet the accuracy requirements. We present an overview of left ventricle segmentation algorithms on short-axis MRI. A wide variety of completely different approaches are used for cardiac segmentation, including machine learning, graph-based methods, deformable models, and low-level heuristics. The current state-of-the-art technique is a combination of deformable models with advanced machine learning methods, such as deep learning or Markov random fields. We expect that approaches based on deep belief networks are the most promising ones because the main training process of networks with this architecture can be performed on the unlabelled data. In order to improve the quality of left ventricle segmentation algorithms, we need more datasets with labelled cardiac MRI data in open access.

Recent Results with a segmented Hybrid Photon Detector for a novel parallax-free PET Scanner for Brain Imaging

CERN Document Server

Braem, André; Joram, Christian; Mathot, Serge; Séguinot, Jacques; Weilhammer, Peter; Ciocia, F; De Leo, R; Nappi, E; Vilardi, I; Argentieri, A; Corsi, F; Dragone, A; Pasqua, D

2007-01-01

We describe the design, fabrication and test results of a segmented Hybrid Photon Detector with integrated auto-triggering front-end electronics. Both the photodetector and its VLSI readout electronics are custom designed and have been tailored to the requirements of a recently proposed novel geometrical concept of a Positron Emission Tomograph. Emphasis is laid on the PET specific features of the device. The detector has been fabricated in the photocathode facility at CERN.

Multi-technique hybrid imaging in PET/CT and PET/MR: what does the future hold?

International Nuclear Information System (INIS)

Galiza Barbosa, F. de; Delso, G.; Voert, E.E.G.W. ter; Huellner, M.W.; Herrmann, K.; Veit-Haibach, P.

2016-01-01

Integrated positron-emission tomography and computed tomography (PET/CT) is one of the most important imaging techniques to have emerged in oncological practice in the last decade. Hybrid imaging, in general, remains a rapidly growing field, not only in developing countries, but also in western industrialised healthcare systems. A great deal of technological development and research is focused on improving hybrid imaging technology further and introducing new techniques, e.g., integrated PET and magnetic resonance imaging (PET/MRI). Additionally, there are several new PET tracers on the horizon, which have the potential to broaden clinical applications in hybrid imaging for diagnosis as well as therapy. This article aims to highlight some of the major technical and clinical advances that are currently taking place in PET/CT and PET/MRI that will potentially maintain the position of hybrid techniques at the forefront of medical imaging technologies.

Novel Damage Detection Techniques for Structural Health Monitoring Using a Hybrid Sensor

Directory of Open Access Journals (Sweden)

Dengjiang Wang

2016-01-01

Full Text Available This study presents a technique for detecting fatigue cracks based on a hybrid sensor monitoring system consisting of a combination of intelligent coating monitoring (ICM and piezoelectric transducer (PZT sensors. An experimental procedure using this hybrid sensor system was designed to monitor the cracks generated by fatigue testing in plate structures. A probability of detection (POD model that quantifies the reliability of damage detection for a specific sensor or the nondestructive testing (NDT method was used to evaluate the weight factor for the ICM and PZT sensors. To estimate the uncertainty of model parameters in this study, the Bayesian method was employed. Realistic data from fatigue testing was used to validate the overall method, and the results show that the novel damage detection technique using a hybrid sensor can quantify fatigue cracks more accurately than results obtained by conventional sensor methods.

Lesion Detection in CT Images Using Deep Learning Semantic Segmentation Technique

Science.gov (United States)

Kalinovsky, A.; Liauchuk, V.; Tarasau, A.

2017-05-01

In this paper, the problem of automatic detection of tuberculosis lesion on 3D lung CT images is considered as a benchmark for testing out algorithms based on a modern concept of Deep Learning. For training and testing of the algorithms a domestic dataset of 338 3D CT scans of tuberculosis patients with manually labelled lesions was used. The algorithms which are based on using Deep Convolutional Networks were implemented and applied in three different ways including slice-wise lesion detection in 2D images using semantic segmentation, slice-wise lesion detection in 2D images using sliding window technique as well as straightforward detection of lesions via semantic segmentation in whole 3D CT scans. The algorithms demonstrate superior performance compared to algorithms based on conventional image analysis methods.

Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization

International Nuclear Information System (INIS)

Mohaghegh, Zahra; Kazemi, Reza; Mosleh, Ali

2009-01-01

This paper is a result of a research with the primary purpose of extending Probabilistic Risk Assessment (PRA) modeling frameworks to include the effects of organizational factors as the deeper, more fundamental causes of accidents and incidents. There have been significant improvements in the sophistication of quantitative methods of safety and risk assessment, but the progress on techniques most suitable for organizational safety risk frameworks has been limited. The focus of this paper is on the choice of 'representational schemes' and 'techniques.' A methodology for selecting appropriate candidate techniques and their integration in the form of a 'hybrid' approach is proposed. Then an example is given through an integration of System Dynamics (SD), Bayesian Belief Network (BBN), Event Sequence Diagram (ESD), and Fault Tree (FT) in order to demonstrate the feasibility and value of hybrid techniques. The proposed hybrid approach integrates deterministic and probabilistic modeling perspectives, and provides a flexible risk management tool for complex socio-technical systems. An application of the hybrid technique is provided in the aviation safety domain, focusing on airline maintenance systems. The example demonstrates how the hybrid method can be used to analyze the dynamic effects of organizational factors on system risk

Advantages of the technique with segmented fields for tangential breast irradiation

International Nuclear Information System (INIS)

Stefanovski, Zoran; Smichkoska, Snezhana; Petrova, Deva; Lazarova, Emilija

2013-01-01

In the case of breast cancer, the prominent role of radiation therapy is an established fact. Depending on the stage of the disease, the breast is most often irradiated with two tangential fields and a direct supraclavicular field. Planning target volume is defined through the recommendations in ICRU Reports 50 and 62. The basic ‘dogma’ of radiotherapy requires the dose in the target volume to be homogenous. The favorable situation would be if the dose width was between 95% and 107%; this, however, is often not possible to be fulfilled. A technique for enhancement of homogeneity of isodose distribution would be using one or more additional fields, which will increase the dose in the volume where it is too low. These fields are called segmented fields (a technique also known as ‘field in field’) because they occupy only part of the primary fields. In this study we will show the influence of this technique on the dose homogeneity improvement in the PTV region. The mean dose in the target volume was increased from 49.51 Gy to 50.79 Gy in favor of the plans with segmented fields; and the dose homogeneity (measured in standard deviations) was also improved - 1.69 vs. 1.30. The increase in the target volume, encompassed by 95% isodose, was chosen as a parameter to characterize overall planning improvement. Thus, in our case, the improvement of dose coverage was from 93.19% to 97.06%. (Author)

Segmentation of 3D microPET images of the rat brain via the hybrid gaussian mixture method with kernel density estimation.

Science.gov (United States)

Chen, Tai-Been; Chen, Jyh-Cheng; Lu, Henry Horng-Shing

2012-01-01

Segmentation of positron emission tomography (PET) is typically achieved using the K-Means method or other approaches. In preclinical and clinical applications, the K-Means method needs a prior estimation of parameters such as the number of clusters and appropriate initialized values. This work segments microPET images using a hybrid method combining the Gaussian mixture model (GMM) with kernel density estimation. Segmentation is crucial to registration of disordered 2-deoxy-2-fluoro-D-glucose (FDG) accumulation locations with functional diagnosis and to estimate standardized uptake values (SUVs) of region of interests (ROIs) in PET images. Therefore, simulation studies are conducted to apply spherical targets to evaluate segmentation accuracy based on Tanimoto's definition of similarity. The proposed method generates a higher degree of similarity than the K-Means method. The PET images of a rat brain are used to compare the segmented shape and area of the cerebral cortex by the K-Means method and the proposed method by volume rendering. The proposed method provides clearer and more detailed activity structures of an FDG accumulation location in the cerebral cortex than those by the K-Means method.

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.

Resizing Technique-Based Hybrid Genetic Algorithm for Optimal Drift Design of Multistory Steel Frame Buildings

Directory of Open Access Journals (Sweden)

Hyo Seon Park

2014-01-01

Full Text Available Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.

A hybrid segmentation method for partitioning the liver based on 4D DCE-MR images

Science.gov (United States)

Zhang, Tian; Wu, Zhiyi; Runge, Jurgen H.; Lavini, Cristina; Stoker, Jaap; van Gulik, Thomas; Cieslak, Kasia P.; van Vliet, Lucas J.; Vos, Frans M.

2018-03-01

The Couinaud classification of hepatic anatomy partitions the liver into eight functionally independent segments. Detection and segmentation of the hepatic vein (HV), portal vein (PV) and inferior vena cava (IVC) plays an important role in the subsequent delineation of the liver segments. To facilitate pharmacokinetic modeling of the liver based on the same data, a 4D DCE-MR scan protocol was selected. This yields images with high temporal resolution but low spatial resolution. Since the liver's vasculature consists of many tiny branches, segmentation of these images is challenging. The proposed framework starts with registration of the 4D DCE-MRI series followed by region growing from manually annotated seeds in the main branches of key blood vessels in the liver. It calculates the Pearson correlation between the time intensity curves (TICs) of a seed and all voxels. A maximum correlation map for each vessel is obtained by combining the correlation maps for all branches of the same vessel through a maximum selection per voxel. The maximum correlation map is incorporated in a level set scheme to individually delineate the main vessels. Subsequently, the eight liver segments are segmented based on three vertical intersecting planes fit through the three skeleton branches of HV and IVC's center of mass as well as a horizontal plane fit through the skeleton of PV. Our segmentation regarding delineation of the vessels is more accurate than the results of two state-of-the-art techniques on five subjects in terms of the average symmetric surface distance (ASSD) and modified Hausdorff distance (MHD). Furthermore, the proposed liver partitioning achieves large overlap with manual reference segmentations (expressed in Dice Coefficient) in all but a small minority of segments (mean values between 87% and 94% for segments 2-8). The lower mean overlap for segment 1 (72%) is due to the limited spatial resolution of our DCE-MR scan protocol.

Empirical gradient threshold technique for automated segmentation across image modalities and cell lines.

Science.gov (United States)

Chalfoun, J; Majurski, M; Peskin, A; Breen, C; Bajcsy, P; Brady, M

2015-10-01

New microscopy technologies are enabling image acquisition of terabyte-sized data sets consisting of hundreds of thousands of images. In order to retrieve and analyze the biological information in these large data sets, segmentation is needed to detect the regions containing cells or cell colonies. Our work with hundreds of large images (each 21,000×21,000 pixels) requires a segmentation method that: (1) yields high segmentation accuracy, (2) is applicable to multiple cell lines with various densities of cells and cell colonies, and several imaging modalities, (3) can process large data sets in a timely manner, (4) has a low memory footprint and (5) has a small number of user-set parameters that do not require adjustment during the segmentation of large image sets. None of the currently available segmentation methods meet all these requirements. Segmentation based on image gradient thresholding is fast and has a low memory footprint. However, existing techniques that automate the selection of the gradient image threshold do not work across image modalities, multiple cell lines, and a wide range of foreground/background densities (requirement 2) and all failed the requirement for robust parameters that do not require re-adjustment with time (requirement 5). We present a novel and empirically derived image gradient threshold selection method for separating foreground and background pixels in an image that meets all the requirements listed above. We quantify the difference between our approach and existing ones in terms of accuracy, execution speed, memory usage and number of adjustable parameters on a reference data set. This reference data set consists of 501 validation images with manually determined segmentations and image sizes ranging from 0.36 Megapixels to 850 Megapixels. It includes four different cell lines and two image modalities: phase contrast and fluorescent. Our new technique, called Empirical Gradient Threshold (EGT), is derived from this reference

Segmentation: Identification of consumer segments

DEFF Research Database (Denmark)

Høg, Esben

2005-01-01

It is very common to categorise people, especially in the advertising business. Also traditional marketing theory has taken in consumer segments as a favorite topic. Segmentation is closely related to the broader concept of classification. From a historical point of view, classification has its...... origin in other sciences as for example biology, anthropology etc. From an economic point of view, it is called segmentation when specific scientific techniques are used to classify consumers to different characteristic groupings. What is the purpose of segmentation? For example, to be able to obtain...... a basic understanding of grouping people. Advertising agencies may use segmentation totarget advertisements, while food companies may usesegmentation to develop products to various groups of consumers. MAPP has for example investigated the positioning of fish in relation to other food products...

Is it possible to preserve lumbar lordosis after hybrid stabilization? Preliminary results of a novel rigid-dynamic stabilization system in degenerative lumbar pathologies.

Science.gov (United States)

Formica, Matteo; Cavagnaro, Luca; Basso, Marco; Zanirato, Andrea; Felli, Lamberto; Formica, Carlo

2015-11-01

To evaluate the results of a novel rigid-dynamic stabilization technique in lumbar degenerative segment diseases (DSD), expressly pointing out the preservation of postoperative lumbar lordosis (LL). Forty-one patients with one level lumbar DSD and initial disc degeneration at the adjacent level were treated. Circumferential lumbar arthrodesis and posterior hybrid instrumentation were performed to preserve an initial disc degeneration above the segment that has to be fused. Clinical and spino-pelvic parameters were evaluated pre- and postoperatively. At 2-year follow-up, a significant improvement of clinical outcomes was reported. No statistically significant difference was noted between postoperative and 2-year follow-up in LL and in disc/vertebral body height ratio at the upper adjacent fusion level. When properly selected, this technique leads to good results. A proper LL should be achieved after any hybrid stabilization to preserve the segment above the fusion.

A Hybrid Method for Image Segmentation Based on Artificial Fish Swarm Algorithm and Fuzzy c-Means Clustering

Directory of Open Access Journals (Sweden)

Li Ma

2015-01-01

Full Text Available Image segmentation plays an important role in medical image processing. Fuzzy c-means (FCM clustering is one of the popular clustering algorithms for medical image segmentation. However, FCM has the problems of depending on initial clustering centers, falling into local optimal solution easily, and sensitivity to noise disturbance. To solve these problems, this paper proposes a hybrid artificial fish swarm algorithm (HAFSA. The proposed algorithm combines artificial fish swarm algorithm (AFSA with FCM whose advantages of global optimization searching and parallel computing ability of AFSA are utilized to find a superior result. Meanwhile, Metropolis criterion and noise reduction mechanism are introduced to AFSA for enhancing the convergence rate and antinoise ability. The artificial grid graph and Magnetic Resonance Imaging (MRI are used in the experiments, and the experimental results show that the proposed algorithm has stronger antinoise ability and higher precision. A number of evaluation indicators also demonstrate that the effect of HAFSA is more excellent than FCM and suppressed FCM (SFCM.

PEAK-TO-AVERAGE POWER RATIO REDUCTION USING CODING AND HYBRID TECHNIQUES FOR OFDM SYSTEM

Directory of Open Access Journals (Sweden)

Bahubali K. Shiragapur

2016-03-01

Full Text Available In this article, the research work investigated is based on an error correction coding techniques are used to reduce the undesirable Peak-to-Average Power Ratio (PAPR quantity. The Golay Code (24, 12, Reed-Muller code (16, 11, Hamming code (7, 4 and Hybrid technique (Combination of Signal Scrambling and Signal Distortion proposed by us are used as proposed coding techniques, the simulation results shows that performance of Hybrid technique, reduces PAPR significantly as compared to Conventional and Modified Selective mapping techniques. The simulation results are validated through statistical properties, for proposed technique’s autocorrelation value is maximum shows reduction in PAPR. The symbol preference is the key idea to reduce PAPR based on Hamming distance. The simulation results are discussed in detail, in this article.

Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization

Energy Technology Data Exchange (ETDEWEB)

Mohaghegh, Zahra [Center for Risk and Reliability, University of Maryland, College Park, MD 20742 (United States)], E-mail: mohagheg@umd.edu; Kazemi, Reza; Mosleh, Ali [Center for Risk and Reliability, University of Maryland, College Park, MD 20742 (United States)

2009-05-15

This paper is a result of a research with the primary purpose of extending Probabilistic Risk Assessment (PRA) modeling frameworks to include the effects of organizational factors as the deeper, more fundamental causes of accidents and incidents. There have been significant improvements in the sophistication of quantitative methods of safety and risk assessment, but the progress on techniques most suitable for organizational safety risk frameworks has been limited. The focus of this paper is on the choice of 'representational schemes' and 'techniques.' A methodology for selecting appropriate candidate techniques and their integration in the form of a 'hybrid' approach is proposed. Then an example is given through an integration of System Dynamics (SD), Bayesian Belief Network (BBN), Event Sequence Diagram (ESD), and Fault Tree (FT) in order to demonstrate the feasibility and value of hybrid techniques. The proposed hybrid approach integrates deterministic and probabilistic modeling perspectives, and provides a flexible risk management tool for complex socio-technical systems. An application of the hybrid technique is provided in the aviation safety domain, focusing on airline maintenance systems. The example demonstrates how the hybrid method can be used to analyze the dynamic effects of organizational factors on system risk.

ACM-based automatic liver segmentation from 3-D CT images by combining multiple atlases and improved mean-shift techniques.

Science.gov (United States)

Ji, Hongwei; He, Jiangping; Yang, Xin; Deklerck, Rudi; Cornelis, Jan

2013-05-01

In this paper, we present an autocontext model(ACM)-based automatic liver segmentation algorithm, which combines ACM, multiatlases, and mean-shift techniques to segment liver from 3-D CT images. Our algorithm is a learning-based method and can be divided into two stages. At the first stage, i.e., the training stage, ACM is performed to learn a sequence of classifiers in each atlas space (based on each atlas and other aligned atlases). With the use of multiple atlases, multiple sequences of ACM-based classifiers are obtained. At the second stage, i.e., the segmentation stage, the test image will be segmented in each atlas space by applying each sequence of ACM-based classifiers. The final segmentation result will be obtained by fusing segmentation results from all atlas spaces via a multiclassifier fusion technique. Specially, in order to speed up segmentation, given a test image, we first use an improved mean-shift algorithm to perform over-segmentation and then implement the region-based image labeling instead of the original inefficient pixel-based image labeling. The proposed method is evaluated on the datasets of MICCAI 2007 liver segmentation challenge. The experimental results show that the average volume overlap error and the average surface distance achieved by our method are 8.3% and 1.5 m, respectively, which are comparable to the results reported in the existing state-of-the-art work on liver segmentation.

A comparative study on medical image segmentation methods

Directory of Open Access Journals (Sweden)

Praylin Selva Blessy SELVARAJ ASSLEY

2014-03-01

Full Text Available Image segmentation plays an important role in medical images. It has been a relevant research area in computer vision and image analysis. Many segmentation algorithms have been proposed for medical images. This paper makes a review on segmentation methods for medical images. In this survey, segmentation methods are divided into five categories: region based, boundary based, model based, hybrid based and atlas based. The five different categories with their principle ideas, advantages and disadvantages in segmenting different medical images are discussed.

Performance Evaluation of Frequency Transform Based Block Classification of Compound Image Segmentation Techniques

Science.gov (United States)

Selwyn, Ebenezer Juliet; Florinabel, D. Jemi

2018-04-01

Compound image segmentation plays a vital role in the compression of computer screen images. Computer screen images are images which are mixed with textual, graphical, or pictorial contents. In this paper, we present a comparison of two transform based block classification of compound images based on metrics like speed of classification, precision and recall rate. Block based classification approaches normally divide the compound images into fixed size blocks of non-overlapping in nature. Then frequency transform like Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are applied over each block. Mean and standard deviation are computed for each 8 × 8 block and are used as features set to classify the compound images into text/graphics and picture/background block. The classification accuracy of block classification based segmentation techniques are measured by evaluation metrics like precision and recall rate. Compound images of smooth background and complex background images containing text of varying size, colour and orientation are considered for testing. Experimental evidence shows that the DWT based segmentation provides significant improvement in recall rate and precision rate approximately 2.3% than DCT based segmentation with an increase in block classification time for both smooth and complex background images.

Strain analysis in CRT candidates using the novel segment length in cine (SLICE) post-processing technique on standard CMR cine images.

Science.gov (United States)

Zweerink, Alwin; Allaart, Cornelis P; Kuijer, Joost P A; Wu, LiNa; Beek, Aernout M; van de Ven, Peter M; Meine, Mathias; Croisille, Pierre; Clarysse, Patrick; van Rossum, Albert C; Nijveldt, Robin

2017-12-01

Although myocardial strain analysis is a potential tool to improve patient selection for cardiac resynchronization therapy (CRT), there is currently no validated clinical approach to derive segmental strains. We evaluated the novel segment length in cine (SLICE) technique to derive segmental strains from standard cardiovascular MR (CMR) cine images in CRT candidates. Twenty-seven patients with left bundle branch block underwent CMR examination including cine imaging and myocardial tagging (CMR-TAG). SLICE was performed by measuring segment length between anatomical landmarks throughout all phases on short-axis cines. This measure of frame-to-frame segment length change was compared to CMR-TAG circumferential strain measurements. Subsequently, conventional markers of CRT response were calculated. Segmental strains showed good to excellent agreement between SLICE and CMR-TAG (septum strain, intraclass correlation coefficient (ICC) 0.76; lateral wall strain, ICC 0.66). Conventional markers of CRT response also showed close agreement between both methods (ICC 0.61-0.78). Reproducibility of SLICE was excellent for intra-observer testing (all ICC ≥0.76) and good for interobserver testing (all ICC ≥0.61). The novel SLICE post-processing technique on standard CMR cine images offers both accurate and robust segmental strain measures compared to the 'gold standard' CMR-TAG technique, and has the advantage of being widely available. • Myocardial strain analysis could potentially improve patient selection for CRT. • Currently a well validated clinical approach to derive segmental strains is lacking. • The novel SLICE technique derives segmental strains from standard CMR cine images. • SLICE-derived strain markers of CRT response showed close agreement with CMR-TAG. • Future studies will focus on the prognostic value of SLICE in CRT candidates.

Techniques to distinguish between electron and photon induced events using segmented germanium detectors

International Nuclear Information System (INIS)

Kroeninger, K.

2007-01-01

Two techniques to distinguish between electron and photon induced events in germanium detectors were studied: (1) anti-coincidence requirements between the segments of segmented germanium detectors and (2) the analysis of the time structure of the detector response. An 18-fold segmented germanium prototype detector for the GERDA neutrinoless double beta-decay experiment was characterized. The rejection of photon induced events was measured for the strongest lines in 60 Co, 152 Eu and 228 Th. An accompanying Monte Carlo simulation was performed and the results were compared to data. An overall agreement with deviations of the order of 5-10% was obtained. The expected background index of the GERDA experiment was estimated. The sensitivity of the GERDA experiment was determined. Special statistical tools were developed to correctly treat the small number of events expected. The GERDA experiment uses a cryogenic liquid as the operational medium for the germanium detectors. It was shown that germanium detectors can be reliably operated through several cooling cycles. (orig.)

Techniques to distinguish between electron and photon induced events using segmented germanium detectors

Energy Technology Data Exchange (ETDEWEB)

Kroeninger, K.

2007-06-05

Two techniques to distinguish between electron and photon induced events in germanium detectors were studied: (1) anti-coincidence requirements between the segments of segmented germanium detectors and (2) the analysis of the time structure of the detector response. An 18-fold segmented germanium prototype detector for the GERDA neutrinoless double beta-decay experiment was characterized. The rejection of photon induced events was measured for the strongest lines in {sup 60}Co, {sup 152}Eu and {sup 228}Th. An accompanying Monte Carlo simulation was performed and the results were compared to data. An overall agreement with deviations of the order of 5-10% was obtained. The expected background index of the GERDA experiment was estimated. The sensitivity of the GERDA experiment was determined. Special statistical tools were developed to correctly treat the small number of events expected. The GERDA experiment uses a cryogenic liquid as the operational medium for the germanium detectors. It was shown that germanium detectors can be reliably operated through several cooling cycles. (orig.)

Improvements in analysis techniques for segmented mirror arrays

Science.gov (United States)

Michels, Gregory J.; Genberg, Victor L.; Bisson, Gary R.

2016-08-01

The employment of actively controlled segmented mirror architectures has become increasingly common in the development of current astronomical telescopes. Optomechanical analysis of such hardware presents unique issues compared to that of monolithic mirror designs. The work presented here is a review of current capabilities and improvements in the methodology of the analysis of mechanically induced surface deformation of such systems. The recent improvements include capability to differentiate surface deformation at the array and segment level. This differentiation allowing surface deformation analysis at each individual segment level offers useful insight into the mechanical behavior of the segments that is unavailable by analysis solely at the parent array level. In addition, capability to characterize the full displacement vector deformation of collections of points allows analysis of mechanical disturbance predictions of assembly interfaces relative to other assembly interfaces. This capability, called racking analysis, allows engineers to develop designs for segment-to-segment phasing performance in assembly integration, 0g release, and thermal stability of operation. The performance predicted by racking has the advantage of being comparable to the measurements used in assembly of hardware. Approaches to all of the above issues are presented and demonstrated by example with SigFit, a commercially available tool integrating mechanical analysis with optical analysis.

Combined amplification and hybridization techniques for genome scanning in vegetatively propagated crops

International Nuclear Information System (INIS)

Kahl, G.; Ramser, J.; Terauchi, R.; Lopez-Peralta, C.; Asemota, H.N.; Weising, K.

1998-01-01

A combination of PCR- and hybridization-based genome scanning techniques and sequence comparisons between non-coding chloroplast DNA flanking tRNA genes has been employed to screen Dioscorea species for intra- and interspecific genetic diversity. This methodology detected extensive polymorphisms within Dioscorea bulbifera L., and revealed taxonomic and phylogenetic relationships among cultivated Guinea yams varieties and their potential wild progenitors. Finally, screening of yam germplasm grown in Jamaica permitted reliable discrimination between all major cultivars. Genome scanning by micro satellite-primed PCR (MP-PCR) and random amplified polymorphic DNA (RAPD) analysis in combination with the novel random amplified micro satellite polymorphisms (RAMPO) hybridization technique has shown high potential for the genetic analysis of yams, and holds promise for other vegetatively propagated orphan crops. (author)

AN EFFICIENT TECHNIQUE FOR RETINAL VESSEL SEGMENTATION AND DENOISING USING MODIFIED ISODATA AND CLAHE

Directory of Open Access Journals (Sweden)

Khan Bahadar Khan

2016-11-01

Full Text Available Retinal damage caused due to complications of diabetes is known as Diabetic Retinopathy (DR. In this case, the vision is obscured due to the damage of retinal tinny blood vessels of the retina. These tinny blood vessels may cause leakage which affect the vision and can lead to complete blindness. Identification of these new retinal vessels and their structure is essential for analysis of DR. Automatic blood vessels segmentation plays a significant role to assist subsequent automatic methodologies that aid to such analysis. In literature most of the people have used computationally hungry a strong preprocessing steps followed by a simple thresholding and post processing, But in our proposed technique we utilize an arrangement of  light pre-processing which consists of Contrast Limited Adaptive Histogram Equalization (CLAHE for contrast enhancement, a difference image of green channel from its Gaussian blur filtered image to remove local noise or geometrical object, Modified Iterative Self Organizing Data Analysis Technique (MISODATA for segmentation of vessel and non-vessel pixels based on global and local thresholding, and a strong  post processing using region properties (area, eccentricity to eliminate the unwanted region/segment, non-vessel pixels and noise that never been used to reject misclassified foreground pixels. The strategy is tested on the publically accessible DRIVE (Digital Retinal Images for Vessel Extraction and STARE (STructured Analysis of the REtina databases. The performance of proposed technique is assessed comprehensively and the acquired accuracy, robustness, low complexity and high efficiency and very less computational time that make the method an efficient tool for automatic retinal image analysis. Proposed technique perform well as compared to the existing strategies on the online available databases in term of accuracy, sensitivity, specificity, false positive rate, true positive rate and area under receiver

Implementation of the Fluorescent in Situ Hybridization technique in the Faculty of Medicine, UdelaR

Directory of Open Access Journals (Sweden)

Andrea Cairus

2017-11-01

Full Text Available The Cytogenetic Laboratory of the Faculty of Medicine processes, on average, 300 annual samples of public and private healthcare centers by conventional cytogenetics. It is essential to implement new techniques to improve the quality of the service offered. The purpose of this work was to implement the Fluorescent in situ Hybridization technique (FISH. An observational, cross-sectional, analytical study was performed. Peripheral blood samples from patients with sex chromosomopathies diagnosed by conventional cytogenetics were analyzed. Fluorescent in situ hybridization technique was applied, comparing results with FISH and with conventional cytogenetics. The percentage of mosaicism detected by conventional cytogenetics and Fluorescent in situ Hybridization was studied: 24 samples were analyzed; 19 presented numerical alterations, 3 structural and 2 both. Numerical alterations were Turner syndrome, Klinefelter syndrome, XXX syndrome and XYY syndrome. Concordance in diagnoses was found for both techniques. For Turner syndrome, 8 of 12 samples corresponded to mosaicism, and there were no significant differences between conventional cytogenetics and the technique studied (p0.05. Klinefelter syndrome and XYY were both presented in a non-mosaic karyotype. For XXX syndrome, a normal line (46, XX was observed in three of the samples, in a percentage close to the cut off. From this research, it will be possible to implement Fluorescent in situ Hybridization in this service, to extend it to other pathologies and to enable the training of human resources; consolidating this laboratory as a national academic reference center.

Obtention of tumor volumes in PET images stacks using techniques of colored image segmentation

International Nuclear Information System (INIS)

Vieira, Jose W.; Lopes Filho, Ferdinand J.; Vieira, Igor F.

2014-01-01

This work demonstrated step by step how to segment color images of the chest of an adult in order to separate the tumor volume without significantly changing the values of the components R (Red), G (Green) and B (blue) of the colors of the pixels. For having information which allow to build color map you need to segment and classify the colors present at appropriate intervals in images. The used segmentation technique is to select a small rectangle with color samples in a given region and then erase with a specific color called 'rubber' the other regions of image. The tumor region was segmented into one of the images available and the procedure is displayed in tutorial format. All necessary computational tools have been implemented in DIP (Digital Image Processing), software developed by the authors. The results obtained, in addition to permitting the construction the colorful map of the distribution of the concentration of activity in PET images will also be useful in future work to enter tumors in voxel phantoms in order to perform dosimetric assessments

COMPARISON AND EVALUATION OF CLUSTER BASED IMAGE SEGMENTATION TECHNIQUES

OpenAIRE

Hetangi D. Mehta*, Daxa Vekariya, Pratixa Badelia

2017-01-01

Image segmentation is the classification of an image into different groups. Numerous algorithms using different approaches have been proposed for image segmentation. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity. A review is done on different types of clustering methods used for image segmentation. Also a methodology is proposed to classify and quantify different clustering algorithms based on their consistency in different...

Strain analysis in CRT candidates using the novel segment length in cine (SLICE) post-processing technique on standard CMR cine images

Energy Technology Data Exchange (ETDEWEB)

Zweerink, Alwin; Allaart, Cornelis P.; Wu, LiNa; Beek, Aernout M.; Rossum, Albert C. van; Nijveldt, Robin [VU University Medical Center, Department of Cardiology, and Institute for Cardiovascular Research (ICaR-VU), Amsterdam (Netherlands); Kuijer, Joost P.A. [VU University Medical Center, Department of Physics and Medical Technology, Amsterdam (Netherlands); Ven, Peter M. van de [VU University Medical Center, Department of Epidemiology and Biostatistics, Amsterdam (Netherlands); Meine, Mathias [University Medical Center, Department of Cardiology, Utrecht (Netherlands); Croisille, Pierre; Clarysse, Patrick [Univ Lyon, UJM-Saint-Etienne, INSA, CNRS UMR 5520, INSERM U1206, CREATIS, Saint-Etienne (France)

2017-12-15

Although myocardial strain analysis is a potential tool to improve patient selection for cardiac resynchronization therapy (CRT), there is currently no validated clinical approach to derive segmental strains. We evaluated the novel segment length in cine (SLICE) technique to derive segmental strains from standard cardiovascular MR (CMR) cine images in CRT candidates. Twenty-seven patients with left bundle branch block underwent CMR examination including cine imaging and myocardial tagging (CMR-TAG). SLICE was performed by measuring segment length between anatomical landmarks throughout all phases on short-axis cines. This measure of frame-to-frame segment length change was compared to CMR-TAG circumferential strain measurements. Subsequently, conventional markers of CRT response were calculated. Segmental strains showed good to excellent agreement between SLICE and CMR-TAG (septum strain, intraclass correlation coefficient (ICC) 0.76; lateral wall strain, ICC 0.66). Conventional markers of CRT response also showed close agreement between both methods (ICC 0.61-0.78). Reproducibility of SLICE was excellent for intra-observer testing (all ICC ≥0.76) and good for interobserver testing (all ICC ≥0.61). The novel SLICE post-processing technique on standard CMR cine images offers both accurate and robust segmental strain measures compared to the 'gold standard' CMR-TAG technique, and has the advantage of being widely available. (orig.)

Strain analysis in CRT candidates using the novel segment length in cine (SLICE) post-processing technique on standard CMR cine images

International Nuclear Information System (INIS)

Zweerink, Alwin; Allaart, Cornelis P.; Wu, LiNa; Beek, Aernout M.; Rossum, Albert C. van; Nijveldt, Robin; Kuijer, Joost P.A.; Ven, Peter M. van de; Meine, Mathias; Croisille, Pierre; Clarysse, Patrick

2017-01-01

Although myocardial strain analysis is a potential tool to improve patient selection for cardiac resynchronization therapy (CRT), there is currently no validated clinical approach to derive segmental strains. We evaluated the novel segment length in cine (SLICE) technique to derive segmental strains from standard cardiovascular MR (CMR) cine images in CRT candidates. Twenty-seven patients with left bundle branch block underwent CMR examination including cine imaging and myocardial tagging (CMR-TAG). SLICE was performed by measuring segment length between anatomical landmarks throughout all phases on short-axis cines. This measure of frame-to-frame segment length change was compared to CMR-TAG circumferential strain measurements. Subsequently, conventional markers of CRT response were calculated. Segmental strains showed good to excellent agreement between SLICE and CMR-TAG (septum strain, intraclass correlation coefficient (ICC) 0.76; lateral wall strain, ICC 0.66). Conventional markers of CRT response also showed close agreement between both methods (ICC 0.61-0.78). Reproducibility of SLICE was excellent for intra-observer testing (all ICC ≥0.76) and good for interobserver testing (all ICC ≥0.61). The novel SLICE post-processing technique on standard CMR cine images offers both accurate and robust segmental strain measures compared to the 'gold standard' CMR-TAG technique, and has the advantage of being widely available. (orig.)

Automatic Melody Segmentation

NARCIS (Netherlands)

Rodríguez López, Marcelo

2016-01-01

The work presented in this dissertation investigates music segmentation. In the field of Musicology, segmentation refers to a score analysis technique, whereby notated pieces or passages of these pieces are divided into “units” referred to as sections, periods, phrases, and so on. Segmentation

Automatic segmentation of vertebrae from radiographs

DEFF Research Database (Denmark)

Mysling, Peter; Petersen, Peter Kersten; Nielsen, Mads

2011-01-01

Segmentation of vertebral contours is an essential task in the design of automatic tools for vertebral fracture assessment. In this paper, we propose a novel segmentation technique which does not require operator interaction. The proposed technique solves the segmentation problem in a hierarchical...... is constrained by a conditional shape model, based on the variability of the coarse spine location estimates. The technique is evaluated on a data set of manually annotated lumbar radiographs. The results compare favorably to the previous work in automatic vertebra segmentation, in terms of both segmentation...

Developing a hybrid dictionary-based bio-entity recognition technique

Science.gov (United States)

2015-01-01

Background Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. Methods This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. Results The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. Conclusions The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall. PMID:26043907

Developing a hybrid dictionary-based bio-entity recognition technique.

Science.gov (United States)

Song, Min; Yu, Hwanjo; Han, Wook-Shin

2015-01-01

Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall.

Combined amplification and hybridization techniques for genome scanning in vegetatively propagated crops

Energy Technology Data Exchange (ETDEWEB)

Kahl, G; Ramser, J; Terauchi, R [Biocentre, University of Frankfurt, Frankfurt am Main (Germany); Lopez-Peralta, C [IRGP, Colegio de Postgraduados, Montecillo, Edo. de Mexico, Texcoco (Mexico); Asemota, H N [Biotechnology Centre, University of the West Indies, Mona, Kingston (Jamaica); Weising, K [School of Biological Sciences, University of Auckland, Auckland (New Zealand)

1998-10-01

A combination of PCR- and hybridization-based genome scanning techniques and sequence comparisons between non-coding chloroplast DNA flanking tRNA genes has been employed to screen Dioscorea species for intra- and interspecific genetic diversity. This methodology detected extensive polymorphisms within Dioscorea bulbifera L., and revealed taxonomic and phylogenetic relationships among cultivated Guinea yams varieties and their potential wild progenitors. Finally, screening of yam germplasm grown in Jamaica permitted reliable discrimination between all major cultivars. Genome scanning by micro satellite-primed PCR (MP-PCR) and random amplified polymorphic DNA (RAPD) analysis in combination with the novel random amplified micro satellite polymorphisms (RAMPO) hybridization technique has shown high potential for the genetic analysis of yams, and holds promise for other vegetatively propagated orphan crops. (author) 46 refs, 3 figs, 3 tabs

Improved Image Encryption for Real-Time Application over Wireless Communication Networks using Hybrid Cryptography Technique

Directory of Open Access Journals (Sweden)

Kazeem B. Adedeji

2016-12-01

Full Text Available Advances in communication networks have enabled organization to send confidential data such as digital images over wireless networks. However, the broadcast nature of wireless communication channel has made it vulnerable to attack from eavesdroppers. We have developed a hybrid cryptography technique, and we present its application to digital images as a means of improving the security of digital image for transmission over wireless communication networks. The hybrid technique uses a combination of a symmetric (Data Encryption Standard and asymmetric (Rivest Shamir Adleman cryptographic algorithms to secure data to be transmitted between different nodes of a wireless network. Three different image samples of type jpeg, png and jpg were tested using this technique. The results obtained showed that the hybrid system encrypt the images with minimal simulation time, and high throughput. More importantly, there is no relation or information between the original images and their encrypted form, according to Shannon’s definition of perfect security, thereby making the system much more secure.

Safety Assessment of Two Hybrid Instrumentation Techniques in a Dental Student Endodontic Clinic: A Retrospective Study.

Science.gov (United States)

Coelho, Marcelo Santos; Card, Steven John; Tawil, Peter Zahi

2017-03-01

The aim of this study was to retrospectively assess the safety potential of a hybrid technique combining nickel-titanium (NiTi) reciprocating and rotary instruments by third- and fourth-year dental students in the predoctoral endodontics clinic at one U.S. dental school. For the study, 3,194 root canal treatments performed by 317 dental students from 2012 through 2015 were evaluated for incidence of ledge creation and instrument separation. The hybrid reciprocating and rotary technique (RRT) consisted of a glide path creation with stainless steel hand files up to size 15/02, a crown down preparation with a NiTi reciprocating instrument, and an apical preparation with NiTi rotary instruments. The control was a traditional rotary and hand technique (RHT) that consisted of the same glide path procedure followed by a crown down preparation with NiTi rotary instruments and an apical preparation with NiTi hand instruments. The results showed that the RHT technique presented a rate of ledge creation of 1.4% per root and the RRT technique was 0.5% per root (protary technique for root canal instrumentation by these dental students provided good safety. This hybrid technique offered a low rate of ledge creation along with no NiTi instrument separation.

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks

Directory of Open Access Journals (Sweden)

Mihai-Victor Micea

2017-06-01

Full Text Available Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H2RTS, which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU utilization factor. From the detailed, integrated schedulability analysis of the H2RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks.

Science.gov (United States)

Micea, Mihai-Victor; Stangaciu, Cristina-Sorina; Stangaciu, Valentin; Curiac, Daniel-Ioan

2017-06-26

Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H²RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H²RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

New multispectral MRI data fusion technique for white matter lesion segmentation: method and comparison with thresholding in FLAIR images

International Nuclear Information System (INIS)

Del C Valdes Hernandez, Maria; Ferguson, Karen J.; Chappell, Francesca M.; Wardlaw, Joanna M.

2010-01-01

Brain tissue segmentation by conventional threshold-based techniques may have limited accuracy and repeatability in older subjects. We present a new multispectral magnetic resonance (MR) image analysis approach for segmenting normal and abnormal brain tissue, including white matter lesions (WMLs). We modulated two 1.5T MR sequences in the red/green colour space and calculated the tissue volumes using minimum variance quantisation. We tested it on 14 subjects, mean age 73.3 ± 10 years, representing the full range of WMLs and atrophy. We compared the results of WML segmentation with those using FLAIR-derived thresholds, examined the effect of sampling location, WML amount and field inhomogeneities, and tested observer reliability and accuracy. FLAIR-derived thresholds were significantly affected by the location used to derive the threshold (P = 0.0004) and by WML volume (P = 0.0003), and had higher intra-rater variability than the multispectral technique (mean difference ± SD: 759 ± 733 versus 69 ± 326 voxels respectively). The multispectral technique misclassified 16 times fewer WMLs. Initial testing suggests that the multispectral technique is highly reproducible and accurate with the potential to be applied to routinely collected clinical MRI data. (orig.)

Development of a hybrid strength training technique for paretic lower-limb muscles

NARCIS (Netherlands)

Bennett, T. L.; Glaser, R. M.; Janssen, T. W J; Couch, W. P.; Herr, C. J.; Almeyda, J. W.; Petrofsky, S. H.; Akuthota, P.

1996-01-01

A hybrid resistance exercise technique for strength training of patients with lower-limb paresis was developed. It consists of electrical stimulation-induced contractions (ESIC) superimposed on voluntary contractions to increase recruitment of motor units and the functional load capability of

Supersonic impinging jet noise reduction using a hybrid control technique

Science.gov (United States)

Wiley, Alex; Kumar, Rajan

2015-07-01

Control of the highly resonant flowfield associated with supersonic impinging jet has been experimentally investigated. Measurements were made in the supersonic impinging jet facility at the Florida State University for a Mach 1.5 ideally expanded jet. Measurements included unsteady pressures on a surface plate near the nozzle exit, acoustics in the nearfield and beneath the impingement plane, and velocity field using particle image velocimetry. Both passive control using porous surface and active control with high momentum microjet injection are effective in reducing nearfield noise and flow unsteadiness over a range of geometrical parameters; however, the type of noise reduction achieved by the two techniques is different. The passive control reduces broadband noise whereas microjet injection attenuates high amplitude impinging tones. The hybrid control, a combination of two control methods, reduces both broadband and high amplitude impinging tones and surprisingly its effectiveness is more that the additive effect of the two control techniques. The flow field measurements show that with hybrid control the impinging jet is stabilized and the turbulence quantities such as streamwise turbulence intensity, transverse turbulence intensity and turbulent shear stress are significantly reduced.

The commercial use of segmentation and predictive modeling techniques for database marketing in the Netherlands

NARCIS (Netherlands)

Verhoef, PC; Spring, PN; Hoekstra, JC; Leeflang, PSH

Although the application of segmentation and predictive modeling is an important topic in the database marketing (DBM) literature, no study has yet investigated the extent of adoption of these techniques. We present the results of a Dutch survey involving 228 database marketing companies. We find

Image Segmentation using a Refined Comprehensive Learning Particle Swarm Optimizer for Maximum Tsallis Entropy Thresholding

OpenAIRE

L. Jubair Ahmed; A. Ebenezer Jeyakumar

2013-01-01

Thresholding is one of the most important techniques for performing image segmentation. In this paper to compute optimum thresholds for Maximum Tsallis entropy thresholding (MTET) model, a new hybrid algorithm is proposed by integrating the Comprehensive Learning Particle Swarm Optimizer (CPSO) with the Powell’s Conjugate Gradient (PCG) method. Here the CPSO will act as the main optimizer for searching the near-optimal thresholds while the PCG method will be used to fine tune the best solutio...

Comparison of segmentation techniques to determine the geometric parameters of structured surfaces

International Nuclear Information System (INIS)

MacAulay, Gavin D; Giusca, Claudiu L; Leach, Richard K; Senin, Nicola

2014-01-01

Structured surfaces, defined as surfaces characterized by topography features whose shape is defined by design specifications, are increasingly being used in industry for a variety of applications, including improving the tribological properties of surfaces. However, characterization of such surfaces still remains an issue. Techniques have been recently proposed, based on identifying and extracting the relevant features from a structured surface so they can be verified individually, using methods derived from those commonly applied to standard-sized parts. Such emerging approaches show promise but are generally complex and characterized by multiple data processing steps making performance difficult to assess. This paper focuses on the segmentation step, i.e. partitioning the topography so that the relevant features can be separated from the background. Segmentation is key for defining the geometric boundaries of the individual feature, which in turn affects any computation of feature size, shape and localization. This paper investigates the effect of varying the segmentation algorithm and its controlling parameters by considering a test case: a structured surface for bearing applications, the relevant features being micro-dimples designed for friction reduction. In particular, the mechanisms through which segmentation leads to identification of the dimple boundary and influences dimensional properties, such as dimple diameter and depth, are illustrated. It is shown that, by using different methods and control parameters, a significant range of measurement results can be achieved, which may not necessarily agree. Indications on how to investigate the influence of each specific choice are given; in particular, stability of the algorithms with respect to control parameters is analyzed as a means to investigate ease of calibration and flexibility to adapt to specific, application-dependent characterization requirements. (paper)

Strain analysis in CRT candidates using the novel segment length in cine (SLICE) post-processing technique on standard CMR cine images

NARCIS (Netherlands)

Zweerink, A.; Allaart, C.P.; Kuijer, J.P.A.; Wu, L.; Beek, A.M.; Ven, P.M. van de; Meine, M.; Croisille, P.; Clarysse, P.; Rossum, A.C. van; Nijveldt, R.

2017-01-01

OBJECTIVES: Although myocardial strain analysis is a potential tool to improve patient selection for cardiac resynchronization therapy (CRT), there is currently no validated clinical approach to derive segmental strains. We evaluated the novel segment length in cine (SLICE) technique to derive

Magnet system optimization for segmented adaptive-gap in-vacuum undulator

Energy Technology Data Exchange (ETDEWEB)

Kitegi, C., E-mail: ckitegi@bnl.gov; Chubar, O.; Eng, C. [Energy Sciences Directorates, Brookhaven National Laboratory, Upton NY1 1973 (United States)

2016-07-27

Segmented Adaptive Gap in-vacuum Undulator (SAGU), in which different segments have different gaps and periods, promises a considerable spectral performance gain over a conventional undulator with uniform gap and period. According to calculations, this gain can be comparable to the gain achievable with a superior undulator technology (e.g. a room-temperature in-vacuum hybrid SAGU would perform as a cryo-cooled hybrid in-vacuum undulator with uniform gap and period). However, for reaching the high spectral performance, SAGU magnetic design has to include compensation of kicks experienced by the electron beam at segment junctions because of different deflection parameter values in the segments. We show that such compensation to large extent can be accomplished by using a passive correction, however, simple correction coils are nevertheless required as well to reach perfect compensation over a whole SAGU tuning range. Magnetic optimizations performed with Radia code, and the resulting undulator radiation spectra calculated using SRW code, demonstrating a possibility of nearly perfect correction, are presented.

A Standalone PV System with a Hybrid P&O MPPT Optimization Technique

Directory of Open Access Journals (Sweden)

S. Hota

2017-12-01

Full Text Available In this paper a maximum power point tracking (MPPT design for a photovoltaic (PV system using a hybrid optimization technique is proposed. For maximum power transfer, maximum harvestable power from a PV cell in a dynamically changing surrounding should be known. The proposed technique is compared with the conventional Perturb and Observe (P&O technique. A comparative analysis of power-voltage and current-voltage characteristics of a PV cell with and without the MPPT module when connected to the grid was performed in SIMULINK, to demonstrate the increment in the efficiency of the PV module after using the MPPT module.

Chromosome condensation and segmentation

International Nuclear Information System (INIS)

Viegas-Pequignot, E.M.

1981-01-01

Some aspects of chromosome condensation in mammalians -humans especially- were studied by means of cytogenetic techniques of chromosome banding. Two further approaches were adopted: a study of normal condensation as early as prophase, and an analysis of chromosome segmentation induced by physical (temperature and γ-rays) or chemical agents (base analogues, antibiotics, ...) in order to show out the factors liable to affect condensation. Here 'segmentation' means an abnormal chromosome condensation appearing systematically and being reproducible. The study of normal condensation was made possible by the development of a technique based on cell synchronization by thymidine and giving prophasic and prometaphasic cells. Besides, the possibility of inducing R-banding segmentations on these cells by BrdU (5-bromodeoxyuridine) allowed a much finer analysis of karyotypes. Another technique was developed using 5-ACR (5-azacytidine), it allowed to induce a segmentation similar to the one obtained using BrdU and identify heterochromatic areas rich in G-C bases pairs [fr

Segmentation of the Infant Food Market

OpenAIRE

Hrůzová, Daniela

2015-01-01

The theoretical part covers general market segmentation, namely the marketing importance of differences among consumers, the essence of market segmentation, its main conditions and the process of segmentation, which consists of four consecutive phases - defining the market, determining important criteria, uncovering segments and developing segment profiles. The segmentation criteria, segmentation approaches, methods and techniques for the process of market segmentation are also described in t...

Electricity market price spike analysis by a hybrid data model and feature selection technique

International Nuclear Information System (INIS)

Amjady, Nima; Keynia, Farshid

2010-01-01

In a competitive electricity market, energy price forecasting is an important activity for both suppliers and consumers. For this reason, many techniques have been proposed to predict electricity market prices in the recent years. However, electricity price is a complex volatile signal owning many spikes. Most of electricity price forecast techniques focus on the normal price prediction, while price spike forecast is a different and more complex prediction process. Price spike forecasting has two main aspects: prediction of price spike occurrence and value. In this paper, a novel technique for price spike occurrence prediction is presented composed of a new hybrid data model, a novel feature selection technique and an efficient forecast engine. The hybrid data model includes both wavelet and time domain variables as well as calendar indicators, comprising a large candidate input set. The set is refined by the proposed feature selection technique evaluating both relevancy and redundancy of the candidate inputs. The forecast engine is a probabilistic neural network, which are fed by the selected candidate inputs of the feature selection technique and predict price spike occurrence. The efficiency of the whole proposed method for price spike occurrence forecasting is evaluated by means of real data from the Queensland and PJM electricity markets. (author)

A Hybrid Islanding Detection Technique Using Average Rate of Voltage Change and Real Power Shift

DEFF Research Database (Denmark)

Mahat, Pukar; Chen, Zhe; Bak-Jensen, Birgitte

2009-01-01

The mainly used islanding detection techniques may be classified as active and passive techniques. Passive techniques don't perturb the system but they have larger nondetection znes, whereas active techniques have smaller nondetection zones but they perturb the system. In this paper, a new hybrid...... technique is proposed to solve this problem. An average rate of voltage change (passive technique) has been used to initiate a real power shift (active technique), which changes the eal power of distributed generation (DG), when the passive technique cannot have a clear discrimination between islanding...

Cleaning capacity of hybrid instrumentation technique using reamer with alternating cutting edges system files: Histological analysis

Directory of Open Access Journals (Sweden)

Emilio Carlos Sponchiado Junior

2014-01-01

Full Text Available Aim: The aim of the following study is to evaluate the cleaning capacity of a hybrid instrumentation technique using Reamer with Alternating Cutting Edges (RaCe system files in the apical third of mesial roots of mandibular molars. Materials and Methods: Twenty teeth were selected and separated into two groups (n = 20 according to instrumentation technique as follows: BioRaCe - chemomechanical preparation with K-type files #10 and #15; and files BioRaCe BR0, BR1, BR2, BR3, and BR4; HybTec - hybrid instrumentation technique with K-type files #10 and #15 in the working length, #20 at 2 mm, #25 at 3 mm, cervical preparation with Largo burs #1 and #2; apical preparation with K-type files #15, #20, and #25 and RaCe files #25.04 and #30.04. The root canals were irrigated with 1 ml of 2.5% sodium hypochlorite at each change of instrument. The specimens were histologically processed and photographed under light optical microscope. The images were inserted onto an integration grid to count the amount of debris present in the root canal. Results: BioRaCe presented the highest percentage of debris in the apical third, however, with no statistically significant difference for HybTec (P > 0.05. Conclusions: The hybrid technique presented similar cleaning capacity as the technique recommended by the manufacturer.

Computed tomography landmark-based semi-automated mesh morphing and mapping techniques: generation of patient specific models of the human pelvis without segmentation.

Science.gov (United States)

Salo, Zoryana; Beek, Maarten; Wright, David; Whyne, Cari Marisa

2015-04-13

Current methods for the development of pelvic finite element (FE) models generally are based upon specimen specific computed tomography (CT) data. This approach has traditionally required segmentation of CT data sets, which is time consuming and necessitates high levels of user intervention due to the complex pelvic anatomy. The purpose of this research was to develop and assess CT landmark-based semi-automated mesh morphing and mapping techniques to aid the generation and mechanical analysis of specimen-specific FE models of the pelvis without the need for segmentation. A specimen-specific pelvic FE model (source) was created using traditional segmentation methods and morphed onto a CT scan of a different (target) pelvis using a landmark-based method. The morphed model was then refined through mesh mapping by moving the nodes to the bone boundary. A second target model was created using traditional segmentation techniques. CT intensity based material properties were assigned to the morphed/mapped model and to the traditionally segmented target models. Models were analyzed to evaluate their geometric concurrency and strain patterns. Strains generated in a double-leg stance configuration were compared to experimental strain gauge data generated from the same target cadaver pelvis. CT landmark-based morphing and mapping techniques were efficiently applied to create a geometrically multifaceted specimen-specific pelvic FE model, which was similar to the traditionally segmented target model and better replicated the experimental strain results (R(2)=0.873). This study has shown that mesh morphing and mapping represents an efficient validated approach for pelvic FE model generation without the need for segmentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Bone graft reconstruction for posterior mandibular segment using the formwork technique].

Science.gov (United States)

Pascual, D; Roig, R; Chossegros, C

2014-04-01

Pre-implant bone graft in posterior mandibular segments is difficult because of masticatory and lingual mechanical constraints, because of the limited bone vascularization, and because of the difficulty to cover it with the mucosa. The formwork technique is especially well adapted to this topography. The recipient site is abraded with a drill. Grooves are created to receive and stabilize the grafts. The bone grafts were harvested from the ramus. The thinned cortices are assembled in a formwork and synthesized by mini-plates. The gaps are filled by bone powder collected during bone harvesting. The bone volume reconstructed with the formwork technique allows anchoring implants more than 8mm long. The proximity of the inferior alveolar nerve does not contra indicate this technique. The formwork size and its positioning on the alveolar crest can be adapted to prosthetic requirements by using osteosynthesis plates. The lateral implant walls are supported by the formwork cortices; the implant apex is anchored on the native alveolar crest. The primary stability of implants is high, and the torque is important. The ramus harvesting decreases operative risks. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Segmenting the Adult Education Market.

Science.gov (United States)

Aurand, Tim

1994-01-01

Describes market segmentation and how the principles of segmentation can be applied to the adult education market. Indicates that applying segmentation techniques to adult education programs results in programs that are educationally and financially satisfying and serve an appropriate population. (JOW)

Energy Conversion and Storage Requirements for Hybrid Electric Aircraft

Science.gov (United States)

Misra, Ajay

2016-01-01

Among various options for reducing greenhouse gases in future large commercial aircraft, hybrid electric option holds significant promise. In the hybrid electric aircraft concept, gas turbine engine is used in combination with an energy storage system to drive the fan that propels the aircraft, with gas turbine engine being used for certain segments of the flight cycle and energy storage system being used for other segments. The paper will provide an overview of various energy conversion and storage options for hybrid electric aircraft. Such options may include fuel cells, batteries, super capacitors, multifunctional structures with energy storage capability, thermoelectric, thermionic or a combination of any of these options. The energy conversion and storage requirements for hybrid electric aircraft will be presented. The role of materials in energy conversion and storage systems for hybrid electric aircraft will be discussed.

Segmental sandwich osteotomy and tunnel technique for three-dimensional reconstruction of the jaw atrophy: a case report.

Science.gov (United States)

Santagata, Mario; Sgaramella, Nicola; Ferrieri, Ivo; Corvo, Giovanni; Tartaro, Gianpaolo; D'Amato, Salvatore

2017-12-01

A three-dimensionally favourable mandibular bone crest is desirable to be able to successfully implant placement to meet the aesthetic and functional criteria in the implant-prosthetic rehabilitation. Several surgical procedures have been advocated for bone augmentation of the atrophic mandible, and the sandwich osteotomy is one of these techniques. The aim of the present case report was to assess the suitability of segmental mandibular sandwich osteotomy combined with a tunnel technique of soft tissue. Based on our knowledge, nobody described before the sandwich osteotomy with tunnel technique to improve the healing of the wound and meet the dimensional requirements of preimplant bone augmentation in cases of a severely atrophic mandible. A 59-year-old woman with a severely atrophied right mandible was treated with the sandwich osteotomy technique filled with autologous bone graft harvested by a cortical bone collector from the ramus. Clinical examination revealed that the mandible was edentulous bilaterally from the first molar to the second molar region. Radiographically, atrophy of the mandibular alveolar ridge in the same teeth site was observed. We began to treat the right side. A horizontal osteotomy of the edentulous mandibular bone was then made with a piezoelectric device after tunnel technique of the soft tissue. The segmental mandibular sandwich osteotomy (SMSO) was finished by two (mesial and distal) slightly divergent vertical osteotomies. The entire bone fragment was displaced cranially, and the desirable position was obtained. The gap was filled completely with autologous bone chips harvested from the mandibular ramus through a cortical bone collector. No barrier membranes were used to protect the grafts. The vertical incisions were closing with interruptive suturing of the flaps with a resorbable material. In this way, the suture will not fall on the osteotomy line of the jaw; the result will be a better predictability of soft and hard tissue

Multifractal-based nuclei segmentation in fish images.

Science.gov (United States)

Reljin, Nikola; Slavkovic-Ilic, Marijeta; Tapia, Coya; Cihoric, Nikola; Stankovic, Srdjan

2017-09-01

The method for nuclei segmentation in fluorescence in-situ hybridization (FISH) images, based on the inverse multifractal analysis (IMFA) is proposed. From the blue channel of the FISH image in RGB format, the matrix of Holder exponents, with one-by-one correspondence with the image pixels, is determined first. The following semi-automatic procedure is proposed: initial nuclei segmentation is performed automatically from the matrix of Holder exponents by applying predefined hard thresholding; then the user evaluates the result and is able to refine the segmentation by changing the threshold, if necessary. After successful nuclei segmentation, the HER2 (human epidermal growth factor receptor 2) scoring can be determined in usual way: by counting red and green dots within segmented nuclei, and finding their ratio. The IMFA segmentation method is tested over 100 clinical cases, evaluated by skilled pathologist. Testing results show that the new method has advantages compared to already reported methods.

An Adaptive Hybrid Multiprocessor technique for bioinformatics sequence alignment

KAUST Repository

Bonny, Talal

2012-07-28

Sequence alignment algorithms such as the Smith-Waterman algorithm are among the most important applications in the development of bioinformatics. Sequence alignment algorithms must process large amounts of data which may take a long time. Here, we introduce our Adaptive Hybrid Multiprocessor technique to accelerate the implementation of the Smith-Waterman algorithm. Our technique utilizes both the graphics processing unit (GPU) and the central processing unit (CPU). It adapts to the implementation according to the number of CPUs given as input by efficiently distributing the workload between the processing units. Using existing resources (GPU and CPU) in an efficient way is a novel approach. The peak performance achieved for the platforms GPU + CPU, GPU + 2CPUs, and GPU + 3CPUs is 10.4 GCUPS, 13.7 GCUPS, and 18.6 GCUPS, respectively (with the query length of 511 amino acid). © 2010 IEEE.

Hybrid platform. Economical hybrid drive for commercial vehicles; Hybrid Plattform. Wirtschaftlicher Hybridantrieb fuer Nutzfahrzeuge

Energy Technology Data Exchange (ETDEWEB)

Wallner, S.; Lamke, M.; Mohr, M.; Sedlacek, M.; Speck, F.D. [ZF Friedrichshafen AG, Friedrichshafen (Germany)

2011-07-01

Up to now, hybrid systems have been adapted to their specific requirements in the various applications for trucks, buses as well as mobile and building machines. From a technical point of view, this does indeed result in optimized hybrid drives for each single vehicle application, but due to small volumes, such single developments are critical from a business point of view. ZF Friedrichshafen AG is providing a solution to the technical and economical requirements of the cost-sensitive CV segment in the form of a modular CV parallel hybrid platform composed of a hybrid module system, an inverter, a battery system, and a hybrid software integrated into the overall vehicle. Thanks to the intelligent combination of assemblies and the use of as many identical parts as possible, platforms are realized which cover power ranges between 60 and 120 kW, voltage ranges between 350 and 650 V, and battery capacities between 2 and 4 kWh. The dimensions of the platform elements are such that integration into the diverse commercial vehicle applications is made easy. The hybrid software required for the vehicle-specific functions is also configurable for the mentioned CV applications. (orig.)

Adaptation of Hybrid FSO/RF Communication System Using Puncturing Technique

Directory of Open Access Journals (Sweden)

M. N. Khan

2016-12-01

Full Text Available Spectrum of radio frequency (RF communications is limited and expensive to install new applications. Free space optical (FSO communication is a viable technology which offers enormous bandwidth, license free installation, inexpensive deployment and error prone links. The FSO links degrade significantly due to the varying atmospheric and weather conditions (fog, cloud, snow, haze and combination of these. We propose a hybrid FSO/RF communication system which adapts the varying nature of atmosphere and weather. For the adaption of varying atmosphere and weather scenarios, we develop a novel optimization algorithm. The proposed algorithm is based on the well-known puncturing technique. We provide an extrinsic information transfer (EXIT chart for the binary and quaternary mapping scheme for the proposed communication system. We simulate the proposed algorithm for the hybrid communication system and analyze the system performance. The proposed algorithm is computationally less expensive and provide better performance gains over varying atmosphere and weather conditions. The algorithm is suitable for fast speed applications.

Saliency U-Net: A regional saliency map-driven hybrid deep learning network for anomaly segmentation

Science.gov (United States)

Karargyros, Alex; Syeda-Mahmood, Tanveer

2018-02-01

Deep learning networks are gaining popularity in many medical image analysis tasks due to their generalized ability to automatically extract relevant features from raw images. However, this can make the learning problem unnecessarily harder requiring network architectures of high complexity. In case of anomaly detection, in particular, there is often sufficient regional difference between the anomaly and the surrounding parenchyma that could be easily highlighted through bottom-up saliency operators. In this paper we propose a new hybrid deep learning network using a combination of raw image and such regional maps to more accurately learn the anomalies using simpler network architectures. Specifically, we modify a deep learning network called U-Net using both the raw and pre-segmented images as input to produce joint encoding (contraction) and expansion paths (decoding) in the U-Net. We present results of successfully delineating subdural and epidural hematomas in brain CT imaging and liver hemangioma in abdominal CT images using such network.

A hybrid Pade-Galerkin technique for differential equations

Science.gov (United States)

Geer, James F.; Andersen, Carl M.

1993-01-01

A three-step hybrid analysis technique, which successively uses the regular perturbation expansion method, the Pade expansion method, and then a Galerkin approximation, is presented and applied to some model boundary value problems. In the first step of the method, the regular perturbation method is used to construct an approximation to the solution in the form of a finite power series in a small parameter epsilon associated with the problem. In the second step of the method, the series approximation obtained in step one is used to construct a Pade approximation in the form of a rational function in the parameter epsilon. In the third step, the various powers of epsilon which appear in the Pade approximation are replaced by new (unknown) parameters (delta(sub j)). These new parameters are determined by requiring that the residual formed by substituting the new approximation into the governing differential equation is orthogonal to each of the perturbation coordinate functions used in step one. The technique is applied to model problems involving ordinary or partial differential equations. In general, the technique appears to provide good approximations to the solution even when the perturbation and Pade approximations fail to do so. The method is discussed and topics for future investigations are indicated.

Structural Interplay - Tuning Mechanics in Peptide-Polyurea Hybrids

Science.gov (United States)

Korley, Lashanda

Utilizing cues from natural materials, we have been inspired to explore the hierarchical arrangement critical to energy absorption and mechanical enhancement in synthetic systems. Of particular interest is the soft domain ordering proposed as a contributing element to the observed toughness in spider silk. Multiblock copolymers, are ideal and dynamic systems in which to explore this approach via variations in secondary structure of nature's building blocks - peptides. We have designed a new class of polyurea hybrids that incorporate peptidic copolymers as the soft segment. The impact of hierarchical ordering on the thermal, mechanical, and morphological behavior of these bio-inspired polyurethanes with a siloxane-based, peptide soft segment was investigated. These peptide-polyurethane/urea hybrids were microphase segregated, and the beta-sheet secondary structure of the soft segment was preserved during polymerization and film casting. Toughness enhancement at low strains was achieved, but the overall extensibility of the peptide-incorporated systems was reduced due to the unique hard domain organization. To decouple the secondary structure influence in the siloxane-peptide soft segment from mechanics dominated by the hard domain, we also developed non-chain extended peptide-polyurea hybrids in which the secondary structure (beta sheet vs. alpha helix) was tuned via choice of peptide and peptide length. It was shown that this structural approach allowed tailoring of extensibility, toughness, and modulus. The sheet-dominant hybrid materials were typically tougher and more elastic due to intermolecular H-bonding facilitating load distribution, while the helical-prevalent systems generally exhibited higher stiffness. Recently, we have explored the impact of a molecular design strategy that overlays a covalent and physically crosslinked architecture in these peptide-polyurea hybrids, demonstrating that physical constraints in the network hybrids influences peptide

[The technique of hearing reconstruction in the cases of conductive hearing loss with malformed tympanic segment of facial nerve].

Science.gov (United States)

Yang, Feng; Song, Rendong; Liu, Yang

2016-02-02

To explore the technique of hearing reconstruction in the cases of conductive hearing loss with malformed tympanic segment of facial nerve. Data of 10 cases from July 2010 to March 2015 were collected.The status of tympanic segment of facial nerve, malformed ossicles and the reconstructed methods of ossicular chain were analyzed and discussed based on the embryo anatomy and surgical technique. All facial nerves in 10 cases were exposed and drooping to stapes or cover the oval window.Three patients who had normal stapes, pushed by the exposed facial nerve, were reconstructed with partial ossicular replacement prostheses (PORP). Two patients who had footplate, with partial fixation, were reconstructed with total ossicular replacement prostheses (TORP). Three patients who had atresia of the oval window were implanted with Piston after being made hole in the atresia plate.Another two cases who had atresia of the oval window were implanted with TORP after promontory being drilled out.All cases had no injury of facial nerve and nervous hearing, and no tinnitus.Nine cases had conductive hearing improvement, except one with promontory drilled out. Patients who had conductive hearing loss with malformed tympanic segment of facial nerve can be treated by the technique of hearing reconstruction.The fenestration technique in the bottom of the scala tympani of the basal turn provides us a new method for treating patients whose oval window was fully covered by malformed facial nerve.

Anatomic and Pathologic Variability During Radiotherapy for a Hybrid Active Breath-Hold Gating Technique

International Nuclear Information System (INIS)

Glide-Hurst, Carri K.; Gopan, Ellen; Hugo, Geoffrey D.

2010-01-01

Purpose: To evaluate intra- and interfraction variability of tumor and lung volume and position using a hybrid active breath-hold gating technique. Methods and Materials: A total of 159 repeat normal inspiration active breath-hold CTs were acquired weekly during radiotherapy for 9 lung cancer patients (12-21 scans per patient). A physician delineated the gross tumor volume (GTV), lungs, and spinal cord on the first breath-hold CT, and contours were propagated semiautomatically. Intra- and interfraction variability of tumor and lung position and volume were evaluated. Tumor centroid and border variability were quantified. Results: On average, intrafraction variability of lung and GTV centroid position was 0.1). Increases in free-breathing tidal volume were associated with increases in breath-hold ipsilateral lung volume (p < 0.05). Conclusions: The breath-hold technique was reproducible within 2 mm during each fraction. Interfraction variability of GTV position and shape was substantial because of tumor volume and breath-hold lung volume change during therapy. These results support the feasibility of a hybrid breath-hold gating technique and suggest that online image guidance would be beneficial.

ProTaper rotary instrument fracture during root canal preparation: a comparison between rotary and hybrid techniques.

Science.gov (United States)

Farid, Huma; Khan, Farhan Raza; Rahman, Munawar

2013-03-01

This study aimed to compare the frequency of ProTaper rotary instrument fracture with rotary (conventional) and hybrid (rotary and hand files) canal preparation techniques. Secondary objectives were to determine whether there was an association of ProTaper file fracture with the canal curvature and to compare the mean time required for canal preparation in the two techniques. An in vitro experiment was conducted on 216 buccal canals of extracted maxillary and mandibular first molars. After creating an access cavity and a glide path for each canal, a periapical radiograph was taken and the canal curvature was measured with Schneider's technique. The canals were then randomly divided into Group A (rotary technique) and Group B (hybrid technique). The length of ProTaper files were measured before and after each canal preparation. Time taken for each canal preparation was recorded. A total of seven ProTaper files fractured in Group A (P=0.014) in canals with a curvature >25 degrees (PProTaper rotary files, although time consuming, was safer in canals having a curvature greater than 25 degrees.

Ultrafast superpixel segmentation of large 3D medical datasets

Science.gov (United States)

Leblond, Antoine; Kauffmann, Claude

2016-03-01

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

Distance measures for image segmentation evaluation

OpenAIRE

Monteiro, Fernando C.; Campilho, Aurélio

2012-01-01

In this paper we present a study of evaluation measures that enable the quantification of the quality of an image segmentation result. Despite significant advances in image segmentation techniques, evaluation of these techniques thus far has been largely subjective. Typically, the effectiveness of a new algorithm is demonstrated only by the presentation of a few segmented images and is otherwise left to subjective evaluation by the reader. Such an evaluation criterion can be useful for differ...

Accuracy and reproducibility of a novel semi-automatic segmentation technique for MR volumetry of the pituitary gland

International Nuclear Information System (INIS)

Renz, Diane M.; Hahn, Horst K.; Rexilius, Jan; Schmidt, Peter; Lentschig, Markus; Pfeil, Alexander; Sauner, Dieter; Fitzek, Clemens; Mentzel, Hans-Joachim; Kaiser, Werner A.; Reichenbach, Juergen R.; Boettcher, Joachim

2011-01-01

Although several reports about volumetric determination of the pituitary gland exist, volumetries have been solely performed by indirect measurements or manual tracing on the gland's boundaries. The purpose of this study was to evaluate the accuracy and reproducibility of a novel semi-automatic MR-based segmentation technique. In an initial technical investigation, T1-weighted 3D native magnetised prepared rapid gradient echo sequences (1.5 T) with 1 mm isotropic voxel size achieved high reliability and were utilised in different in vitro and in vivo studies. The computer-assisted segmentation technique was based on an interactive watershed transform after resampling and gradient computation. Volumetry was performed by three observers with different software and neuroradiologic experiences, evaluating phantoms of known volume (0.3, 0.9 and 1.62 ml) and healthy subjects (26 to 38 years; overall 135 volumetries). High accuracy of the volumetry was shown by phantom analysis; measurement errors were 0.05). The analysed semi-automatic MR volumetry of the pituitary gland is a valid, reliable and fast technique. Possible clinical applications are hyperplasia or atrophy of the gland in pathological circumstances either by a single assessment or by monitoring in follow-up studies. (orig.)

Structured oligonucleotides for target indexing to allow single-vessel PCR amplification and solid support microarray hybridization.

Science.gov (United States)

Girard, Laurie D; Boissinot, Karel; Peytavi, Régis; Boissinot, Maurice; Bergeron, Michel G

2015-02-07

The combination of molecular diagnostic technologies is increasingly used to overcome limitations on sensitivity, specificity or multiplexing capabilities, and provide efficient lab-on-chip devices. Two such techniques, PCR amplification and microarray hybridization are used serially to take advantage of the high sensitivity and specificity of the former combined with high multiplexing capacities of the latter. These methods are usually performed in different buffers and reaction chambers. However, these elaborate methods have high complexity and cost related to reagent requirements, liquid storage and the number of reaction chambers to integrate into automated devices. Furthermore, microarray hybridizations have a sequence dependent efficiency not always predictable. In this work, we have developed the concept of a structured oligonucleotide probe which is activated by cleavage from polymerase exonuclease activity. This technology is called SCISSOHR for Structured Cleavage Induced Single-Stranded Oligonucleotide Hybridization Reaction. The SCISSOHR probes enable indexing the target sequence to a tag sequence. The SCISSOHR technology also allows the combination of nucleic acid amplification and microarray hybridization in a single vessel in presence of the PCR buffer only. The SCISSOHR technology uses an amplification probe that is irreversibly modified in presence of the target, releasing a single-stranded DNA tag for microarray hybridization. Each tag is composed of a 3-nucleotide sequence-dependent segment and a unique "target sequence-independent" 14-nucleotide segment allowing for optimal hybridization with minimal cross-hybridization. We evaluated the performance of five (5) PCR buffers to support microarray hybridization, compared to a conventional hybridization buffer. Finally, as a proof of concept, we developed a multiplexed assay for the amplification, detection, and identification of three (3) DNA targets. This new technology will facilitate the design

Fabrication of ridge waveguide structure from photosensitive TiO2/ormosil hybrid films by using an ultraviolet soft imprint technique

International Nuclear Information System (INIS)

Zhang, Xuehua; Que, Wenxiu; Chen, Jing; Gao, Tianxi; Hu, Jiaxing; Liu, Weiguo

2013-01-01

Photosensitive TiO 2 /organically modified silane hybrid films were prepared by combining a low-temperature sol–gel process with a spin-coating technique. Optical properties and photochemical activities of the as-prepared hybrid sol–gel films under different UV irradiation time were characterized and monitored by prism coupling technique, UV–visible spectroscopy, and Fourier transform infrared spectroscopy. Surface morphology of the hybrid films was also observed by an atomic force microscopy. Advantages for fabrication of ridge waveguide structure based on the photosensitive hybrid films were demonstrated by an ultraviolet soft imprint technique. Effects of imprint force, imprint time, and UV irradiation time on high replication fidelity of the ridge waveguide structure were also investigated. An altitude replication fidelity of 99.7% can be obtained when the imprint force of 2 MPa, imprint time of 30 min and UV irradiation time of 45 min were chosen. Scanning electron microscopy and surface profiler were used to characterize the morphological and surface profile properties of the as fabricated ridge waveguide structure. Results indicate that the as-prepared photosensitive hybrid materials have great applicability for the fabrication of micro-optical elements and advantage as the imprint layer under the ultraviolet soft imprint technique. - Highlights: ► Photosensitive TiO 2 /ormosil hybrid film is prepared by a sol–gel process. ► Optical properties of the films change a little with UV exposure time. ► Photo-chemical property of the film changes a lot with UV exposure time. ► The imprint force and time, and the UV exposure time affect the imprint fidelity. ► A fidelity value of 99.7% is obtained under an optimized condition

Heart dose reduction in breast cancer treatment with simultaneous integrated boost. Comparison of treatment planning and dosimetry for a novel hybrid technique and 3D-CRT

International Nuclear Information System (INIS)

Joest, Vincent; Kretschmer, Matthias; Sabatino, Marcello; Wuerschmidt, Florian; Dahle, Joerg; Lorenzen, Joern; Ueberle, Friedrich

2015-01-01

The present study compares in silico treatment plans of clinically established three-dimensional conformal radiotherapy (3D-CRT) with a hybrid technique consisting of intensity-modulated radiotherapy (IMRT) and volumetric modulated arc radiotherapy (VMAT) during normally fractionated radiation of mammary carcinomas with simultaneous integrated boost on the basis of dose-volume histogram (DVH) parameters. Radiation treatment planning was performed with a hybrid and a 3D-CRT treatment plan for 20 patients. Hybrid plans were implemented with two tangential IMRT fields and a VMAT field in the angular range of the tangents. Verification of the plan was performed with a manufacturer-independent measurement system consisting of a detector array and rotation unit. The mean values of the heart dose for the entire patient collective were 3.6 ± 2.5 Gy for 3D-CRT and 2.9 ± 2.1 Gy for the hybrid technique (p < 0.01). For the left side (n = 10), the mean values for the left anterior descending artery were 21.8 ± 7.4 Gy for 3D-CRT and 17.6 ± 7.4 Gy for the hybrid technique (p < 0.01). The mean values of the ipsilateral lung were 11.9 ± 1.6 Gy for 3D-CRT and 10.5 ± 1.3 Gy for the hybrid technique (p < 0.01). Calculated dose distributions in the hybrid arm were in good accordance with measured dose (on average 95.6 ± 0.5 % for γ < 1 and 3 %/3 mm). The difference of the mean treatment time per fraction was 7 s in favor of 3D-CRT. Compared with the established 3D-CRT technique, the hybrid technique allows for a decrease in dose, particularly of the mean heart and lung dose with comparable target volume acquisition and without disadvantageous low-dose load of contralateral structures. Uncomplicated implementation of the hybrid technique was demonstrated in this context. The hybrid technique combines the advantages of tangential IMRT with the superior sparing of organs at risk by VMAT. (orig.) [de

A new framework for interactive images segmentation

International Nuclear Information System (INIS)

Ashraf, M.; Sarim, M.; Shaikh, A.B.

2017-01-01

Image segmentation has become a widely studied research problem in image processing. There exist different graph based solutions for interactive image segmentation but the domain of image segmentation still needs persistent improvements. The segmentation quality of existing techniques generally depends on the manual input provided in beginning, therefore, these algorithms may not produce quality segmentation with initial seed labels provided by a novice user. In this work we investigated the use of cellular automata in image segmentation and proposed a new algorithm that follows a cellular automaton in label propagation. It incorporates both the pixel's local and global information in the segmentation process. We introduced the novel global constraints in automata evolution rules; hence proposed scheme of automata evolution is more effective than the automata based earlier evolution schemes. Global constraints are also effective in deceasing the sensitivity towards small changes made in manual input; therefore proposed approach is less dependent on label seed marks. It can produce the quality segmentation with modest user efforts. Segmentation results indicate that the proposed algorithm performs better than the earlier segmentation techniques. (author)

COMPARISON OF DIFFERENT SEGMENTATION ALGORITHMS FOR DERMOSCOPIC IMAGES

Directory of Open Access Journals (Sweden)

A.A. Haseena Thasneem

2015-05-01

Full Text Available This paper compares different algorithms for the segmentation of skin lesions in dermoscopic images. The basic segmentation algorithms compared are Thresholding techniques (Global and Adaptive, Region based techniques (K-means, Fuzzy C means, Expectation Maximization and Statistical Region Merging, Contour models (Active Contour Model and Chan - Vese Model and Spectral Clustering. Accuracy, sensitivity, specificity, Border error, Hammoude distance, Hausdorff distance, MSE, PSNR and elapsed time metrices were used to evaluate various segmentation techniques.

Simplified Model Surgery Technique for Segmental Maxillary Surgeries

Directory of Open Access Journals (Sweden)

Namit Nagar

2011-01-01

Full Text Available Model surgery is the dental cast version of cephalometric prediction of surgical results. Patients having vertical maxillary excess with prognathism invariably require Lefort I osteotomy with maxillary segmentation and maxillary first premolar extractions during surgery. Traditionally, model surgeries in these cases have been done by sawing the model through the first premolar interproximal area and removing that segment. This clinical innovation employed the use of X-ray film strips as separators in maxillary first premolar interproximal area. The method advocated is a time-saving procedure where no special clinical or laboratory tools, such as plaster saw (with accompanying plaster dust, were required and reusable separators were made from old and discarded X-ray films.

Ranked retrieval of segmented nuclei for objective assessment of cancer gene repositioning

Directory of Open Access Journals (Sweden)

Cukierski William J

2012-09-01

Full Text Available Abstract Background Correct segmentation is critical to many applications within automated microscopy image analysis. Despite the availability of advanced segmentation algorithms, variations in cell morphology, sample preparation, and acquisition settings often lead to segmentation errors. This manuscript introduces a ranked-retrieval approach using logistic regression to automate selection of accurately segmented nuclei from a set of candidate segmentations. The methodology is validated on an application of spatial gene repositioning in breast cancer cell nuclei. Gene repositioning is analyzed in patient tissue sections by labeling sequences with fluorescence in situ hybridization (FISH, followed by measurement of the relative position of each gene from the nuclear center to the nuclear periphery. This technique requires hundreds of well-segmented nuclei per sample to achieve statistical significance. Although the tissue samples in this study contain a surplus of available nuclei, automatic identification of the well-segmented subset remains a challenging task. Results Logistic regression was applied to features extracted from candidate segmented nuclei, including nuclear shape, texture, context, and gene copy number, in order to rank objects according to the likelihood of being an accurately segmented nucleus. The method was demonstrated on a tissue microarray dataset of 43 breast cancer patients, comprising approximately 40,000 imaged nuclei in which the HES5 and FRA2 genes were labeled with FISH probes. Three trained reviewers independently classified nuclei into three classes of segmentation accuracy. In man vs. machine studies, the automated method outperformed the inter-observer agreement between reviewers, as measured by area under the receiver operating characteristic (ROC curve. Robustness of gene position measurements to boundary inaccuracies was demonstrated by comparing 1086 manually and automatically segmented nuclei. Pearson

Accounting for segment correlations in segmented gamma-ray scans

International Nuclear Information System (INIS)

Sheppard, G.A.; Prettyman, T.H.; Piquette, E.C.

1994-01-01

In a typical segmented gamma-ray scanner (SGS), the detector's field of view is collimated so that a complete horizontal slice or segment of the desired thickness is visible. Ordinarily, the collimator is not deep enough to exclude gamma rays emitted from sample volumes above and below the segment aligned with the collimator. This can lead to assay biases, particularly for certain radioactive-material distributions. Another consequence of the collimator's low aspect ratio is that segment assays at the top and bottom of the sample are biased low because the detector's field of view is not filled. This effect is ordinarily countered by placing the sample on a low-Z pedestal and scanning one or more segment thicknesses below and above the sample. This takes extra time, however, We have investigated a number of techniques that both account for correlated segments and correct for end effects in SGS assays. Also, we have developed an algorithm that facilitates estimates of assay precision. Six calculation methods have been compared by evaluating the results of thousands of simulated, assays for three types of gamma-ray source distribution and ten masses. We will report on these computational studies and their experimental verification

Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.

Science.gov (United States)

Banik, Shipra; Khodadad Khan, A F M; Anwer, Mohammad

2014-01-01

Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange.

Novel hybrid (magnet plus curve grasper) technique during transumbilical cholecystectomy: initial experience of a promising approach.

Science.gov (United States)

Millan, Carolina; Bignon, Horacion; Bellia, Gaston; Buela, Enrique; Rabinovich, Fernando; Albertal, Mariano; Martinez Ferro, Marcelo

2013-10-01

The use of magnets in transumbilical cholecystectomy (TUC) improves triangulation and achieves an optimal critical view. Nonetheless, the tendency of the magnets to collide hinders the process. In order to simplify the surgical technique, we developed a hybrid model with a single magnet and a curved grasper. All TUCs performed with a hybrid strategy in our pediatric population between September 2009 and July 2012 were retrospectively reviewed. Of 260 surgical procedures in which at least one magnet was used, 87 were TUCs. Of those, 62 were hybrid: 33 in adults and 29 in pediatric patients. The technique combines a magnet and a curved grasper. Through a transumbilical incision, we placed a 12-mm trocar and another flexible 5-mm trocar. The laparoscope with the working channel used the 12-mm trocar. The magnetic grasper was introduced to the abdominal cavity using the working channel to provide cephalic retraction of the gallbladder fundus. Across the flexible trocar, the assistant manipulated the curved grasper to mobilize the infundibulum. The surgeon operated through the working channel of the laparoscope. In this pediatric population, the mean age was 14 years (range, 4-17 years), and mean weight was 50 kg (range, 18-90 kg); 65% were girls. Mean operative time was 62 minutes. All procedures achieved a critical view of safety with no instrumental collision. There were no intraoperative or postoperative complications. The hospital stay was 1.4±0.6 days, and the median follow-up was 201 days. A hybrid technique, combining magnets and a curved grasper, simplifies transumbilical surgery. It seems feasible and safe for TUC and potentially reproducible.

ADVANCED CLUSTER BASED IMAGE SEGMENTATION

Directory of Open Access Journals (Sweden)

D. Kesavaraja

2011-11-01

Full Text Available This paper presents efficient and portable implementations of a useful image segmentation technique which makes use of the faster and a variant of the conventional connected components algorithm which we call parallel Components. In the Modern world majority of the doctors are need image segmentation as the service for various purposes and also they expect this system is run faster and secure. Usually Image segmentation Algorithms are not working faster. In spite of several ongoing researches in Conventional Segmentation and its Algorithms might not be able to run faster. So we propose a cluster computing environment for parallel image Segmentation to provide faster result. This paper is the real time implementation of Distributed Image Segmentation in Clustering of Nodes. We demonstrate the effectiveness and feasibility of our method on a set of Medical CT Scan Images. Our general framework is a single address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient cluster process which uses a novel approach for parallel merging. Our experimental results are consistent with the theoretical analysis and practical results. It provides the faster execution time for segmentation, when compared with Conventional method. Our test data is different CT scan images from the Medical database. More efficient implementations of Image Segmentation will likely result in even faster execution times.

Surgical technique for en bloc transurethral resection of bladder tumour with a Hybrid Knife(®).

Science.gov (United States)

Islas-García, J J O; Campos-Salcedo, J G; López-Benjume, B I; Torres-Gómez, J J; Aguilar-Colmenero, J; Martínez-Alonso, I A; Gil-Villa, S A

2016-05-01

Bladder cancer is the second most common malignancy of the urinary tract and the 9th worldwide. Latin American has an incidence of 5.6 per 100,000 inhabitants per year. Seventy-five percent of newly diagnosed cases are nonmuscle invasive bladder cancer, and 25% of cases present as muscle invasive. The mainstay of treatment for nonmuscle invasive bladder cancer is loop transurethral resection. In 2013, the group led by Dr Mundhenk of the University Hospital of Tübingen, Germany, was the first to describe the Hybrid Knife(®) equipment for performing en bloc bladder tumour resection, with favourable functional and oncological results. To describe the surgical technique of en bloc bladder tumour resection with a Hybrid Knife(®) as an alternative treatment for nonmuscle invasive bladder tumours. A male patient was diagnosed by urotomography and urethrocystoscopy with a bladder tumour measuring 2×1cm on the floor. En bloc transurethral resection of the bladder tumour was performed with a Hybrid Knife(®). Surgery was performed for 35min, with 70 watts for cutting and 50 watts for coagulation, resecting and evacuating en bloc the bladder tumour, which macroscopically included the muscle layer of the bladder. There were no complications. The technique of en bloc bladder tumour resection with Hybrid Knife(®) is an effective alternative to bipolar loop transurethral resection. Resection with a Hybrid Knife(®) is a procedure with little bleeding and good surgical vision and minimises the risk of bladder perforation and tumour implants. The procedure facilitates determining the positivity of the neoplastic process, vascular infiltration and bladder muscle invasion in the histopathology study. Copyright © 2015 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Joint shape segmentation with linear programming

KAUST Repository

Huang, Qixing

2011-01-01

We present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. © 2011 ACM.

The Metal-Zirconia Implant Fixed Hybrid Full-Arch Prosthesis: An Alternative Technique for Fabrication.

Science.gov (United States)

Stumpel, Lambert J; Haechler, Walter

2018-03-01

The metal-resin hybrid full-arch prosthesis has been a traditionally used type of restoration for full-arch implant fixed dentures. A newer development has centered around the use of monolithic zirconia or zirconia veneered with porcelain. Being a ceramic, zirconia has the potential for fracture. This article describes a technique that utilizes a metal substructure to support a chemically and mechanically resinbonded shell of zirconia. The workflow is discussed, ranging from in-office master cast fabrication to the CAD/ CAM production of the provisional and the definitive metal-zirconia prosthesis. The article also highlights the advantages and disadvantages of various materials used for hybrid prostheses.

Solving Linear Equations by Classical Jacobi-SR Based Hybrid Evolutionary Algorithm with Uniform Adaptation Technique

OpenAIRE

Jamali, R. M. Jalal Uddin; Hashem, M. M. A.; Hasan, M. Mahfuz; Rahman, Md. Bazlar

2013-01-01

Solving a set of simultaneous linear equations is probably the most important topic in numerical methods. For solving linear equations, iterative methods are preferred over the direct methods especially when the coefficient matrix is sparse. The rate of convergence of iteration method is increased by using Successive Relaxation (SR) technique. But SR technique is very much sensitive to relaxation factor, {\\omega}. Recently, hybridization of classical Gauss-Seidel based successive relaxation t...

All Internal Segmental Bone Transport and Optional Lengthening With a Newly Developed Universal Cylinder-Kombi-Tube Module for Motorized Nails-Description of a Surgical Technique.

Science.gov (United States)

Krettek, Christian; El Naga, Ashraf

2017-10-01

Segmental transport is an effective method of treatment for segmental defects, but the need for external fixation during the transport phase is a disadvantage. To avoid external fixation, we have developed a Cylinder-Kombi-Tube Segmental Transport (CKTST) module for combination with a commercially available motorized lengthening nail. This CKTST module allows for an all-internal segmental bone transport and also allows for optional lengthening if needed. The concept and surgical technique of CKTST are described and illustrated with a clinical case.

Genome reorganization in Nicotiana asymmetric somatic hybrids analysed by in situ hybridization

International Nuclear Information System (INIS)

Parokonny, A.S.; Kenton, A.Y.; Gleba, Y.Y.; Bennett, M.D.

1992-01-01

In situ hybridization was used to examine genome reorganization in asymmetric somatic hybrids between Nicotiana plumbaginifolia and Nicotiana sylvestris obtained by fusion of gamma-irradiated protoplasts from one of the parents (donor) with non-irradiated protoplasts from the other (recipient). Probing with biotinylated total genomic DNA from either the donor or the recipient species unequivocally identified genetic material from both parents in 31 regenerant plants, each originating from a different nuclear hybrid colony. This method, termed genomic in situ hybridization (GISH), allowed intergenomic translocations containing chromosome segments from both species to be recognized in four regenerants. A probe homologous to the consensus sequence of the Arabidopsis thaliana telomeric repeat (5'-TTTAGGG-3')n, identified telomeres on all chromosomes, including 'mini-chromosomes' originating from the irradiated donor genome. Genomic in situ hybridization to plant chromosomes provides a rapid and reliable means of screening for recombinant genotypes in asymmetric somatic hybrids. Used in combination with other DNA probes, it also contributes to a greater understanding of the events responsible for genomic recovery and restabilization following genetic manipulation in vitro

Efficacy and safety of Hybrid-APC for the ablation of Barrett's esophagus.

Science.gov (United States)

Manner, Hendrik; May, Andrea; Kouti, Ioanna; Pech, Oliver; Vieth, Michael; Ell, Christian

2016-04-01

After thermal ablation of Barrett's esophagus (BE), stricture formation is reported in 5 to over 10% of patients. The question arises whether submucosal fluid injection prior to ablation may lower the risk of stricture formation. The aim of the present study was to evaluate the efficacy and safety of the new technique of Hybrid-APC which combines submucosal injection with APC. Patients who had a residual BE segment of at least 1 cm after endoscopic resection of early Barrett's neoplasia underwent thermal ablation of BE by Hybrid-APC. Prior to thermal ablation, submucosal injection of sodium chloride 0.9% was carried out using a flexible water-jet probe (Erbejet 2; Erbe Elektromedizin, Tuebingen, Germany). Check-up upper GI endoscopy was carried out 3 months after macroscopically complete ablation including biopsies from the neo-Z-line and the former BE segment, and recording of stricture formation. From May 2011 to November 2012, a total of 60 patients (pt) were included in the study [55 pt male (92%); mean age 62 ± 9 years, range 42-79]. Ten patients were excluded from the study. In the remaining 50 pt, Hybrid-APC ablation and check-up endoscopy at 3 months were carried out. Forty-eight out of 50 pt (96%; ITT: 49/60, 82%) achieved macroscopically complete remission after a median of 3.5 APC sessions [SD 2.4; range 1-10]. Freedom from BE was histopathologically observed in 39/50 patients (78%). There was one treatment-related stricture (2%). Minor adverse events of Hybrid-APC were observed in 11 patients (22%). According to this pilot series, Hybrid-APC was effective and safe for BE ablation in a tertiary referral center. The rate of stricture formation was only 2%. Further studies are required to confirm the present results. DRKS00003369.

Detection of DNA hybridizations using solid-state nanopores

International Nuclear Information System (INIS)

Balagurusamy, Venkat S K; Weinger, Paul; Sean Ling, Xinsheng

2010-01-01

We report an experimental study of using DNA translocation through solid-state nanopores to detect the sequential arrangement of two double-stranded 12-mer hybridization segments on a single-stranded DNA molecule. The sample DNA is a trimer molecule formed by hybridizing three single-stranded oligonucleotides. A polystyrene bead is attached to the end of the trimer DNA, providing a mechanism in slowing down the translocation and suppressing the thermal diffusion, thereby allowing the detection of short features of DNA by standard patch-clamp electronics. The electrical signature of the translocation of a trimer molecule through a nanopore has been identified successfully in the temporal traces of ionic current. The results reported here represent the first successful attempt in using a solid-state nanopore as an ionic scanning device in resolving individual hybridization segments (or 'probes') on a DNA molecule.

Detection of DNA hybridizations using solid-state nanopores

Energy Technology Data Exchange (ETDEWEB)

Balagurusamy, Venkat S K; Weinger, Paul; Sean Ling, Xinsheng, E-mail: Xinsheng_Ling@brown.edu [Department of Physics, Brown University, Providence, RI 02912 (United States)

2010-08-20

We report an experimental study of using DNA translocation through solid-state nanopores to detect the sequential arrangement of two double-stranded 12-mer hybridization segments on a single-stranded DNA molecule. The sample DNA is a trimer molecule formed by hybridizing three single-stranded oligonucleotides. A polystyrene bead is attached to the end of the trimer DNA, providing a mechanism in slowing down the translocation and suppressing the thermal diffusion, thereby allowing the detection of short features of DNA by standard patch-clamp electronics. The electrical signature of the translocation of a trimer molecule through a nanopore has been identified successfully in the temporal traces of ionic current. The results reported here represent the first successful attempt in using a solid-state nanopore as an ionic scanning device in resolving individual hybridization segments (or 'probes') on a DNA molecule.

Fabrication of ridge waveguide structure from photosensitive TiO{sub 2}/ormosil hybrid films by using an ultraviolet soft imprint technique

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xuehua [Electronic Materials Research Laboratory, International Center for Dielectric Research, Xi' an Jiaotong University, Xi' an 710049, Shaanxi (China); Que, Wenxiu, E-mail: wxque@mail.xjtu.edu.cn [Electronic Materials Research Laboratory, International Center for Dielectric Research, Xi' an Jiaotong University, Xi' an 710049, Shaanxi (China); Chen, Jing; Gao, Tianxi; Hu, Jiaxing [Electronic Materials Research Laboratory, International Center for Dielectric Research, Xi' an Jiaotong University, Xi' an 710049, Shaanxi (China); Liu, Weiguo [Micro-optoelectronic Systems Laboratories, Xi' an Technological University, Xi' an 710032, Shaanxi (China)

2013-03-01

Photosensitive TiO{sub 2}/organically modified silane hybrid films were prepared by combining a low-temperature sol–gel process with a spin-coating technique. Optical properties and photochemical activities of the as-prepared hybrid sol–gel films under different UV irradiation time were characterized and monitored by prism coupling technique, UV–visible spectroscopy, and Fourier transform infrared spectroscopy. Surface morphology of the hybrid films was also observed by an atomic force microscopy. Advantages for fabrication of ridge waveguide structure based on the photosensitive hybrid films were demonstrated by an ultraviolet soft imprint technique. Effects of imprint force, imprint time, and UV irradiation time on high replication fidelity of the ridge waveguide structure were also investigated. An altitude replication fidelity of 99.7% can be obtained when the imprint force of 2 MPa, imprint time of 30 min and UV irradiation time of 45 min were chosen. Scanning electron microscopy and surface profiler were used to characterize the morphological and surface profile properties of the as fabricated ridge waveguide structure. Results indicate that the as-prepared photosensitive hybrid materials have great applicability for the fabrication of micro-optical elements and advantage as the imprint layer under the ultraviolet soft imprint technique. - Highlights: ► Photosensitive TiO{sub 2}/ormosil hybrid film is prepared by a sol–gel process. ► Optical properties of the films change a little with UV exposure time. ► Photo-chemical property of the film changes a lot with UV exposure time. ► The imprint force and time, and the UV exposure time affect the imprint fidelity. ► A fidelity value of 99.7% is obtained under an optimized condition.

An objective evaluation framework for segmentation techniques of functional positron emission tomography studies

CERN Document Server

Kim, J; Eberl, S; Feng, D

2004-01-01

Segmentation of multi-dimensional functional positron emission tomography (PET) studies into regions of interest (ROI) exhibiting similar temporal behavior is useful in diagnosis and evaluation of neurological images. Quantitative evaluation plays a crucial role in measuring the segmentation algorithm's performance. Due to the lack of "ground truth" available for evaluating segmentation of clinical images, automated segmentation results are usually compared with manual delineation of structures which is, however, subjective, and is difficult to perform. Alternatively, segmentation of co-registered anatomical images such as magnetic resonance imaging (MRI) can be used as the ground truth to the PET segmentation. However, this is limited to PET studies which have corresponding MRI. In this study, we introduce a framework for the objective and quantitative evaluation of functional PET study segmentation without the need for manual delineation or registration to anatomical images of the patient. The segmentation ...

Continuation of Sets of Constrained Orbit Segments

DEFF Research Database (Denmark)

Schilder, Frank; Brøns, Morten; Chamoun, George Chaouki

Sets of constrained orbit segments of time continuous flows are collections of trajectories that represent a whole or parts of an invariant set. A non-trivial but simple example is a homoclinic orbit. A typical representation of this set consists of an equilibrium point of the flow and a trajectory...... that starts close and returns close to this fixed point within finite time. More complicated examples are hybrid periodic orbits of piecewise smooth systems or quasi-periodic invariant tori. Even though it is possible to define generalised two-point boundary value problems for computing sets of constrained...... orbit segments, this is very disadvantageous in practice. In this talk we will present an algorithm that allows the efficient continuation of sets of constrained orbit segments together with the solution of the full variational problem....

Genetic relatedness of orbiviruses by RNA-RNA blot hybridization

International Nuclear Information System (INIS)

Bodkin, D.K.

1985-01-01

RNA-RNA blot hybridization was developed in order to identify type-specific genes among double-stranded (ds) RNA viruses, to assess the genetic relatedness of dsRNA viruses and to classify new strains. Viral dsRNA segments were electrophoresed through 10% polyacrylamide gels, transferred to membranes, and hybridized to [5' 32 P]-pCp labeled genomic RNA from a related strain. Hybridization was performed at 52 0 C, 50% formamide, 5X SSC. Under these conditions heterologous RNA species must share ≥ 74% sequence homology in order to form stable dsRNA hybrids. Cognate genes of nine members of the Palyam serogroup of orbiviruses were identified and their sequence relatedness to the prototype. Palyam virus, was determined. Reciprocal blot hybridizations were performed using radiolabeled genomic RNA of all members of the Palyam serogroup. Unique and variant genes were identified by lack of cross-homology or by weak homology between segments. Since genes 2 and 6 exhibited the highest degree of sequence variability, response to the vertebrate immune system may be a major cause of sequence divergence among members of a single serogroup. Changuinola serogroup isolates were compared by dot-blot hybridization, while Colorado tick fever (CTF) serogroup isolates were compared by the RNA-RNA blot hybridization procedure described for reovirus and Palyam serogroup isolates. Preliminary blot hybridization data were also obtained on the relatedness of members of different Orbivirus serogroups

Innovative hybrid pile oscillator technique in the Minerve reactor: open loop vs. closed loop

Science.gov (United States)

Geslot, Benoit; Gruel, Adrien; Bréaud, Stéphane; Leconte, Pierre; Blaise, Patrick

2018-01-01

Pile oscillator techniques are powerful methods to measure small reactivity worth of isotopes of interest for nuclear data improvement. This kind of experiments has long been implemented in the Mineve experimental reactor, operated by CEA Cadarache. A hybrid technique, mixing reactivity worth estimation and measurement of small changes around test samples is presented here. It was made possible after the development of high sensitivity miniature fission chambers introduced next to the irradiation channel. A test campaign, called MAESTRO-SL, took place in 2015. Its objective was to assess the feasibility of the hybrid method and investigate the possibility to separate mixed neutron effects, such as fission/capture or scattering/capture. Experimental results are presented and discussed in this paper, which focus on comparing two measurements setups, one using a power control system (closed loop) and another one where the power is free to drift (open loop). First, it is demonstrated that open loop is equivalent to closed loop. Uncertainty management and methods reproducibility are discussed. Second, results show that measuring the flux depression around oscillated samples provides valuable information regarding partial neutron cross sections. The technique is found to be very sensitive to the capture cross section at the expense of scattering, making it very useful to measure small capture effects of highly scattering samples.

A double labeling technique for performing immunocytochemistry and in situ hybridization in virus infected cell cultures and tissues

International Nuclear Information System (INIS)

Gendelman, H.E.; Moench, T.R.; Narayan, O.; Griffin, D.E.; Clements, J.E.

1985-01-01

This report describes a combined immunocytochemical and in situ hybridization procedure which allows visualization of cellular or viral antigens and viral RNA in the same cell. Cultures infected with visna or measles virus were fixed in periodate-lysine-paraformaldehyde-glutaraldehyde, stained by the avidin-biotin-peroxidase technique using antibodies to viral or cellular proteins and then incubated with radiolabeled specific DNA probes (in situ hybridization). This technique provides a new approach to the study of viral pathogenesis by: (1) identifying the types of cells which are infected in the host and (2) identifying points of blockade in the virus life cycle during persistent infections. (Auth.)

Market Segmentation: An Instructional Module.

Science.gov (United States)

Wright, Peter H.

A concept-based introduction to market segmentation is provided in this instructional module for undergraduate and graduate transportation-related courses. The material can be used in many disciplines including engineering, business, marketing, and technology. The concept of market segmentation is primarily a transportation planning technique by…

Radiation hybrids from human chromosome 3: A basis for the construction of region and specific sublibraries

International Nuclear Information System (INIS)

Atchison, L.; Cosmis, R.L.; Atchison, M.L.

1990-01-01

The authors are interested in identifying genes on human chromosome involved in disease processes. To date at least 20 different loci on this chromosome are implicated with various disease states. DNA libraries containing clones derived from a small chromosomal subregion implicated in a particular disease would greatly assist these studies. They have utilized the radiation hybrid (RH) technique to generate a series of somatic cell hybrids that contain small segments of human chromosome 3 as the only human genetic material. A Chinese hamster-human cell hybrid (Q314-2) containing only human chromosome 3 was used to prepare radiation hybrids. Cells were lethally X-irradiated with 6,000 rads and fused to Urd(??) Chinese hamster cells by PEG 1000 treatment. The majority of hybrids (>72%) analyzed retained portions of chromosome 3. The amount of chromosome 3 in each hybrid ranged from nearly all of the chromosome to very little. Currently these hybrids are being further characterized with single copy probes of known map location in order to isolate regions of chromosome 3 that contain specific disease locus. These reduced hybrids can then be used for the construction of region specific libraries and for the generation of new DNA probes from the specific region of interest

A hybrid lightwave transmission system based on light injection/optoelectronic feedback techniques and fiber-VLLC integration

International Nuclear Information System (INIS)

Tsai, Wen-Shing; Lu, Hai-Han; Li, Chung-Yi; Chen, Bo-Rui; Lin, Hung-Hsien; Lin, Dai-Hua

2016-01-01

A hybrid lightwave transmission system based on light injection/optoelectronic feedback techniques and fiber-visible laser light communication (VLLC) integration is proposed and experimentally demonstrated. To be the first one of its kind in employing light injection and optoelectronic feedback techniques in a fiber-VLLC integration lightwave transmission system, the light is successfully directly modulated with Community Access Television (CATV), 16-QAM, and 16-QAM-OFDM signals. Over a 40 km SMF and a 10 m free-space VLLC transport, good performances of carrier-to-noise ratio (CNR)/composite second-order (CSO)/composite triple-beat (CTB)/bit error rate (BER) are achieved for CATV/16-QAM/16-QAM-OFDM signals transmission. Such a hybrid lightwave transmission system would be very useful since it can provide broadband integrated services including CATV, Internet, and telecommunication services over both distribute fiber and in-building networks. (letter)

An unsupervised strategy for biomedical image segmentation

Directory of Open Access Journals (Sweden)

Roberto Rodríguez

2010-09-01

Full Text Available Roberto Rodríguez1, Rubén Hernández21Digital Signal Processing Group, Institute of Cybernetics, Mathematics, and Physics, Havana, Cuba; 2Interdisciplinary Professional Unit of Engineering and Advanced Technology, IPN, MexicoAbstract: Many segmentation techniques have been published, and some of them have been widely used in different application problems. Most of these segmentation techniques have been motivated by specific application purposes. Unsupervised methods, which do not assume any prior scene knowledge can be learned to help the segmentation process, and are obviously more challenging than the supervised ones. In this paper, we present an unsupervised strategy for biomedical image segmentation using an algorithm based on recursively applying mean shift filtering, where entropy is used as a stopping criterion. This strategy is proven with many real images, and a comparison is carried out with manual segmentation. With the proposed strategy, errors less than 20% for false positives and 0% for false negatives are obtained.Keywords: segmentation, mean shift, unsupervised segmentation, entropy

Hybrid image classification technique for land-cover mapping in the Arctic tundra, North Slope, Alaska

Science.gov (United States)

Chaudhuri, Debasish

Remotely sensed image classification techniques are very useful to understand vegetation patterns and species combination in the vast and mostly inaccessible arctic region. Previous researches that were done for mapping of land cover and vegetation in the remote areas of northern Alaska have considerably low accuracies compared to other biomes. The unique arctic tundra environment with short growing season length, cloud cover, low sun angles, snow and ice cover hinders the effectiveness of remote sensing studies. The majority of image classification research done in this area as reported in the literature used traditional unsupervised clustering technique with Landsat MSS data. It was also emphasized by previous researchers that SPOT/HRV-XS data lacked the spectral resolution to identify the small arctic tundra vegetation parcels. Thus, there is a motivation and research need to apply a new classification technique to develop an updated, detailed and accurate vegetation map at a higher spatial resolution i.e. SPOT-5 data. Traditional classification techniques in remotely sensed image interpretation are based on spectral reflectance values with an assumption of the training data being normally distributed. Hence it is difficult to add ancillary data in classification procedures to improve accuracy. The purpose of this dissertation was to develop a hybrid image classification approach that effectively integrates ancillary information into the classification process and combines ISODATA clustering, rule-based classifier and the Multilayer Perceptron (MLP) classifier which uses artificial neural network (ANN). The main goal was to find out the best possible combination or sequence of classifiers for typically classifying tundra type vegetation that yields higher accuracy than the existing classified vegetation map from SPOT data. Unsupervised ISODATA clustering and rule-based classification techniques were combined to produce an intermediate classified map which was

A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set

Directory of Open Access Journals (Sweden)

Abdul Wahab Muzaffar

2015-01-01

Full Text Available The information extraction from unstructured text segments is a complex task. Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size. Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining. Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades. A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques. In the last decade, the focus has changed to hybrid approaches showing better results. This research presents a hybrid feature set for classification of relations between biomedical entities. The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS and a ranking algorithm. Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations. Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001. Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus.

Strategies for regular segmented reductions on GPU

DEFF Research Database (Denmark)

Larsen, Rasmus Wriedt; Henriksen, Troels

2017-01-01

We present and evaluate an implementation technique for regular segmented reductions on GPUs. Existing techniques tend to be either consistent in performance but relatively inefficient in absolute terms, or optimised for specific workloads and thereby exhibiting bad performance for certain input...... is in the context of the Futhark compiler, the implementation technique is applicable to any library or language that has a need for segmented reductions. We evaluate the technique on four microbenchmarks, two of which we also compare to implementations in the CUB library for GPU programming, as well as on two...

Clinical pilot study for the automatic segmentation and recognition of abdominal adipose tissue compartments from MRI data

Energy Technology Data Exchange (ETDEWEB)

Noel, P.B.; Bauer, J.S.; Ganter, C.; Markus, C.; Rummeny, E.J.; Engels, H.P. [Klinikum rechts der Isar, Technische Univ. Muenchen (Germany). Inst. fuer Radiologie; Hauner, H. [Klinikum rechts der Isar, Technische Univ. Muenchen (Germany). Else Kroener-Fresenius-Center for Nutritional Medicine

2012-06-15

Purpose: In the diagnosis and risk assessment of obesity, both the amount and distribution of adipose tissue compartments are critical factors. We present a hybrid method for the quantitative measurement of human body fat compartments. Materials and Methods: MRI imaging was performed on a 1.5 T scanner. In a pre-processing step, the images were corrected for bias field inhomogeneity. For segmentation and recognition a hybrid algorithm was developed to automatically differentiate between different adipose tissue compartments. The presented algorithm is designed with a combination of shape and intensity-based techniques. To incorporate the presented algorithm into the clinical routine, we developed a graphical user interface. Results from our methods were compared with the known volume of an adipose tissue phantom. To evaluate our method, we analyzed 40 clinical MRI scans of the abdominal region. Results: Relatively low segmentation errors were found for subcutaneous adipose tissue (3.56 %) and visceral adipose tissue (0.29 %) in phantom studies. The clinical results indicated high correlations between the distribution of adipose tissue compartments and obesity. Conclusion: We present an approach that rapidly identifies and quantifies adipose tissue depots of interest. With this method examination and analysis can be performed in a clinically feasible timeframe. (orig.)

Clinical pilot study for the automatic segmentation and recognition of abdominal adipose tissue compartments from MRI data

International Nuclear Information System (INIS)

Noel, P.B.; Bauer, J.S.; Ganter, C.; Markus, C.; Rummeny, E.J.; Engels, H.P.; Hauner, H.

2012-01-01

Purpose: In the diagnosis and risk assessment of obesity, both the amount and distribution of adipose tissue compartments are critical factors. We present a hybrid method for the quantitative measurement of human body fat compartments. Materials and Methods: MRI imaging was performed on a 1.5 T scanner. In a pre-processing step, the images were corrected for bias field inhomogeneity. For segmentation and recognition a hybrid algorithm was developed to automatically differentiate between different adipose tissue compartments. The presented algorithm is designed with a combination of shape and intensity-based techniques. To incorporate the presented algorithm into the clinical routine, we developed a graphical user interface. Results from our methods were compared with the known volume of an adipose tissue phantom. To evaluate our method, we analyzed 40 clinical MRI scans of the abdominal region. Results: Relatively low segmentation errors were found for subcutaneous adipose tissue (3.56 %) and visceral adipose tissue (0.29 %) in phantom studies. The clinical results indicated high correlations between the distribution of adipose tissue compartments and obesity. Conclusion: We present an approach that rapidly identifies and quantifies adipose tissue depots of interest. With this method examination and analysis can be performed in a clinically feasible timeframe. (orig.)

[Evaluation of Image Quality of Readout Segmented EPI with Readout Partial Fourier Technique].

Science.gov (United States)

Yoshimura, Yuuki; Suzuki, Daisuke; Miyahara, Kanae

Readout segmented EPI (readout segmentation of long variable echo-trains: RESOLVE) segmented k-space in the readout direction. By using the partial Fourier method in the readout direction, the imaging time was shortened. However, the influence on image quality due to insufficient data sampling is concerned. The setting of the partial Fourier method in the readout direction in each segment was changed. Then, we examined signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and distortion ratio for changes in image quality due to differences in data sampling. As the number of sampling segments decreased, SNR and CNR showed a low value. In addition, the distortion ratio did not change. The image quality of minimum sampling segments is greatly different from full data sampling, and caution is required when using it.

Modified GrabCut for human face segmentation

Directory of Open Access Journals (Sweden)

Dina Khattab

2014-12-01

Full Text Available GrabCut is a segmentation technique for 2D still color images, which is mainly based on an iterative energy minimization. The energy function of the GrabCut optimization algorithm is based mainly on a probabilistic model for pixel color distribution. Therefore, GrabCut may introduce unacceptable results in the cases of low contrast between foreground and background colors. In this manner, this paper presents a modified GrabCut technique for the segmentation of human faces from images of full humans. The modified technique introduces a new face location model for the energy minimization function of the GrabCut, in addition to the existing color one. This location model considers the distance distribution of the pixels from the silhouette boundary of a fitted head, of a 3D morphable model, to the image. The experimental results of the modified GrabCut have demonstrated better segmentation robustness and accuracy compared to the original GrabCut for human face segmentation.

Hybrid lightweight X-ray optics for half arcsecond imaging

Science.gov (United States)

Reid, Paul

This proposal is for the development of grazing incidence optics suitable to meet the 0.5 arcsec imaging and 2.3 square meter effective area requirements of the X-ray Surveyor mission concept, currently under study by NASA. Our approach is to combine two promising technologies, as yet individually unproven at the 0.5 arcsec level, into a hybrid mirror approach. The two technologies are thin piezoelectric film adjustable optics under development at SAO and PSU, and differential deposition under development at NASA MSFC. These technologies are complementary: adjustable optics are best suited to fixing low spatial frequency errors due to piezoelectric cell size limitations, and differential deposition is best suited for fixing mid-spatial frequency errors so as to limit the amount of material that must be deposited. Thus, the combination of the two techniques extends the bandwidth of figure errors that can be corrected beyond what it was for either individual technique. Both technologies will be applied to fabricate Wolter-I mirror segment from single thermally formed glass substrates. This work is directed at mirror segments only (not full shells), as we believe segments are the most appropriate for developing the 3 m diameter X-ray Surveyor high resolution mirror. In this program we will extend differential deposition to segment surfaces (from line profiles), investigate the most realistic error bandwidths for each technology, and determine the impacts of one technologys processing steps on the other to find if there is an optimal order to combining the technologies. In addition, we will also conduct a conical/cylindrical mirror metrology "round-robin," to cross-calibrate the different cylindrical metrology to one another as a means of minimizing systematic errors. Finally, we will examine the balancing and compensating of mirror stress due to the various thin films employed (piezoelectric layer, differential deposition, X-ray reflecting layer(s)) with an eye to

High capacity fiber optic sensor networks using hybrid multiplexing techniques and their applications

Science.gov (United States)

Sun, Qizhen; Li, Xiaolei; Zhang, Manliang; Liu, Qi; Liu, Hai; Liu, Deming

2013-12-01

Fiber optic sensor network is the development trend of fiber senor technologies and industries. In this paper, I will discuss recent research progress on high capacity fiber sensor networks with hybrid multiplexing techniques and their applications in the fields of security monitoring, environment monitoring, Smart eHome, etc. Firstly, I will present the architecture of hybrid multiplexing sensor passive optical network (HSPON), and the key technologies for integrated access and intelligent management of massive fiber sensor units. Two typical hybrid WDM/TDM fiber sensor networks for perimeter intrusion monitor and cultural relics security are introduced. Secondly, we propose the concept of "Microstructure－Optical X Domin Refecltor (M-OXDR)" for fiber sensor network expansion. By fabricating smart micro-structures with the ability of multidimensional encoded and low insertion loss along the fiber, the fiber sensor network of simple structure and huge capacity more than one thousand could be achieved. Assisted by the WDM/TDM and WDM/FDM decoding methods respectively, we built the verification systems for long-haul and real-time temperature sensing. Finally, I will show the high capacity and flexible fiber sensor network with IPv6 protocol based hybrid fiber/wireless access. By developing the fiber optic sensor with embedded IPv6 protocol conversion module and IPv6 router, huge amounts of fiber optic sensor nodes can be uniquely addressed. Meanwhile, various sensing information could be integrated and accessed to the Next Generation Internet.

Innovative hybrid pile oscillator technique in the Minerve reactor: open loop vs. closed loop

Directory of Open Access Journals (Sweden)

Geslot Benoit

2018-01-01

Full Text Available Pile oscillator techniques are powerful methods to measure small reactivity worth of isotopes of interest for nuclear data improvement. This kind of experiments has long been implemented in the Mineve experimental reactor, operated by CEA Cadarache. A hybrid technique, mixing reactivity worth estimation and measurement of small changes around test samples is presented here. It was made possible after the development of high sensitivity miniature fission chambers introduced next to the irradiation channel. A test campaign, called MAESTRO-SL, took place in 2015. Its objective was to assess the feasibility of the hybrid method and investigate the possibility to separate mixed neutron effects, such as fission/capture or scattering/capture. Experimental results are presented and discussed in this paper, which focus on comparing two measurements setups, one using a power control system (closed loop and another one where the power is free to drift (open loop. First, it is demonstrated that open loop is equivalent to closed loop. Uncertainty management and methods reproducibility are discussed. Second, results show that measuring the flux depression around oscillated samples provides valuable information regarding partial neutron cross sections. The technique is found to be very sensitive to the capture cross section at the expense of scattering, making it very useful to measure small capture effects of highly scattering samples.

Novel techniques for enhancement and segmentation of acne vulgaris lesions.

Science.gov (United States)

Malik, A S; Humayun, J; Kamel, N; Yap, F B-B

2014-08-01

More than 99% acne patients suffer from acne vulgaris. While diagnosing the severity of acne vulgaris lesions, dermatologists have observed inter-rater and intra-rater variability in diagnosis results. This is because during assessment, identifying lesion types and their counting is a tedious job for dermatologists. To make the assessment job objective and easier for dermatologists, an automated system based on image processing methods is proposed in this study. There are two main objectives: (i) to develop an algorithm for the enhancement of various acne vulgaris lesions; and (ii) to develop a method for the segmentation of enhanced acne vulgaris lesions. For the first objective, an algorithm is developed based on the theory of high dynamic range (HDR) images. The proposed algorithm uses local rank transform to generate the HDR images from a single acne image followed by the log transformation. Then, segmentation is performed by clustering the pixels based on Mahalanobis distance of each pixel from spectral models of acne vulgaris lesions. Two metrics are used to evaluate the enhancement of acne vulgaris lesions, i.e., contrast improvement factor (CIF) and image contrast normalization (ICN). The proposed algorithm is compared with two other methods. The proposed enhancement algorithm shows better result than both the other methods based on CIF and ICN. In addition, sensitivity and specificity are calculated for the segmentation results. The proposed segmentation method shows higher sensitivity and specificity than other methods. This article specifically discusses the contrast enhancement and segmentation for automated diagnosis system of acne vulgaris lesions. The results are promising that can be used for further classification of acne vulgaris lesions for final grading of the lesions. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

An efficient hybrid technique in RCS predictions of complex targets at high frequencies

Science.gov (United States)

Algar, María-Jesús; Lozano, Lorena; Moreno, Javier; González, Iván; Cátedra, Felipe

2017-09-01

Most computer codes in Radar Cross Section (RCS) prediction use Physical Optics (PO) and Physical theory of Diffraction (PTD) combined with Geometrical Optics (GO) and Geometrical Theory of Diffraction (GTD). The latter approaches are computationally cheaper and much more accurate for curved surfaces, but not applicable for the computation of the RCS of all surfaces of a complex object due to the presence of caustic problems in the analysis of concave surfaces or flat surfaces in the far field. The main contribution of this paper is the development of a hybrid method based on a new combination of two asymptotic techniques: GTD and PO, considering the advantages and avoiding the disadvantages of each of them. A very efficient and accurate method to analyze the RCS of complex structures at high frequencies is obtained with the new combination. The proposed new method has been validated comparing RCS results obtained for some simple cases using the proposed approach and RCS using the rigorous technique of Method of Moments (MoM). Some complex cases have been examined at high frequencies contrasting the results with PO. This study shows the accuracy and the efficiency of the hybrid method and its suitability for the computation of the RCS at really large and complex targets at high frequencies.

Crop to wild introgression in lettuce: following the fate of crop genome segments in backcross populations

NARCIS (Netherlands)

Uwimana, B.; Smulders, M.J.M.; Hooftman, D.A.P.; Hartman, Y.; van Tienderen, P.H.; Jansen, J.; McHale, L.K.; Michelmore, R.W.; Visser, R.G.F.; van de Wiel, C.C.M.

2012-01-01

Background: After crop-wild hybridization, some of the crop genomic segments may become established in wild populations through selfing of the hybrids or through backcrosses to the wild parent. This constitutes a possible route through which crop (trans)genes could become established in natural

Crop to wild introgression in lettuce: following the fate of crop genome segments in backcross populations

NARCIS (Netherlands)

Uwimana, B.; Smulders, M.J.M.; Hooftman, D.A.P.; Hartman, Y.; Tienderen, van P.H.; Jansen, J.; McHale, L.K.; Michelmore, R.; Visser, R.G.F.; Wiel, van de C.C.M.

2012-01-01

After crop-wild hybridization, some of the crop genomic segments may become established in wild populations through selfing of the hybrids or through backcrosses to the wild parent. This constitutes a possible route through which crop (trans)genes could become established in natural populations. The

Nationwide Hybrid Change Detection of Buildings

Science.gov (United States)

Hron, V.; Halounova, L.

2016-06-01

The Fundamental Base of Geographic Data of the Czech Republic (hereinafter FBGD) is a national 2D geodatabase at a 1:10,000 scale with more than 100 geographic objects. This paper describes the design of the permanent updating mechanism of buildings in FBGD. The proposed procedure belongs to the category of hybrid change detection (HCD) techniques which combine pixel-based and object-based evaluation. The main sources of information for HCD are cadastral information and bi-temporal vertical digital aerial photographs. These photographs have great information potential because they contain multispectral, position and also elevation information. Elevation information represents a digital surface model (DSM) which can be obtained using the image matching technique. Pixel-based evaluation of bi-temporal DSMs enables fast localization of places with potential building changes. These coarse results are subsequently classified through the object-based image analysis (OBIA) using spectral, textural and contextual features and GIS tools. The advantage of the two-stage evaluation is the pre-selection of locations where image segmentation (a computationally demanding part of OBIA) is performed. It is not necessary to apply image segmentation to the entire scene, but only to the surroundings of detected changes, which contributes to significantly faster processing and lower hardware requirements. The created technology is based on open-source software solutions that allow easy portability on multiple computers and parallelization of processing. This leads to significant savings of financial resources which can be expended on the further development of FBGD.

Energy functionals for medical image segmentation: choices and consequences

OpenAIRE

McIntosh, Christopher

2011-01-01

Medical imaging continues to permeate the practice of medicine, but automated yet accurate segmentation and labeling of anatomical structures continues to be a major obstacle to computerized medical image analysis. Though there exists numerous approaches for medical image segmentation, one in particular has gained increasing popularity: energy minimization-based techniques, and the large set of methods encompassed therein. With these techniques an energy function must be chosen, segmentations...

Economics of hybrid photovoltaic power plants

Energy Technology Data Exchange (ETDEWEB)

Breyer, Christian

2012-08-16

The global power supply stability is faced to several severe and fundamental threats, in particular steadily increasing power demand, diminishing and degrading fossil and nuclear energy resources, very harmful greenhouse gas emissions, significant energy injustice and a structurally misbalanced ecological footprint. Photovoltaic (PV) power systems are analysed in various aspects focusing on economic and technical considerations of supplemental and substitutional power supply to the constraint conventional power system. To infer the most relevant system approach for PV power plants several solar resources available for PV systems are compared. By combining the different solar resources and respective economics, two major PV systems are identified to be very competitive in almost all regions in the world. The experience curve concept is used as a key technique for the development of scenario assumptions on economic projections for the decade of the 2010s. Main drivers for cost reductions in PV systems are learning and production growth rate, thus several relevant aspects are discussed such as research and development investments, technical PV market potential, different PV technologies and the energetic sustainability of PV. Three major market segments for PV systems are identified: off-grid PV solutions, decentralised small scale on-grid PV systems (several kWp) and large scale PV power plants (tens of MWp). Mainly by application of 'grid-parity' and 'fuel-parity' concepts per country, local market and conventional power plant basis, the global economic market potential for all major PV system segments is derived. PV power plant hybridization potential of all relevant power technologies and the global power plant structure are analyzed regarding technical, economical and geographical feasibility. Key success criteria for hybrid PV power plants are discussed and comprehensively analysed for all adequate power plant technologies, i.e. oil, gas and coal fired power

Economics of hybrid photovoltaic power plants

Energy Technology Data Exchange (ETDEWEB)

Breyer, Christian

2012-08-16

The global power supply stability is faced to several severe and fundamental threats, in particular steadily increasing power demand, diminishing and degrading fossil and nuclear energy resources, very harmful greenhouse gas emissions, significant energy injustice and a structurally misbalanced ecological footprint. Photovoltaic (PV) power systems are analysed in various aspects focusing on economic and technical considerations of supplemental and substitutional power supply to the constraint conventional power system. To infer the most relevant system approach for PV power plants several solar resources available for PV systems are compared. By combining the different solar resources and respective economics, two major PV systems are identified to be very competitive in almost all regions in the world. The experience curve concept is used as a key technique for the development of scenario assumptions on economic projections for the decade of the 2010s. Main drivers for cost reductions in PV systems are learning and production growth rate, thus several relevant aspects are discussed such as research and development investments, technical PV market potential, different PV technologies and the energetic sustainability of PV. Three major market segments for PV systems are identified: off-grid PV solutions, decentralised small scale on-grid PV systems (several kWp) and large scale PV power plants (tens of MWp). Mainly by application of 'grid-parity' and 'fuel-parity' concepts per country, local market and conventional power plant basis, the global economic market potential for all major PV system segments is derived. PV power plant hybridization potential of all relevant power technologies and the global power plant structure are analyzed regarding technical, economical and geographical feasibility. Key success criteria for hybrid PV power plants are discussed and comprehensively analysed for all adequate power plant technologies, i.e. oil, gas and

Establishment of 60Co dose calibration curve using fluorescent in situ hybridization assay technique: Result of preliminary study

International Nuclear Information System (INIS)

Rahimah Abdul Rahim; Noriah Jamal; Noraisyah Mohd Yusof; Juliana Mahamad Napiah; Nelly Bo Nai Lee

2010-01-01

This study aims at establishing an in-vitro 60 Co dose calibration curve using Fluorescent In-Situ Hybridization assay technique for the Malaysian National Bio dosimetry Laboratory. Blood samples collected from a female healthy donor were irradiated with several doses of 60 Co radiation. Following culturing of lymphocytes, microscopic slides are prepared, denatured and hybridized. The frequencies of translocation are estimated in the metaphases. A calibration curve was then generated using a regression technique. It shows a good fit to a linear-quadratic model. The results of this study might be useful in estimating absorbed dose for the individual exposed to ionizing radiation retrospectively. This information may be useful as a guide for medical treatment for the assessment of possible health consequences. (author)

REVIEW OF HEART DISEASE PREDICTION SYSTEM USING DATA MINING AND HYBRID INTELLIGENT TECHNIQUES

Directory of Open Access Journals (Sweden)

R. Chitra

2013-07-01

Full Text Available The Healthcare industry generally clinical diagnosis is done mostly by doctor’s expertise and experience. Computer Aided Decision Support System plays a major role in medical field. With the growing research on heart disease predicting system, it has become important to categories the research outcomes and provides readers with an overview of the existing heart disease prediction techniques in each category. Neural Networks are one of many data mining analytical tools that can be utilized to make predictions for medical data. From the study it is observed that Hybrid Intelligent Algorithm improves the accuracy of the heart disease prediction system. The commonly used techniques for Heart Disease Prediction and their complexities are summarized in this paper.

Improving cerebellar segmentation with statistical fusion

Science.gov (United States)

Plassard, Andrew J.; Yang, Zhen; Prince, Jerry L.; Claassen, Daniel O.; Landman, Bennett A.

2016-03-01

The cerebellum is a somatotopically organized central component of the central nervous system well known to be involved with motor coordination and increasingly recognized roles in cognition and planning. Recent work in multiatlas labeling has created methods that offer the potential for fully automated 3-D parcellation of the cerebellar lobules and vermis (which are organizationally equivalent to cortical gray matter areas). This work explores the trade offs of using different statistical fusion techniques and post hoc optimizations in two datasets with distinct imaging protocols. We offer a novel fusion technique by extending the ideas of the Selective and Iterative Method for Performance Level Estimation (SIMPLE) to a patch-based performance model. We demonstrate the effectiveness of our algorithm, Non- Local SIMPLE, for segmentation of a mixed population of healthy subjects and patients with severe cerebellar anatomy. Under the first imaging protocol, we show that Non-Local SIMPLE outperforms previous gold-standard segmentation techniques. In the second imaging protocol, we show that Non-Local SIMPLE outperforms previous gold standard techniques but is outperformed by a non-locally weighted vote with the deeper population of atlases available. This work advances the state of the art in open source cerebellar segmentation algorithms and offers the opportunity for routinely including cerebellar segmentation in magnetic resonance imaging studies that acquire whole brain T1-weighted volumes with approximately 1 mm isotropic resolution.

Storing tooth segments for optimal esthetics

NARCIS (Netherlands)

Tuzuner, T.; Turgut, S.; Özen, B.; Kılınç, H.; Bagis, B.

2016-01-01

Objective: A fractured whole crown segment can be reattached to its remnant; crowns from extracted teeth may be used as pontics in splinting techniques. We aimed to evaluate the effect of different storage solutions on tooth segment optical properties after different durations. Study design: Sixty

Engine Yaw Augmentation for Hybrid-Wing-Body Aircraft via Optimal Control Allocation Techniques

Science.gov (United States)

Taylor, Brian R.; Yoo, Seung Yeun

2011-01-01

Asymmetric engine thrust was implemented in a hybrid-wing-body non-linear simulation to reduce the amount of aerodynamic surface deflection required for yaw stability and control. Hybrid-wing-body aircraft are especially susceptible to yaw surface deflection due to their decreased bare airframe yaw stability resulting from the lack of a large vertical tail aft of the center of gravity. Reduced surface deflection, especially for trim during cruise flight, could reduce the fuel consumption of future aircraft. Designed as an add-on, optimal control allocation techniques were used to create a control law that tracks total thrust and yaw moment commands with an emphasis on not degrading the baseline system. Implementation of engine yaw augmentation is shown and feasibility is demonstrated in simulation with a potential drag reduction of 2 to 4 percent. Future flight tests are planned to demonstrate feasibility in a flight environment.

A hybrid flower pollination algorithm based modified randomized location for multi-threshold medical image segmentation.

Science.gov (United States)

Wang, Rui; Zhou, Yongquan; Zhao, Chengyan; Wu, Haizhou

2015-01-01

Multi-threshold image segmentation is a powerful image processing technique that is used for the preprocessing of pattern recognition and computer vision. However, traditional multilevel thresholding methods are computationally expensive because they involve exhaustively searching the optimal thresholds to optimize the objective functions. To overcome this drawback, this paper proposes a flower pollination algorithm with a randomized location modification. The proposed algorithm is used to find optimal threshold values for maximizing Otsu's objective functions with regard to eight medical grayscale images. When benchmarked against other state-of-the-art evolutionary algorithms, the new algorithm proves itself to be robust and effective through numerical experimental results including Otsu's objective values and standard deviations.

Hybrid Segmentation of Vessels and Automated Flow Measures in In-Vivo Ultrasound Imaging

DEFF Research Database (Denmark)

Moshavegh, Ramin; Martins, Bo; Hansen, Kristoffer Lindskov

2016-01-01

Vector Flow Imaging (VFI) has received an increasing attention in the scientific field of ultrasound, as it enables angle independent visualization of blood flow. VFI can be used in volume flow estimation, but a vessel segmentation is needed to make it fully automatic. A novel vessel segmentation...

Socio-economic Classification and its Scope in Crafting Rural Segments

Directory of Open Access Journals (Sweden)

Rinalini Pathak Kakati

2015-12-01

Full Text Available With the liberalization of the Indian Economy in the mid 1990’s, substantial growth has been seen in the rural areas. Rural India which comprises around 70% of the total population of the country has become an emerging area for marketers. This study tries to identify key market variables that can help in crafting rural market segments. The socio-economic classification (SEC 2011 which segments the market based on education level and possession of consumer durables. This study examines income as another key market variable together with education in the creation of distinct segments or hybrid segments. It then further identifies important criteria like technical, promotional and social in influencing consumers’ behaviour in the context of the purchase of consumer durables which can thereby help to create segments. The study concludes that the increase in education level has higher impact than increase in income on the important identified purchase criteria.

A hybrid technique for private location-based queries with database protection

KAUST Repository

Ghinita, Gabriel

2009-01-01

Mobile devices with global positioning capabilities allow users to retrieve points of interest (POI) in their proximity. To protect user privacy, it is important not to disclose exact user coordinates to un-trusted entities that provide location-based services. Currently, there are two main approaches to protect the location privacy of users: (i) hiding locations inside cloaking regions (CRs) and (ii) encrypting location data using private information retrieval (PIR) protocols. Previous work focused on finding good trade-offs between privacy and performance of user protection techniques, but disregarded the important issue of protecting the POI dataset D. For instance, location cloaking requires large-sized CRs, leading to excessive disclosure of POIs (O(|D|) in the worst case). PIR, on the other hand, reduces this bound to , but at the expense of high processing and communication overhead. We propose a hybrid, two-step approach to private location-based queries, which provides protection for both the users and the database. In the first step, user locations are generalized to coarse-grained CRs which provide strong privacy. Next, a PIR protocol is applied with respect to the obtained query CR. To protect excessive disclosure of POI locations, we devise a cryptographic protocol that privately evaluates whether a point is enclosed inside a rectangular region. We also introduce an algorithm to efficiently support PIR on dynamic POI sub-sets. Our method discloses O(1) POI, orders of magnitude fewer than CR- or PIR-based techniques. Experimental results show that the hybrid approach is scalable in practice, and clearly outperforms the pure-PIR approach in terms of computational and communication overhead. © 2009 Springer Berlin Heidelberg.

Optimized Audio Classification and Segmentation Algorithm by Using Ensemble Methods

Directory of Open Access Journals (Sweden)

Saadia Zahid

2015-01-01

Full Text Available Audio segmentation is a basis for multimedia content analysis which is the most important and widely used application nowadays. An optimized audio classification and segmentation algorithm is presented in this paper that segments a superimposed audio stream on the basis of its content into four main audio types: pure-speech, music, environment sound, and silence. An algorithm is proposed that preserves important audio content and reduces the misclassification rate without using large amount of training data, which handles noise and is suitable for use for real-time applications. Noise in an audio stream is segmented out as environment sound. A hybrid classification approach is used, bagged support vector machines (SVMs with artificial neural networks (ANNs. Audio stream is classified, firstly, into speech and nonspeech segment by using bagged support vector machines; nonspeech segment is further classified into music and environment sound by using artificial neural networks and lastly, speech segment is classified into silence and pure-speech segments on the basis of rule-based classifier. Minimum data is used for training classifier; ensemble methods are used for minimizing misclassification rate and approximately 98% accurate segments are obtained. A fast and efficient algorithm is designed that can be used with real-time multimedia applications.

Comparative methods for PET image segmentation in pharyngolaryngeal squamous cell carcinoma

Energy Technology Data Exchange (ETDEWEB)

Zaidi, Habib [Geneva University Hospital, Division of Nuclear Medicine and Molecular Imaging, Geneva (Switzerland); Geneva University, Geneva Neuroscience Center, Geneva (Switzerland); University of Groningen, Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen (Netherlands); Abdoli, Mehrsima [University of Groningen, Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen (Netherlands); Fuentes, Carolina Llina [Geneva University Hospital, Division of Nuclear Medicine and Molecular Imaging, Geneva (Switzerland); Naqa, Issam M.El [McGill University, Department of Medical Physics, Montreal (Canada)

2012-05-15

Several methods have been proposed for the segmentation of {sup 18}F-FDG uptake in PET. In this study, we assessed the performance of four categories of {sup 18}F-FDG PET image segmentation techniques in pharyngolaryngeal squamous cell carcinoma using clinical studies where the surgical specimen served as the benchmark. Nine PET image segmentation techniques were compared including: five thresholding methods; the level set technique (active contour); the stochastic expectation-maximization approach; fuzzy clustering-based segmentation (FCM); and a variant of FCM, the spatial wavelet-based algorithm (FCM-SW) which incorporates spatial information during the segmentation process, thus allowing the handling of uptake in heterogeneous lesions. These algorithms were evaluated using clinical studies in which the segmentation results were compared to the 3-D biological tumour volume (BTV) defined by histology in PET images of seven patients with T3-T4 laryngeal squamous cell carcinoma who underwent a total laryngectomy. The macroscopic tumour specimens were collected ''en bloc'', frozen and cut into 1.7- to 2-mm thick slices, then digitized for use as reference. The clinical results suggested that four of the thresholding methods and expectation-maximization overestimated the average tumour volume, while a contrast-oriented thresholding method, the level set technique and the FCM-SW algorithm underestimated it, with the FCM-SW algorithm providing relatively the highest accuracy in terms of volume determination (-5.9 {+-} 11.9%) and overlap index. The mean overlap index varied between 0.27 and 0.54 for the different image segmentation techniques. The FCM-SW segmentation technique showed the best compromise in terms of 3-D overlap index and statistical analysis results with values of 0.54 (0.26-0.72) for the overlap index. The BTVs delineated using the FCM-SW segmentation technique were seemingly the most accurate and approximated closely the 3-D BTVs

Planning and delivering high doses to targets surrounding the spinal cord at the lower neck and upper mediastinal levels: static beam-segmentation technique executed with a multileaf collimator

International Nuclear Information System (INIS)

Neve, W. de; Wagter, C. de; Jaeger, K. de; Thienpont, M.; Colle, C.; Derycke, S.; Schelfhout, J.

1996-01-01

Background and purpose. It remains a technical challenge to limit the dose to the spinal cord below tolerance if, in head and neck or thyroid cancer, the planning target volume reaches to a level below the shoulders. In order to avoid these dose limitations, we developed a standard plan involving Beam Intensity Modulation (BIM) executed by a static technique of beam segmentation. In this standard plan, many machine parameters (gantry angles, couch position, relative beam and segment weights) as well as the beam segmentation rules were identical for all patients. Materials and methods. The standard plan involved: the use of static beams with a single isocenter; BIM by field segmentation executable with a standard Philips multileaf collimator; virtual simulation and dose computation on a general 3D-planning system (Sherouse's GRATIS[reg]); heuristic computation of segment intensities and optimization (improving the dose distribution and reducing the execution time) by human intelligence. The standard plan used 20 segments spread over 8 gantry angles plus 2 non-segmented wedged beams (2 gantry angles). Results. The dose that could be achieved at the lowest target voxel, without exceeding tolerance of the spinal cord (50 Gy at highest voxel) was 70-80 Gy. The in-target 3D dose-inhomogeneity was ∼25%. The shortest time of execution of a treatment (22 segments) on a patient (unpublished) was 25 min. Conclusions. A heuristic model has been developed and investigated to obtain a 3D concave dose distribution applicable to irradiate targets in the lower neck and upper mediastinal regions. The technique spares efficiently the spinal cord and allows the delivery of higher target doses than with conventional techniques. It can be planned as a standard plan using conventional 3D-planning technology. The routine clinical implementation is performed with commercially available equipment, however, at the expense of extended execution times

Application of Fluorescence In Situ Hybridization (FISH) Technique for the Detection of Genetic Aberration in Medical Science

OpenAIRE

Ratan, Zubair Ahmed; Zaman, Sojib Bin; Mehta, Varshil; Haidere, Mohammad Faisal; Runa, Nusrat Jahan; Akter, Nasrin

2017-01-01

Fluorescence in situ hybridization (FISH) is a macromolecule recognition technique, which is considered as a new advent in the field of cytology.?Initially, it was developed as a physical mapping tool to delineate genes within chromosomes. The accuracy and versatility of FISH were subsequently capitalized upon in biological and medical research. This visually appealing technique provides an intermediate degree of resolution between DNA analysis and chromosomal investigations. FISH consists of...

Transfer learning improves supervised image segmentation across imaging protocols

DEFF Research Database (Denmark)

van Opbroek, Annegreet; Ikram, M. Arfan; Vernooij, Meike W.

2015-01-01

with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two MRI brain-segmentation tasks with multi-site data: white matter, gray matter, and CSF segmentation; and white-matter- /MS-lesion segmentation......The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform...... well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore...

Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation.

Science.gov (United States)

Babin, D; Pižurica, A; Bellens, R; De Bock, J; Shang, Y; Goossens, B; Vansteenkiste, E; Philips, W

2012-07-01

Extraction of structural and geometric information from 3-D images of blood vessels is a well known and widely addressed segmentation problem. The segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, with a special application in diagnostics and surgery on arteriovenous malformations (AVM). However, the techniques addressing the problem of the AVM inner structure segmentation are rare. In this work we present a novel method of pixel profiling with the application to segmentation of the 3-D angiography AVM images. Our algorithm stands out in situations with low resolution images and high variability of pixel intensity. Another advantage of our method is that the parameters are set automatically, which yields little manual user intervention. The results on phantoms and real data demonstrate its effectiveness and potentials for fine delineation of AVM structure. Copyright © 2012 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2016-01-01

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

SU-E-T-451: Hybrid-VMAT: A Novel Technique Combining VMAT and 3D in Planning Whole Breast Radiotherapy with a Simultaneously-Integrated Boost (WBRT+SIB)

International Nuclear Information System (INIS)

Guida, K; Qamar, K; Thompson, M

2015-01-01

Purpose: The RTOG 1005 trial offered a hypofractionated arm in delivering WBRT+SIB. Traditionally, treatments were planned at our institution using field-in-field (FiF) tangents with a concurrent 3D conformal boost. With the availability of VMAT, it is possible that a hybrid VMAT-3D planning technique could provide another avenue in treating WBRT+SIB. Methods: A retrospective study of nine patients previously treated using RTOG 1005 guidelines was performed to compare FiF+3D plans with the hybrid technique. A combination of static tangents and partial VMAT arcs were used in base-dose optimization. The hybrid plans were optimized to deliver 4005cGy to the breast PTVeval and 4800cGy to the lumpectomy PTVeval over 15 fractions. Plans were optimized to meet the planning goals dictated by RTOG 1005. Results: Hybrid plans yielded similar coverage of breast and lumpectomy PTVs (average D95 of 4013cGy compared to 3990cGy for conventional), while reducing the volume of high dose within the breast; the average D30 and D50 for the hybrid technique were 4517cGy and 4288cGy, compared to 4704cGy and 4377cGy for conventional planning. Hybrid plans increased conformity as well, yielding CI95% values of 1.22 and 1.54 for breast and lumpectomy PTVeval volumes; in contrast, conventional plans averaged 1.49 and 2.27, respectively. The nearby organs at risk (OARs) received more low dose with the hybrid plans due to low dose spray from the partial arcs, but all hybrid plans did meet the acceptable constraints, at a minimum, from the protocol. Treatment planning time was also reduced, as plans were inversely optimized (VMAT) rather than forward optimized. Conclusion: Hybrid-VMAT could be a solution in delivering WB+SIB, as plans yield very conformal treatment plans and maintain clinical standards in OAR sparing. For treating breast cancer patients with a simultaneously-integrated boost, Hybrid-VMAT offers superiority in dosimetric conformity and planning time as compared to FIF

SU-E-T-451: Hybrid-VMAT: A Novel Technique Combining VMAT and 3D in Planning Whole Breast Radiotherapy with a Simultaneously-Integrated Boost (WBRT+SIB)

Energy Technology Data Exchange (ETDEWEB)

Guida, K; Qamar, K; Thompson, M [University of Kansas Hospital, Kansas City, MO (United States)

2015-06-15

Purpose: The RTOG 1005 trial offered a hypofractionated arm in delivering WBRT+SIB. Traditionally, treatments were planned at our institution using field-in-field (FiF) tangents with a concurrent 3D conformal boost. With the availability of VMAT, it is possible that a hybrid VMAT-3D planning technique could provide another avenue in treating WBRT+SIB. Methods: A retrospective study of nine patients previously treated using RTOG 1005 guidelines was performed to compare FiF+3D plans with the hybrid technique. A combination of static tangents and partial VMAT arcs were used in base-dose optimization. The hybrid plans were optimized to deliver 4005cGy to the breast PTVeval and 4800cGy to the lumpectomy PTVeval over 15 fractions. Plans were optimized to meet the planning goals dictated by RTOG 1005. Results: Hybrid plans yielded similar coverage of breast and lumpectomy PTVs (average D95 of 4013cGy compared to 3990cGy for conventional), while reducing the volume of high dose within the breast; the average D30 and D50 for the hybrid technique were 4517cGy and 4288cGy, compared to 4704cGy and 4377cGy for conventional planning. Hybrid plans increased conformity as well, yielding CI95% values of 1.22 and 1.54 for breast and lumpectomy PTVeval volumes; in contrast, conventional plans averaged 1.49 and 2.27, respectively. The nearby organs at risk (OARs) received more low dose with the hybrid plans due to low dose spray from the partial arcs, but all hybrid plans did meet the acceptable constraints, at a minimum, from the protocol. Treatment planning time was also reduced, as plans were inversely optimized (VMAT) rather than forward optimized. Conclusion: Hybrid-VMAT could be a solution in delivering WB+SIB, as plans yield very conformal treatment plans and maintain clinical standards in OAR sparing. For treating breast cancer patients with a simultaneously-integrated boost, Hybrid-VMAT offers superiority in dosimetric conformity and planning time as compared to FIF

Statistical segmentation of multidimensional brain datasets

Science.gov (United States)

Desco, Manuel; Gispert, Juan D.; Reig, Santiago; Santos, Andres; Pascau, Javier; Malpica, Norberto; Garcia-Barreno, Pedro

2001-07-01

This paper presents an automatic segmentation procedure for MRI neuroimages that overcomes part of the problems involved in multidimensional clustering techniques like partial volume effects (PVE), processing speed and difficulty of incorporating a priori knowledge. The method is a three-stage procedure: 1) Exclusion of background and skull voxels using threshold-based region growing techniques with fully automated seed selection. 2) Expectation Maximization algorithms are used to estimate the probability density function (PDF) of the remaining pixels, which are assumed to be mixtures of gaussians. These pixels can then be classified into cerebrospinal fluid (CSF), white matter and grey matter. Using this procedure, our method takes advantage of using the full covariance matrix (instead of the diagonal) for the joint PDF estimation. On the other hand, logistic discrimination techniques are more robust against violation of multi-gaussian assumptions. 3) A priori knowledge is added using Markov Random Field techniques. The algorithm has been tested with a dataset of 30 brain MRI studies (co-registered T1 and T2 MRI). Our method was compared with clustering techniques and with template-based statistical segmentation, using manual segmentation as a gold-standard. Our results were more robust and closer to the gold-standard.

Hybrid PIV-PTV technique for measuring blood flow in rat mesenteric vessels.

Science.gov (United States)

Ha, Hojin; Nam, Kweon-Ho; Lee, Sang Joon

2012-11-01

The micro-particle tracking velocimetry (μ-PTV) technique is used to obtain the velocity fields of blood flow in the microvasculature under in vivo conditions because it can provide the blood velocity distribution in microvessels with high spatial resolution. The in vivo μ-PTV technique usually requires a few to tens of seconds to obtain a whole velocity profile across the vessel diameter because of the limited number density of tracer particles under in vivo conditions. Thus, the μ-PTV technique alone is limited in measuring unsteady blood flows that fluctuate irregularly due to the heart beating and muscle movement in surrounding tissues. In this study, a new hybrid PIV-PTV technique was established by combining PTV and particle image velocimetry (PIV) techniques to resolve the drawbacks of the μ-PTV method in measuring blood flow in microvessels under in vivo conditions. Images of red blood cells (RBCs) and fluorescent particles in rat mesenteric vessels were obtained simultaneously. Temporal variations of the centerline blood velocity were monitored using a fast Fourier transform-based cross-correlation PIV method. The fluorescence particle images were analyzed using the μ-PTV technique to extract the spatial distribution of the velocity vectors. Data from the μ-PTV and PIV methods were combined to obtain a better estimate of the velocity profile in actual blood flow. This technique will be useful in investigating hemodynamics in microcirculation by measuring unsteady irregular blood flows more accurately. Copyright © 2012 Elsevier Inc. All rights reserved.

Quantification of esophageal wall thickness in CT using atlas-based segmentation technique

Science.gov (United States)

Wang, Jiahui; Kang, Min Kyu; Kligerman, Seth; Lu, Wei

2015-03-01

Esophageal wall thickness is an important predictor of esophageal cancer response to therapy. In this study, we developed a computerized pipeline for quantification of esophageal wall thickness using computerized tomography (CT). We first segmented the esophagus using a multi-atlas-based segmentation scheme. The esophagus in each atlas CT was manually segmented to create a label map. Using image registration, all of the atlases were aligned to the imaging space of the target CT. The deformation field from the registration was applied to the label maps to warp them to the target space. A weighted majority-voting label fusion was employed to create the segmentation of esophagus. Finally, we excluded the lumen from the esophagus using a threshold of -600 HU and measured the esophageal wall thickness. The developed method was tested on a dataset of 30 CT scans, including 15 esophageal cancer patients and 15 normal controls. The mean Dice similarity coefficient (DSC) and mean absolute distance (MAD) between the segmented esophagus and the reference standard were employed to evaluate the segmentation results. Our method achieved a mean Dice coefficient of 65.55 ± 10.48% and mean MAD of 1.40 ± 1.31 mm for all the cases. The mean esophageal wall thickness of cancer patients and normal controls was 6.35 ± 1.19 mm and 6.03 ± 0.51 mm, respectively. We conclude that the proposed method can perform quantitative analysis of esophageal wall thickness and would be useful for tumor detection and tumor response evaluation of esophageal cancer.

A multi-scale tensor voting approach for small retinal vessel segmentation in high resolution fundus images.

Science.gov (United States)

Christodoulidis, Argyrios; Hurtut, Thomas; Tahar, Houssem Ben; Cheriet, Farida

2016-09-01

Segmenting the retinal vessels from fundus images is a prerequisite for many CAD systems for the automatic detection of diabetic retinopathy lesions. So far, research efforts have concentrated mainly on the accurate localization of the large to medium diameter vessels. However, failure to detect the smallest vessels at the segmentation step can lead to false positive lesion detection counts in a subsequent lesion analysis stage. In this study, a new hybrid method for the segmentation of the smallest vessels is proposed. Line detection and perceptual organization techniques are combined in a multi-scale scheme. Small vessels are reconstructed from the perceptual-based approach via tracking and pixel painting. The segmentation was validated in a high resolution fundus image database including healthy and diabetic subjects using pixel-based as well as perceptual-based measures. The proposed method achieves 85.06% sensitivity rate, while the original multi-scale line detection method achieves 81.06% sensitivity rate for the corresponding images (p<0.05). The improvement in the sensitivity rate for the database is 6.47% when only the smallest vessels are considered (p<0.05). For the perceptual-based measure, the proposed method improves the detection of the vasculature by 7.8% against the original multi-scale line detection method (p<0.05). Copyright © 2016 Elsevier Ltd. All rights reserved.

SEGMENTATION AND CLASSIFICATION OF CERVICAL CYTOLOGY IMAGES USING MORPHOLOGICAL AND STATISTICAL OPERATIONS

Directory of Open Access Journals (Sweden)

S Anantha Sivaprakasam

2017-02-01

Full Text Available Cervical cancer that is a disease, in which malignant (cancer cells form in the tissues of the cervix, is one of the fourth leading causes of cancer death in female community worldwide. The cervical cancer can be prevented and/or cured if it is diagnosed in the pre-cancerous lesion stage or earlier. A common physical examination technique widely used in the screening is called Papanicolaou test or Pap test which is used to detect the abnormality of the cell. Due to intricacy of the cell nature, automating of this procedure is still a herculean task for the pathologist. This paper addresses solution for the challenges in terms of a simple and novel method to segment and classify the cervical cell automatically. The primary step of this procedure is pre-processing in which de-nosing, de-correlation operation and segregation of colour components are carried out, Then, two new techniques called Morphological and Statistical Edge based segmentation and Morphological and Statistical Region Based segmentation Techniques- put forward in this paper, and that are applied on the each component of image to segment the nuclei from cervical image. Finally, all segmented colour components are combined together to make a final segmentation result. After extracting the nuclei, the morphological features are extracted from the nuclei. The performance of two techniques mentioned above outperformed than standard segmentation techniques. Besides, Morphological and Statistical Edge based segmentation is outperformed than Morphological and Statistical Region based Segmentation. Finally, the nuclei are classified based on the morphological value The segmentation accuracy is echoed in classification accuracy. The overall segmentation accuracy is 97%.

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

Directory of Open Access Journals (Sweden)

Paolo Gargiulo

2014-03-01

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

User-guided segmentation for volumetric retinal optical coherence tomography images

Science.gov (United States)

Yin, Xin; Chao, Jennifer R.; Wang, Ruikang K.

2014-01-01

Abstract. Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method. PMID:25147962

Parallel fuzzy connected image segmentation on GPU

OpenAIRE

Zhuge, Ying; Cao, Yong; Udupa, Jayaram K.; Miller, Robert W.

2011-01-01

Purpose: Image segmentation techniques using fuzzy connectedness (FC) principles have shown their effectiveness in segmenting a variety of objects in several large applications. However, one challenge in these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays, commodity graphics hardware provides a highly parallel computing environment. In this paper, the authors present a parallel fuzzy connected image segmentation algorithm impleme...

Hybrid strategies in nanolithography

Energy Technology Data Exchange (ETDEWEB)

Saavedra, Hector M; Mullen, Thomas J; Zhang Pengpeng; Dewey, Daniel C; Claridge, Shelley A; Weiss, Paul S [Department of Chemistry, The Pennsylvania State University, University Park, PA 16802 (United States)], E-mail: psw@cnsi.ucla.edu

2010-03-15

Hybrid nanoscale patterning strategies combine the registration and addressability of conventional lithographic techniques with the chemical and physical functionality enabled by intermolecular, electrostatic and/or biological interactions. This review aims to highlight and to provide a comprehensive description of recent developments in hybrid nanoscale patterning strategies that enhance existing lithographic techniques or can be used to fabricate functional chemical patterns that interact with their environment. These functional structures create new capabilities, such as the fabrication of physicochemical surfaces that can recognize and capture analytes from complex liquid or gaseous mixtures. The nanolithographic techniques we describe can be classified into three general areas: traditional lithography, soft lithography and scanning-probe lithography. The strengths and limitations of each hybrid patterning technique will be discussed, along with the current and potential applications of the resulting patterned, functional surfaces.

NSCT BASED LOCAL ENHANCEMENT FOR ACTIVE CONTOUR BASED IMAGE SEGMENTATION APPLICATION

Directory of Open Access Journals (Sweden)

Hiren Mewada

2010-08-01

Full Text Available Because of cross-disciplinary nature, Active Contour modeling techniques have been utilized extensively for the image segmentation. In traditional active contour based segmentation techniques based on level set methods, the energy functions are defined based on the intensity gradient. This makes them highly sensitive to the situation where the underlying image content is characterized by image nonhomogeneities due to illumination and contrast condition. This is the most difficult problem to make them as fully automatic image segmentation techniques. This paper introduces one of the approaches based on image enhancement to this problem. The enhanced image is obtained using NonSubsampled Contourlet Transform, which improves the edges strengths in the direction where the illumination is not proper and then active contour model based on level set technique is utilized to segment the object. Experiment results demonstrate that proposed method can be utilized along with existing active contour model based segmentation method under situation characterized by intensity non-homogeneity to make them fully automatic.

Speed control with torque ripple reduction of switched reluctance motor by Hybrid Many Optimizing Liaison Gravitational Search technique

Directory of Open Access Journals (Sweden)

Nutan Saha

2017-06-01

Full Text Available This paper presents a control scheme for simultaneous control of the speed of Switched Reluctance Motor (SRM and minimizing the torque ripple employing Hybrid Many Optimizing Liaison Gravitational Search Algorithm (Hybrid MOLGSA technique. The control mechanism includes two controlling loops, the outer loop is governed for speed control and a current controller for the inner loop, intelligent selection of turn on and turn off angle for a 60 KW, 3-phase 6/8 SRM. It is noticed that the torque ripple coefficient, ISE of speed & current are reduced by 12.81%, 38.60%, 16.74% respectively by Hybrid MOLGSA algorithm compared to Gravitational Search Algorithm (GSA algorithm. It is also observed that the settling times for the controller using the parameter values for obtaining best values of torque ripple, Integral square error of speed and current are reduced by 51.25%, 58.04% and 59.375% by proposed Hybrid MOLGSA algorithm compared to the GSA algorithm.

Segmental dynamics in polymer melts by relaxation techniques and quasielastic neutron scattering

Science.gov (United States)

Colmenero, J.

1993-01-01

The dynamics of the segmental α-relaxation in three different polymeric systems, poly(vinyl methy ether) (PVME), poly(vinyl chloride) (PVC) and poly(bisphenol A, 2-hydroxypropylether) (PH) has been studied by means of relaxation techniques and quasielastic neutron scattering (backscattering spectrometers IN10 and IN13 at the ILL-Grenoble). By using these techniques we have covered a wide timescale ranging from mesoscopic to macroscopic times (10-10-101s). For analyzing the experimental data we have developed a phenomenological procedure in the frequency domain based on the Havriliak-Negami relaxation function which in fact implies a Kohlrausch-Williams-Watts relaxation function in the time domain. The results obtained indicate that the dynamics of the α-relaxation in a wide timescale shows a clear non-Debye behaviour. The shape of the relaxation function is found to be similar for the different techniques used and independent of temperature and momentum transfer (Q). Moreover the characteristic relaxation times deduced from the fitting of the experimental data can also be described using only one Vogel-Fulcher functional form. Besides we found that the Q-dependence of the relaxation times obtained by QENS is given by a power law, τ(Q) propto Q-n (n > 2) n being dependent on the system, and that the Q-behaviour and the non-Debye behaviour are directly correlated. We discuss this correlation taking into account several data of the dynamics of the α-relaxation previously reported in the literature. We also outline a possible scenario for explaining this empirical correlation.

Multidimensional Brain MRI segmentation using graph cuts

International Nuclear Information System (INIS)

Lecoeur, Jeremy

2010-01-01

This thesis deals with the segmentation of multimodal brain MRIs by graph cuts method. First, we propose a method that utilizes three MRI modalities by merging them. The border information given by the spectral gradient is then challenged by a region information, given by the seeds selected by the user, using a graph cut algorithm. Then, we propose three enhancements of this method. The first consists in finding an optimal spectral space because the spectral gradient is based on natural images and then inadequate for multimodal medical images. This results in a learning based segmentation method. We then explore the automation of the graph cut method. Here, the various pieces of information usually given by the user are inferred from a robust expectation-maximization algorithm. We show the performance of these two enhanced versions on multiple sclerosis lesions. Finally, we integrate atlases for the automatic segmentation of deep brain structures. These three new techniques show the adaptability of our method to various problems. Our different segmentation methods are better than most of nowadays techniques, speaking of computation time or segmentation accuracy. (authors)

Automatic Segmentation of Dermoscopic Images by Iterative Classification

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Maciel Zortea

2011-01-01

Full Text Available Accurate detection of the borders of skin lesions is a vital first step for computer aided diagnostic systems. This paper presents a novel automatic approach to segmentation of skin lesions that is particularly suitable for analysis of dermoscopic images. Assumptions about the image acquisition, in particular, the approximate location and color, are used to derive an automatic rule to select small seed regions, likely to correspond to samples of skin and the lesion of interest. The seed regions are used as initial training samples, and the lesion segmentation problem is treated as binary classification problem. An iterative hybrid classification strategy, based on a weighted combination of estimated posteriors of a linear and quadratic classifier, is used to update both the automatically selected training samples and the segmentation, increasing reliability and final accuracy, especially for those challenging images, where the contrast between the background skin and lesion is low.

NATIONWIDE HYBRID CHANGE DETECTION OF BUILDINGS

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V. Hron

2016-06-01

Full Text Available The Fundamental Base of Geographic Data of the Czech Republic (hereinafter FBGD is a national 2D geodatabase at a 1:10,000 scale with more than 100 geographic objects. This paper describes the design of the permanent updating mechanism of buildings in FBGD. The proposed procedure belongs to the category of hybrid change detection (HCD techniques which combine pixel-based and object-based evaluation. The main sources of information for HCD are cadastral information and bi-temporal vertical digital aerial photographs. These photographs have great information potential because they contain multispectral, position and also elevation information. Elevation information represents a digital surface model (DSM which can be obtained using the image matching technique. Pixel-based evaluation of bi-temporal DSMs enables fast localization of places with potential building changes. These coarse results are subsequently classified through the object-based image analysis (OBIA using spectral, textural and contextual features and GIS tools. The advantage of the two-stage evaluation is the pre-selection of locations where image segmentation (a computationally demanding part of OBIA is performed. It is not necessary to apply image segmentation to the entire scene, but only to the surroundings of detected changes, which contributes to significantly faster processing and lower hardware requirements. The created technology is based on open-source software solutions that allow easy portability on multiple computers and parallelization of processing. This leads to significant savings of financial resources which can be expended on the further development of FBGD.

Parallel Implementation of the Recursive Approximation of an Unsupervised Hierarchical Segmentation Algorithm. Chapter 5

Science.gov (United States)

Tilton, James C.; Plaza, Antonio J. (Editor); Chang, Chein-I. (Editor)

2008-01-01

The hierarchical image segmentation algorithm (referred to as HSEG) is a hybrid of hierarchical step-wise optimization (HSWO) and constrained spectral clustering that produces a hierarchical set of image segmentations. HSWO is an iterative approach to region grooving segmentation in which the optimal image segmentation is found at N(sub R) regions, given a segmentation at N(sub R+1) regions. HSEG's addition of constrained spectral clustering makes it a computationally intensive algorithm, for all but, the smallest of images. To counteract this, a computationally efficient recursive approximation of HSEG (called RHSEG) has been devised. Further improvements in processing speed are obtained through a parallel implementation of RHSEG. This chapter describes this parallel implementation and demonstrates its computational efficiency on a Landsat Thematic Mapper test scene.

Managing hybrid marketing systems.

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Moriarty, R T; Moran, U

1990-01-01

As competition increases and costs become critical, companies that once went to market only one way are adding new channels and using new methods - creating hybrid marketing systems. These hybrid marketing systems hold the promise of greater coverage and reduced costs. But they are also hard to manage; they inevitably raise questions of conflict and control: conflict because marketing units compete for customers; control because new indirect channels are less subject to management authority. Hard as they are to manage, however, hybrid marketing systems promise to become the dominant design, replacing the "purebred" channel strategy in all kinds of businesses. The trick to managing the hybrid is to analyze tasks and channels within and across a marketing system. A map - the hybrid grid - can help managers make sense of their hybrid system. What the chart reveals is that channels are not the basic building blocks of a marketing system; marketing tasks are. The hybrid grid forces managers to consider various combinations of channels and tasks that will optimize both cost and coverage. Managing conflict is also an important element of a successful hybrid system. Managers should first acknowledge the inevitability of conflict. Then they should move to bound it by creating guidelines that spell out which customers to serve through which methods. Finally, a marketing and sales productivity (MSP) system, consisting of a central marketing database, can act as the central nervous system of a hybrid marketing system, helping managers create customized channels and service for specific customer segments.

Study of the morphology exhibited by linear segmented polyurethanes

International Nuclear Information System (INIS)

Pereira, I.M.; Orefice, R.L.

2009-01-01

Five series of segmented polyurethanes with different hard segment content were prepared by the prepolymer mixing method. The nano-morphology of the obtained polyurethanes and their microphase separation were investigated by infrared spectroscopy, modulated differential scanning calorimetry and small-angle X-ray scattering. Although highly hydrogen bonded hard segments were formed, high hard segment contents promoted phase mixture and decreased the chain mobility, decreasing the hard segment domain precipitation and the soft segments crystallization. The applied techniques were able to show that the hard-segment content and the hard-segment interactions were the two controlling factors for determining the structure of segmented polyurethanes. (author)

A comprehensive overview of hybrid electric vehicle: Powertrain configurations, powertrain control techniques and electronic control units

Energy Technology Data Exchange (ETDEWEB)

Cagatay Bayindir, Kamil; Goezuekuecuek, Mehmet Ali; Teke, Ahmet [Cukurova University, Department of Electrical and Electronics Engineering, Balcali, Saricam, Adana (Turkey)

2011-02-15

The studies for hybrid electrical vehicle (HEV) have attracted considerable attention because of the necessity of developing alternative methods to generate energy for vehicles due to limited fuel based energy, global warming and exhaust emission limits in the last century. HEV incorporates internal composition engine, electric machines and power electronic equipments. In this study, overview of HEVs with a focus on hybrid configurations, energy management strategies and electronic control units are presented. Advantages and disadvantages of each configuration are clearly emphasized. The existing powertrain control techniques for HEVs are classified and comprehensively described. Electronic control units used in HEV configuration are also elaborated. The latest trends and technological challenges in the near future for HEVs are discussed. (author)

Multi-Wave and Hybrid Imaging Techniques: A New Direction for Nondestructive Testing and Structural Health Monitoring

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Yuhua Cheng

2013-11-01

Full Text Available In this article, the state-of-the-art multi-wave and hybrid imaging techniques in the field of nondestructive evaluation and structural health monitoring were comprehensively reviewed. A new direction for assessment and health monitoring of various structures by capitalizing the advantages of those imaging methods was discussed. Although sharing similar system configurations, the imaging physics and principles of multi-wave phenomena and hybrid imaging methods are inherently different. After a brief introduction of nondestructive evaluation (NDE , structure health monitoring (SHM and their related challenges, several recent advances that have significantly extended imaging methods from laboratory development into practical applications were summarized, followed by conclusions and discussion on future directions.

The benefits of segmentation: Evidence from a South African bank and other studies

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Douw G. Breed

2017-09-01

Full Text Available We applied different modelling techniques to six data sets from different disciplines in the industry, on which predictive models can be developed, to demonstrate the benefit of segmentation in linear predictive modelling. We compared the model performance achieved on the data sets to the performance of popular non-linear modelling techniques, by first segmenting the data (using unsupervised, semi-supervised, as well as supervised methods and then fitting a linear modelling technique. A total of eight modelling techniques was compared. We show that there is no one single modelling technique that always outperforms on the data sets. Specifically considering the direct marketing data set from a local South African bank, it is observed that gradient boosting performed the best. Depending on the characteristics of the data set, one technique may outperform another. We also show that segmenting the data benefits the performance of the linear modelling technique in the predictive modelling context on all data sets considered. Specifically, of the three segmentation methods considered, the semi-supervised segmentation appears the most promising. Significance: The use of non-linear modelling techniques may not necessarily increase model performance when data sets are first segmented. No single modelling technique always performed the best. Applications of predictive modelling are unlimited; some examples of areas of application include database marketing applications; financial risk management models; fraud detection methods; medical and environmental predictive models.

A new iterative triclass thresholding technique in image segmentation.

Science.gov (United States)

Cai, Hongmin; Yang, Zhong; Cao, Xinhua; Xia, Weiming; Xu, Xiaoyin

2014-03-01

We present a new method in image segmentation that is based on Otsu's method but iteratively searches for subregions of the image for segmentation, instead of treating the full image as a whole region for processing. The iterative method starts with Otsu's threshold and computes the mean values of the two classes as separated by the threshold. Based on the Otsu's threshold and the two mean values, the method separates the image into three classes instead of two as the standard Otsu's method does. The first two classes are determined as the foreground and background and they will not be processed further. The third class is denoted as a to-be-determined (TBD) region that is processed at next iteration. At the succeeding iteration, Otsu's method is applied on the TBD region to calculate a new threshold and two class means and the TBD region is again separated into three classes, namely, foreground, background, and a new TBD region, which by definition is smaller than the previous TBD regions. Then, the new TBD region is processed in the similar manner. The process stops when the Otsu's thresholds calculated between two iterations is less than a preset threshold. Then, all the intermediate foreground and background regions are, respectively, combined to create the final segmentation result. Tests on synthetic and real images showed that the new iterative method can achieve better performance than the standard Otsu's method in many challenging cases, such as identifying weak objects and revealing fine structures of complex objects while the added computational cost is minimal.

Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue

Science.gov (United States)

Sawyer, Travis W.; Rice, Photini F. S.; Sawyer, David M.; Koevary, Jennifer W.; Barton, Jennifer K.

2018-02-01

Ovarian cancer has the lowest survival rate among all gynecologic cancers due to predominantly late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Optical coherence tomography (OCT) is an emerging technique that provides depthresolved, high-resolution images of biological tissue in real time and demonstrates great potential for imaging of ovarian tissue. Mouse models are crucial to quantitatively assess the diagnostic potential of OCT for ovarian cancer imaging; however, due to small organ size, the ovaries must rst be separated from the image background using the process of segmentation. Manual segmentation is time-intensive, as OCT yields three-dimensional data. Furthermore, speckle noise complicates OCT images, frustrating many processing techniques. While much work has investigated noise-reduction and automated segmentation for retinal OCT imaging, little has considered the application to the ovaries, which exhibit higher variance and inhomogeneity than the retina. To address these challenges, we evaluated a set of algorithms to segment OCT images of mouse ovaries. We examined ve preprocessing techniques and six segmentation algorithms. While all pre-processing methods improve segmentation, Gaussian filtering is most effective, showing an improvement of 32% +/- 1.2%. Of the segmentation algorithms, active contours performs best, segmenting with an accuracy of 0.948 +/- 0.012 compared with manual segmentation (1.0 being identical). Nonetheless, further optimization could lead to maximizing the performance for segmenting OCT images of the ovaries.

High luminescent fibers with hybrid SiO2-coated CdTe nanocrystals fabricated by electrospinning technique

International Nuclear Information System (INIS)

Cao, Yongqiang; Liu, Ning; Yang, Ping; Shi, Ruixia; Ma, Qian; Zhang, Aiyu; Zhu, Yuanna; Wang, Junpeng; Wang, Jianrong

2015-01-01

The polyvinylpyrrolidone (PVP) hybrid luminescent micro-/nanofibers doped with the novel hybrid SiO 2 -coated CdTe nanocrystals (HS-CdTe NCs) have been fabricated for the first time via the electrospinning technique. The morphologies and photoluminescence (PL) emissions of HS-CdTe/PVP micro-/nanofibers prepared by doping the HS-CdTe NCs with the different PL peak wavelength (571, 616, and 643 nm) in PVP fibers were investigated by optical and PL microscope. The results revealed that all the HS-CdTe/PVP hybrid fibers showed an ultralong length for several hundreds of micrometers and a relatively uniform diameter of 1000 ∼ 1200 nm. The hybrid fibers displayed a wavelength-tunable PL emission, determining by the PL of doped HS-CdTe NCs. Moreover, similar to the original PL properties of HS-CdTe NCs before the electrospinning, the HS-CdTe/PVP fibers also showed a series of superior PL properties, such as narrow and symmetry PL spectrum, high, and uniform brightness. For comparison purpose, we also prepared three CdTe/PVP hybrid fibers by doping the 553 nm, 600 nm, and 633 nm PL-emitting CdTe NCs respectively in PVP electrospinning fibers. The characterization results showed that, the obtained three CdTe/PVP hybrid fibers had a basically satisfactory micro-/nanofiber morphology with a long length and relatively uniform diameter, but all the fibers exhibited very weak PL emissions. The enormous contrast in PL properties between HS-CdTe/PVP and CdTe/PVP fibers should mainly be ascribed to the different connection modes of ligands with the NCs and the passivation effect of inert hybrid silica shell on HS-CdTe. It is hopeful that the high luminescent HS-CdTe/PVP micro-/nanofibers with the tunable PL peak wavelength would be a good candidate in the optical sensor, light-emitting devices (LEDs), nanometer-scale waveguides, and the other related photonic materials. - Highlights: • The HS-CdTe/PVP electrospun hybrid fibers were fabricated for the first time. • The

Segmentation of DTI based on tensorial morphological gradient

Science.gov (United States)

Rittner, Leticia; de Alencar Lotufo, Roberto

2009-02-01

This paper presents a segmentation technique for diffusion tensor imaging (DTI). This technique is based on a tensorial morphological gradient (TMG), defined as the maximum dissimilarity over the neighborhood. Once this gradient is computed, the tensorial segmentation problem becomes an scalar one, which can be solved by conventional techniques, such as watershed transform and thresholding. Similarity functions, namely the dot product, the tensorial dot product, the J-divergence and the Frobenius norm, were compared, in order to understand their differences regarding the measurement of tensor dissimilarities. The study showed that the dot product and the tensorial dot product turned out to be inappropriate for computation of the TMG, while the Frobenius norm and the J-divergence were both capable of measuring tensor dissimilarities, despite the distortion of Frobenius norm, since it is not an affine invariant measure. In order to validate the TMG as a solution for DTI segmentation, its computation was performed using distinct similarity measures and structuring elements. TMG results were also compared to fractional anisotropy. Finally, synthetic and real DTI were used in the method validation. Experiments showed that the TMG enables the segmentation of DTI by watershed transform or by a simple choice of a threshold. The strength of the proposed segmentation method is its simplicity and robustness, consequences of TMG computation. It enables the use, not only of well-known algorithms and tools from the mathematical morphology, but also of any other segmentation method to segment DTI, since TMG computation transforms tensorial images in scalar ones.

Automatic labeling and segmentation of vertebrae in CT images

Science.gov (United States)

Rasoulian, Abtin; Rohling, Robert N.; Abolmaesumi, Purang

2014-03-01

Labeling and segmentation of the spinal column from CT images is a pre-processing step for a range of image- guided interventions. State-of-the art techniques have focused either on image feature extraction or template matching for labeling of the vertebrae followed by segmentation of each vertebra. Recently, statistical multi- object models have been introduced to extract common statistical characteristics among several anatomies. In particular, we have created models for segmentation of the lumbar spine which are robust, accurate, and computationally tractable. In this paper, we reconstruct a statistical multi-vertebrae pose+shape model and utilize it in a novel framework for labeling and segmentation of the vertebra in a CT image. We validate our technique in terms of accuracy of the labeling and segmentation of CT images acquired from 56 subjects. The method correctly labels all vertebrae in 70% of patients and is only one level off for the remaining 30%. The mean distance error achieved for the segmentation is 2.1 +/- 0.7 mm.

Simultaneous Binding of Hybrid Molecules Constructed with Dual DNA-Binding Components to a G-Quadruplex and Its Proximal Duplex.

Science.gov (United States)

Asamitsu, Sefan; Obata, Shunsuke; Phan, Anh Tuân; Hashiya, Kaori; Bando, Toshikazu; Sugiyama, Hiroshi

2018-03-20

A G-quadruplex (quadruplex) is a nucleic acid secondary structure adopted by guanine-rich sequences and is considered to be relevant to various pharmacological and biological contexts. Although a number of researchers have endeavored to discover and develop quadruplex-interactive molecules, poor ligand designability originating from topological similarity of the skeleton of diverse quadruplexes has remained a bottleneck for gaining specificity for individual quadruplexes. This work reports on hybrid molecules that were constructed with dual DNA-binding components, a cyclic imidazole/lysine polyamide (cIKP), and a hairpin pyrrole/imidazole polyamide (hPIP), with the aim toward specific quadruplex targeting by reading out the local duplex DNA sequence adjacent to designated quadruplexes in the genome. By means of circular dichroism (CD), fluorescence resonance energy transfer (FRET), surface plasmon resonance (SPR), and NMR techniques, we showed the dual and simultaneous recognition of the respective segment via hybrid molecules, and the synergistic and mutual effect of each binding component that was appropriately linked on higher binding affinity and modest sequence specificity. Monitoring quadruplex and duplex imino protons of the quadruplex/duplex motif titrated with hybrid molecules clearly revealed distinct features of the binding of hybrid molecules to the respective segments upon their simultaneous recognition. A series of the systematic and detailed binding assays described here showed that the concept of simultaneous recognition of quadruplex and its proximal duplex by hybrid molecules constructed with the dual DNA-binding components may provide a new strategy for ligand design, enabling targeting of a large variety of designated quadruplexes at specific genome locations. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multilevel Image Segmentation Based on an Improved Firefly Algorithm

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Kai Chen

2016-01-01

Full Text Available Multilevel image segmentation is time-consuming and involves large computation. The firefly algorithm has been applied to enhancing the efficiency of multilevel image segmentation. However, in some cases, firefly algorithm is easily trapped into local optima. In this paper, an improved firefly algorithm (IFA is proposed to search multilevel thresholds. In IFA, in order to help fireflies escape from local optima and accelerate the convergence, two strategies (i.e., diversity enhancing strategy with Cauchy mutation and neighborhood strategy are proposed and adaptively chosen according to different stagnation stations. The proposed IFA is compared with three benchmark optimal algorithms, that is, Darwinian particle swarm optimization, hybrid differential evolution optimization, and firefly algorithm. The experimental results show that the proposed method can efficiently segment multilevel images and obtain better performance than the other three methods.

[Cotton identification and extraction using near infrared sensor and object-oriented spectral segmentation technique].

Science.gov (United States)

Deng, Jin-Song; Shi, Yuan-Yuan; Chen, Li-Su; Wang, Ke; Zhu, Jin-Xia

2009-07-01

The real-time, effective and reliable method of identifying crop is the foundation of scientific management for crop in the precision agriculture. It is also one of the key techniques for the precision agriculture. However, this expectation cannot be fulfilled by the traditional pixel-based information extraction method with respect to complicated image processing and accurate objective identification. In the present study, visible-near infrared image of cotton was acquired using high-resolution sensor. Object-oriented segmentation technique was performed on the image to produce image objects and spatial/spectral features of cotton. Afterwards, nearest neighbor classifier integrated the spectral, shape and topologic information of image objects to precisely identify cotton according to various features. Finally, 300 random samples and an error matrix were applied to undertake the accuracy assessment of identification. Although errors and confusion exist, this method shows satisfying results with an overall accuracy of 96.33% and a KAPPA coefficient of 0.926 7, which can meet the demand of automatic management and decision-making in precision agriculture.

Hybrid Clustering-GWO-NARX neural network technique in predicting stock price

Science.gov (United States)

Das, Debashish; Safa Sadiq, Ali; Mirjalili, Seyedali; Noraziah, A.

2017-09-01

Prediction of stock price is one of the most challenging tasks due to nonlinear nature of the stock data. Though numerous attempts have been made to predict the stock price by applying various techniques, yet the predicted price is not always accurate and even the error rate is high to some extent. Consequently, this paper endeavours to determine an efficient stock prediction strategy by implementing a combinatorial method of Grey Wolf Optimizer (GWO), Clustering and Non Linear Autoregressive Exogenous (NARX) Technique. The study uses stock data from prominent stock market i.e. New York Stock Exchange (NYSE), NASDAQ and emerging stock market i.e. Malaysian Stock Market (Bursa Malaysia), Dhaka Stock Exchange (DSE). It applies K-means clustering algorithm to determine the most promising cluster, then MGWO is used to determine the classification rate and finally the stock price is predicted by applying NARX neural network algorithm. The prediction performance gained through experimentation is compared and assessed to guide the investors in making investment decision. The result through this technique is indeed promising as it has shown almost precise prediction and improved error rate. We have applied the hybrid Clustering-GWO-NARX neural network technique in predicting stock price. We intend to work with the effect of various factors in stock price movement and selection of parameters. We will further investigate the influence of company news either positive or negative in stock price movement. We would be also interested to predict the Stock indices.

Comparing Individual Tree Segmentation Based on High Resolution Multispectral Image and Lidar Data

Science.gov (United States)

Xiao, P.; Kelly, M.; Guo, Q.

2014-12-01

This study compares the use of high-resolution multispectral WorldView images and high density Lidar data for individual tree segmentation. The application focuses on coniferous and deciduous forests in the Sierra Nevada Mountains. The tree objects are obtained in two ways: a hybrid region-merging segmentation method with multispectral images, and a top-down and bottom-up region-growing method with Lidar data. The hybrid region-merging method is used to segment individual tree from multispectral images. It integrates the advantages of global-oriented and local-oriented region-merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region. The merging iterations are constrained within the local vicinity, thus the segmentation is accelerated and can reflect the local context. The top-down region-growing method is adopted in coniferous forest to delineate individual tree from Lidar data. It exploits the spacing between the tops of trees to identify and group points into a single tree based on simple rules of proximity and likely tree shape. The bottom-up region-growing method based on the intensity and 3D structure of Lidar data is applied in deciduous forest. It segments tree trunks based on the intensity and topological relationships of the points, and then allocate other points to exact tree crowns according to distance. The accuracies for each method are evaluated with field survey data in several test sites, covering dense and sparse canopy. Three types of segmentation results are produced: true positive represents a correctly segmented individual tree, false negative represents a tree that is not detected and assigned to a nearby tree, and false positive represents that a point or pixel cluster is segmented as a tree that does not in fact exist. They respectively represent correct-, under-, and over-segmentation. Three types of index are compared for segmenting individual tree

Cellular image segmentation using n-agent cooperative game theory

Science.gov (United States)

Dimock, Ian B.; Wan, Justin W. L.

2016-03-01

Image segmentation is an important problem in computer vision and has significant applications in the segmentation of cellular images. Many different imaging techniques exist and produce a variety of image properties which pose difficulties to image segmentation routines. Bright-field images are particularly challenging because of the non-uniform shape of the cells, the low contrast between cells and background, and imaging artifacts such as halos and broken edges. Classical segmentation techniques often produce poor results on these challenging images. Previous attempts at bright-field imaging are often limited in scope to the images that they segment. In this paper, we introduce a new algorithm for automatically segmenting cellular images. The algorithm incorporates two game theoretic models which allow each pixel to act as an independent agent with the goal of selecting their best labelling strategy. In the non-cooperative model, the pixels choose strategies greedily based only on local information. In the cooperative model, the pixels can form coalitions, which select labelling strategies that benefit the entire group. Combining these two models produces a method which allows the pixels to balance both local and global information when selecting their label. With the addition of k-means and active contour techniques for initialization and post-processing purposes, we achieve a robust segmentation routine. The algorithm is applied to several cell image datasets including bright-field images, fluorescent images and simulated images. Experiments show that the algorithm produces good segmentation results across the variety of datasets which differ in cell density, cell shape, contrast, and noise levels.

Rendezvous technique for recanalization of long-segmental chronic total occlusion above the knee following unsuccessful standard angioplasty.

Science.gov (United States)

Cao, Jun; Lu, Hai-Tao; Wei, Li-Ming; Zhao, Jun-Gong; Zhu, Yue-Qi

2016-04-01

To assess the technical feasibility and efficacy of the rendezvous technique, a type of subintimal retrograde wiring, for the treatment of long-segmental chronic total occlusions above the knee following unsuccessful standard angioplasty. The rendezvous technique was attempted in eight limbs of eight patients with chronic total occlusions above the knee after standard angioplasty failed. The clinical symptoms and ankle-brachial index were compared before and after the procedure. At follow-up, pain relief, wound healing, limb salvage, and the presence of restenosis of the target vessels were evaluated. The rendezvous technique was performed successfully in seven patients (87.5%) and failed in one patient (12.5%). Foot pain improved in all seven patients who underwent successful treatment, with ankle-brachial indexes improving from 0.23 ± 0.13 before to 0.71 ± 0.09 after the procedure (P rendezvous technique is a feasible and effective treatment for chronic total occlusions above the knee when standard angioplasty fails. © The Author(s) 2015.

GLOBAL CLASSIFICATION OF DERMATITIS DISEASE WITH K-MEANS CLUSTERING IMAGE SEGMENTATION METHODS

OpenAIRE

Prafulla N. Aerkewar1 & Dr. G. H. Agrawal2

2018-01-01

The objective of this paper to presents a global technique for classification of different dermatitis disease lesions using the process of k-Means clustering image segmentation method. The word global is used such that the all dermatitis disease having skin lesion on body are classified in to four category using k-means image segmentation and nntool of Matlab. Through the image segmentation technique and nntool can be analyze and study the segmentation properties of skin lesions occurs in...

Robust medical image segmentation for hyperthermia treatment planning

International Nuclear Information System (INIS)

Neufeld, E.; Chavannes, N.; Kuster, N.; Samaras, T.

2005-01-01

Full text: This work is part of an ongoing effort to develop a comprehensive hyperthermia treatment planning (HTP) tool. The goal is to unify all the steps necessary to perform treatment planning - from image segmentation to optimization of the energy deposition pattern - in a single tool. The bases of the HTP software are the routines and know-how developed in our TRINTY project that resulted the commercial EM platform SEMCAD-X. It incorporates the non-uniform finite-difference time-domain (FDTD) method, permitting the simulation of highly detailed models. Subsequently, in order to create highly resolved patient models, a powerful and robust segmentation tool is needed. A toolbox has been created that allows the flexible combination of various segmentation methods as well as several pre-and postprocessing functions. It works primarily with CT and MRI images, which it can read in various formats. A wide variety of segmentation methods has been implemented. This includes thresholding techniques (k-means classification, expectation maximization and modal histogram analysis for automatic threshold detection, multi-dimensional if required), region growing methods (with hysteretic behavior and simultaneous competitive growing), an interactive marker based watershed transformation, level-set methods (homogeneity and edge based, fast-marching), a flexible live-wire implementation as well as fuzzy connectedness. Due to the large number of tissues that need to be segmented for HTP, no methods that rely on prior knowledge have been implemented. Various edge extraction routines, distance transforms, smoothing techniques (convolutions, anisotropic diffusion, sigma filter...), connected component analysis, topologically flexible interpolation, image algebra and morphological operations are available. Moreover, contours or surfaces can be extracted, simplified and exported. Using these different techniques on several samples, the following conclusions have been drawn: Due to the

Comparison of segmentation algorithms for fluorescence microscopy images of cells.

Science.gov (United States)

Dima, Alden A; Elliott, John T; Filliben, James J; Halter, Michael; Peskin, Adele; Bernal, Javier; Kociolek, Marcin; Brady, Mary C; Tang, Hai C; Plant, Anne L

2011-07-01

The analysis of fluorescence microscopy of cells often requires the determination of cell edges. This is typically done using segmentation techniques that separate the cell objects in an image from the surrounding background. This study compares segmentation results from nine different segmentation techniques applied to two different cell lines and five different sets of imaging conditions. Significant variability in the results of segmentation was observed that was due solely to differences in imaging conditions or applications of different algorithms. We quantified and compared the results with a novel bivariate similarity index metric that evaluates the degree of underestimating or overestimating a cell object. The results show that commonly used threshold-based segmentation techniques are less accurate than k-means clustering with multiple clusters. Segmentation accuracy varies with imaging conditions that determine the sharpness of cell edges and with geometric features of a cell. Based on this observation, we propose a method that quantifies cell edge character to provide an estimate of how accurately an algorithm will perform. The results of this study will assist the development of criteria for evaluating interlaboratory comparability. Published 2011 Wiley-Liss, Inc.

Muscle gap approach under a minimally invasive channel technique for treating long segmental lumbar spinal stenosis: A retrospective study.

Science.gov (United States)

Bin, Yang; De Cheng, Wang; Wei, Wang Zong; Hui, Li

2017-08-01

This study aimed to compare the efficacy of muscle gap approach under a minimally invasive channel surgical technique with the traditional median approach.In the Orthopedics Department of Traditional Chinese and Western Medicine Hospital, Tongzhou District, Beijing, 68 cases of lumbar spinal canal stenosis underwent surgery using the muscle gap approach under a minimally invasive channel technique and a median approach between September 2013 and February 2016. Both approaches adopted lumbar spinal canal decompression, intervertebral disk removal, cage implantation, and pedicle screw fixation. The operation time, bleeding volume, postoperative drainage volume, and preoperative and postoperative visual analog scale (VAS) score and Japanese Orthopedics Association score (JOA) were compared between the 2 groups.All patients were followed up for more than 1 year. No significant difference between the 2 groups was found with respect to age, gender, surgical segments. No diversity was noted in the operation time, intraoperative bleeding volume, preoperative and 1 month after the operation VAS score, preoperative and 1 month after the operation JOA score, and 6 months after the operation JOA score between 2 groups (P > .05). The amount of postoperative wound drainage (260.90 ± 160 mL vs 447.80 ± 183.60 mL, P gap approach group than in the median approach group (P gap approach under a minimally invasive channel group, the average drainage volume was reduced by 187 mL, and the average VAS score 6 months after the operation was reduced by an average of 0.48.The muscle gap approach under a minimally invasive channel technique is a feasible method to treat long segmental lumbar spinal canal stenosis. It retains the integrity of the posterior spine complex to the greatest extent, so as to reduce the adjacent spinal segmental degeneration and soft tissue trauma. Satisfactory short-term and long-term clinical results were obtained.

Color Image Segmentation Based on Different Color Space Models Using Automatic GrabCut

Directory of Open Access Journals (Sweden)

Dina Khattab

2014-01-01

Full Text Available This paper presents a comparative study using different color spaces to evaluate the performance of color image segmentation using the automatic GrabCut technique. GrabCut is considered as one of the semiautomatic image segmentation techniques, since it requires user interaction for the initialization of the segmentation process. The automation of the GrabCut technique is proposed as a modification of the original semiautomatic one in order to eliminate the user interaction. The automatic GrabCut utilizes the unsupervised Orchard and Bouman clustering technique for the initialization phase. Comparisons with the original GrabCut show the efficiency of the proposed automatic technique in terms of segmentation, quality, and accuracy. As no explicit color space is recommended for every segmentation problem, automatic GrabCut is applied with RGB, HSV, CMY, XYZ, and YUV color spaces. The comparative study and experimental results using different color images show that RGB color space is the best color space representation for the set of the images used.

WRHT: A Hybrid Technique for Detection of Wormhole Attack in Wireless Sensor Networks

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Rupinder Singh

2016-01-01

Full Text Available Wormhole attack is a challenging security threat to wireless sensor networks which results in disrupting most of the routing protocols as this attack can be triggered in different modes. In this paper, WRHT, a wormhole resistant hybrid technique, is proposed, which can detect the presence of wormhole attack in a more optimistic manner than earlier techniques. WRHT is based on the concept of watchdog and Delphi schemes and ensures that the wormhole will not be left untreated in the sensor network. WRHT makes use of the dual wormhole detection mechanism of calculating probability factor time delay probability and packet loss probability of the established path in order to find the value of wormhole presence probability. The nodes in the path are given different ranking and subsequently colors according to their behavior. The most striking feature of WRHT consists of its capacity to defend against almost all categories of wormhole attacks without depending on any required additional hardware such as global positioning system, timing information or synchronized clocks, and traditional cryptographic schemes demanding high computational needs. The experimental results clearly indicate that the proposed technique has significant improvement over the existing wormhole attack detection techniques.

Application of Genomic In Situ Hybridization in Horticultural Science

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Fahad Ramzan

2017-01-01

Full Text Available Molecular cytogenetic techniques, such as in situ hybridization methods, are admirable tools to analyze the genomic structure and function, chromosome constituents, recombination patterns, alien gene introgression, genome evolution, aneuploidy, and polyploidy and also genome constitution visualization and chromosome discrimination from different genomes in allopolyploids of various horticultural crops. Using GISH advancement as multicolor detection is a significant approach to analyze the small and numerous chromosomes in fruit species, for example, Diospyros hybrids. This analytical technique has proved to be the most exact and effective way for hybrid status confirmation and helps remarkably to distinguish donor parental genomes in hybrids such as Clivia, Rhododendron, and Lycoris ornamental hybrids. The genome characterization facilitates in hybrid selection having potential desirable characteristics during the early hybridization breeding, as this technique expedites to detect introgressed sequence chromosomes. This review study epitomizes applications and advancements of genomic in situ hybridization (GISH techniques in horticultural plants.

Identification of bacteria used for microbial enhanced oil recovery process by fluorescence in situ hybridization technique

Energy Technology Data Exchange (ETDEWEB)

Fujiwara, K.; Tanaka, S.; Otsuka, M. [Kansai Research Institute, Kyoto (Japan). Lifescience Lab.; Yonebayashi, H. [Japan National Oil Corp., Chiba (Japan). Tech. Research Center; Enomoto, H. [Tohoku University, Sendai (Japan). Dept. of Geoscience and Tech.

2000-01-01

A fluorescence in situ hybridization (FISH) technique using 16S rRNA-targeted oligonucleotide probes was developed for rapid detection of microorganisms for use in the microbial enhancement of oil recovery (MEOR) process. Two microorganisms, Enterobacter cloacae TRC-322 and Bacillus licheniformis TRC-18-2-a, were selected from a collection of Enterobacter sp. and Bacillus sp. which were screened in previous studies as candidate microorganisms for injection, and were used for this experiment. Oligonucleotide probes, design based on specific sequences in the 16S rRNA gene were labeled with either fluorescein isothiocyanate (FITC), or 6-car-boxy-X-rhodamine (ROX), and were allowed to hybridize with fixed cells of the two microorganisms noted above. The fluorescence signal emitted from each microorganism cells could clearly be detected by an epifluorescence microscope. Moreover, E. cloacae TRC-322 and B, licheniformis TRC-18-2-a, suspended in actual reservoir brine, including inorganic salts, oil and aboriginal cells of the reservoir brine, could be detected directly by this hybridization method, without the need for cultivation and isolation. (author)

Degradation of reactive orange 4 dye using hydrodynamic cavitation based hybrid techniques.

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Gore, Mohan M; Saharan, Virendra Kumar; Pinjari, Dipak V; Chavan, Prakash V; Pandit, Aniruddha B

2014-05-01

In the present work, degradation of reactive orange 4 dye (RO4) has been investigated using hydrodynamic cavitation (HC) and in combination with other AOP's. In the hybrid techniques, combination of hydrodynamic cavitation and other oxidizing agents such as H2O2 and ozone have been used to get the enhanced degradation efficiency through HC device. The hydrodynamic cavitation was first optimized in terms of different operating parameters such as operating inlet pressure, cavitation number and pH of the operating medium to get the maximum degradation of RO4. Following the optimization of HC parameters, the degradation of RO4 was carried out using the combination of HC with H2O2 and ozone. It has been found that the efficiency of the HC can be improved significantly by combining it with H2O2 and ozone. The mineralization rate of RO4 increases considerably with 14.67% mineralization taking place using HC alone increases to 31.90% by combining it with H2O2 and further increases to 76.25% through the combination of HC and ozone. The synergetic coefficient of greater than one for the hybrid processes of HC+H2O2 and HC+Ozone has suggested that the combination of HC with other oxidizing agents is better than the individual processes for the degradation of dye effluent containing RO4. The combination of HC with ozone proves to be the most energy efficient method for the degradation of RO4 as compared to HC alone and the hybrid process of HC and H2O2. Copyright © 2013 Elsevier B.V. All rights reserved.

Interactive tele-radiological segmentation systems for treatment and diagnosis.

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Zimeras, S; Gortzis, L G

2012-01-01

Telehealth is the exchange of health information and the provision of health care services through electronic information and communications technology, where participants are separated by geographic, time, social and cultural barriers. The shift of telemedicine from desktop platforms to wireless and mobile technologies is likely to have a significant impact on healthcare in the future. It is therefore crucial to develop a general information exchange e-medical system to enables its users to perform online and offline medical consultations through diagnosis. During the medical diagnosis, image analysis techniques combined with doctor's opinions could be useful for final medical decisions. Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. In medical images, segmentation has traditionally been done by human experts. Even with the aid of image processing software (computer-assisted segmentation tools), manual segmentation of 2D and 3D CT images is tedious, time-consuming, and thus impractical, especially in cases where a large number of objects must be specified. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. The main purpose of this work is to analyze segmentation techniques for the definition of anatomical structures under telemedical systems.

Interactive Tele-Radiological Segmentation Systems for Treatment and Diagnosis

Directory of Open Access Journals (Sweden)

S. Zimeras

2012-01-01

Full Text Available Telehealth is the exchange of health information and the provision of health care services through electronic information and communications technology, where participants are separated by geographic, time, social and cultural barriers. The shift of telemedicine from desktop platforms to wireless and mobile technologies is likely to have a significant impact on healthcare in the future. It is therefore crucial to develop a general information exchange e-medical system to enables its users to perform online and offline medical consultations through diagnosis. During the medical diagnosis, image analysis techniques combined with doctor’s opinions could be useful for final medical decisions. Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. In medical images, segmentation has traditionally been done by human experts. Even with the aid of image processing software (computer-assisted segmentation tools, manual segmentation of 2D and 3D CT images is tedious, time-consuming, and thus impractical, especially in cases where a large number of objects must be specified. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. The main purpose of this work is to analyze segmentation techniques for the definition of anatomical structures under telemedical systems.

Alternative radiation-free registration technique for image-guided pedicle screw placement in deformed cervico-thoracic segments.

Science.gov (United States)

Kantelhardt, Sven R; Neulen, Axel; Keric, Naureen; Gutenberg, Angelika; Conrad, Jens; Giese, Alf

2017-10-01

Image-guided pedicle screw placement in the cervico-thoracic region is a commonly applied technique. In some patients with deformed cervico-thoracic segments, conventional or 3D fluoroscopy based registration of image-guidance might be difficult or impossible because of the anatomic/pathological conditions. Landmark based registration has been used as an alternative, mostly using separate registration of each vertebra. We here investigated a routine for landmark based registration of rigid spinal segments as single objects, using cranial image-guidance software. Landmark based registration of image-guidance was performed using cranial navigation software. After surgical exposure of the spinous processes, lamina and facet joints and fixation of a reference marker array, up to 26 predefined landmarks were acquired using a pointer. All pedicle screws were implanted using image guidance alone. Following image-guided screw placement all patients underwent postoperative CT scanning. Screw positions as well as intraoperative and clinical parameters were retrospectively analyzed. Thirteen patients received 73 pedicle screws at levels C6 to Th8. Registration of spinal segments, using the cranial image-guidance succeeded in all cases. Pedicle perforations were observed in 11.0%, severe perforations of >2 mm occurred in 5.4%. One patient developed a transient C8 syndrome and had to be revised for deviation of the C7 pedicle screw. No other pedicle screw-related complications were observed. In selected patients suffering from pathologies of the cervico-thoracic region, which impair intraoperative fluoroscopy or 3D C-arm imaging, landmark based registration of image-guidance using cranial software is a feasible, radiation-saving and a safe alternative.

Lung tumor segmentation in PET images using graph cuts.

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Ballangan, Cherry; Wang, Xiuying; Fulham, Michael; Eberl, Stefan; Feng, David Dagan

2013-03-01

The aim of segmentation of tumor regions in positron emission tomography (PET) is to provide more accurate measurements of tumor size and extension into adjacent structures, than is possible with visual assessment alone and hence improve patient management decisions. We propose a segmentation energy function for the graph cuts technique to improve lung tumor segmentation with PET. Our segmentation energy is based on an analysis of the tumor voxels in PET images combined with a standardized uptake value (SUV) cost function and a monotonic downhill SUV feature. The monotonic downhill feature avoids segmentation leakage into surrounding tissues with similar or higher PET tracer uptake than the tumor and the SUV cost function improves the boundary definition and also addresses situations where the lung tumor is heterogeneous. We evaluated the method in 42 clinical PET volumes from patients with non-small cell lung cancer (NSCLC). Our method improves segmentation and performs better than region growing approaches, the watershed technique, fuzzy-c-means, region-based active contour and tumor customized downhill. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Accuracy and reproducibility of a novel semi-automatic segmentation technique for MR volumetry of the pituitary gland

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Renz, Diane M. [Charite University Medicine Berlin, Campus Virchow Clinic, Department of Radiology, Berlin (Germany); Hahn, Horst K.; Rexilius, Jan [Institute for Medical Image Computing, Fraunhofer MEVIS, Bremen (Germany); Schmidt, Peter [Friedrich-Schiller-University, Jena University Hospital, Institute of Diagnostic and Interventional Radiology, Department of Neuroradiology, Jena (Germany); Lentschig, Markus [MR- and PET/CT Centre Bremen, Bremen (Germany); Pfeil, Alexander [Friedrich-Schiller-University, Jena University Hospital, Department of Internal Medicine III, Jena (Germany); Sauner, Dieter [St. Georg Clinic Leipzig, Hospital Hubertusburg, Department of Radiology, Wermsdorf (Germany); Fitzek, Clemens [Asklepios Clinic Brandenburg, Department of Radiology and Neuroradiology, Brandenburg an der Havel (Germany); Mentzel, Hans-Joachim [Friedrich-Schiller-University, Jena University Hospital, Institute of Diagnostic and Interventional Radiology, Department of Pediatric Radiology, Jena (Germany); Kaiser, Werner A. [Friedrich-Schiller-University, Jena University Hospital, Institute of Diagnostic and Interventional Radiology, Jena (Germany); Reichenbach, Juergen R. [Friedrich-Schiller-University, Jena University Hospital, Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena (Germany); Boettcher, Joachim [SRH Clinic Gera, Institute of Diagnostic and Interventional Radiology, Gera (Germany)

2011-04-15

Although several reports about volumetric determination of the pituitary gland exist, volumetries have been solely performed by indirect measurements or manual tracing on the gland's boundaries. The purpose of this study was to evaluate the accuracy and reproducibility of a novel semi-automatic MR-based segmentation technique. In an initial technical investigation, T1-weighted 3D native magnetised prepared rapid gradient echo sequences (1.5 T) with 1 mm isotropic voxel size achieved high reliability and were utilised in different in vitro and in vivo studies. The computer-assisted segmentation technique was based on an interactive watershed transform after resampling and gradient computation. Volumetry was performed by three observers with different software and neuroradiologic experiences, evaluating phantoms of known volume (0.3, 0.9 and 1.62 ml) and healthy subjects (26 to 38 years; overall 135 volumetries). High accuracy of the volumetry was shown by phantom analysis; measurement errors were <4% with a mean error of 2.2%. In vitro, reproducibility was also promising with intra-observer variability of 0.7% for observer 1 and 0.3% for observers 2 and 3; mean inter-observer variability was in vitro 1.2%. In vivo, scan-rescan, intra-observer and inter-observer variability showed mean values of 3.2%, 1.8% and 3.3%, respectively. Unifactorial analysis of variance demonstrated no significant differences between pituitary volumes for various MR scans or software calculations in the healthy study groups (p > 0.05). The analysed semi-automatic MR volumetry of the pituitary gland is a valid, reliable and fast technique. Possible clinical applications are hyperplasia or atrophy of the gland in pathological circumstances either by a single assessment or by monitoring in follow-up studies. (orig.)

Retinal Image Preprocessing: Background and Noise Segmentation

Directory of Open Access Journals (Sweden)

Usman Akram

2012-09-01

Full Text Available Retinal images are used for the automated screening and diagnosis of diabetic retinopathy. The retinal image quality must be improved for the detection of features and abnormalities and for this purpose preprocessing of retinal images is vital. In this paper, we present a novel automated approach for preprocessing of colored retinal images. The proposed technique improves the quality of input retinal image by separating the background and noisy area from the overall image. It contains coarse segmentation and fine segmentation. Standard retinal images databases Diaretdb0, Diaretdb1, DRIVE and STARE are used to test the validation of our preprocessing technique. The experimental results show the validity of proposed preprocessing technique.

Intra- and interoperator variability of lobar pulmonary volumes and emphysema scores in patients with chronic obstructive pulmonary disease and emphysema: comparison of manual and semi-automated segmentation techniques.

Science.gov (United States)

Molinari, Francesco; Pirronti, Tommaso; Sverzellati, Nicola; Diciotti, Stefano; Amato, Michele; Paolantonio, Guglielmo; Gentile, Luigia; Parapatt, George K; D'Argento, Francesco; Kuhnigk, Jan-Martin

2013-01-01

We aimed to compare the intra- and interoperator variability of lobar volumetry and emphysema scores obtained by semi-automated and manual segmentation techniques in lung emphysema patients. In two sessions held three months apart, two operators performed lobar volumetry of unenhanced chest computed tomography examinations of 47 consecutive patients with chronic obstructive pulmonary disease and lung emphysema. Both operators used the manual and semi-automated segmentation techniques. The intra- and interoperator variability of the volumes and emphysema scores obtained by semi-automated segmentation was compared with the variability obtained by manual segmentation of the five pulmonary lobes. The intra- and interoperator variability of the lobar volumes decreased when using semi-automated lobe segmentation (coefficients of repeatability for the first operator: right upper lobe, 147 vs. 96.3; right middle lobe, 137.7 vs. 73.4; right lower lobe, 89.2 vs. 42.4; left upper lobe, 262.2 vs. 54.8; and left lower lobe, 260.5 vs. 56.5; coefficients of repeatability for the second operator: right upper lobe, 61.4 vs. 48.1; right middle lobe, 56 vs. 46.4; right lower lobe, 26.9 vs. 16.7; left upper lobe, 61.4 vs. 27; and left lower lobe, 63.6 vs. 27.5; coefficients of reproducibility in the interoperator analysis: right upper lobe, 191.3 vs. 102.9; right middle lobe, 219.8 vs. 126.5; right lower lobe, 122.6 vs. 90.1; left upper lobe, 166.9 vs. 68.7; and left lower lobe, 168.7 vs. 71.6). The coefficients of repeatability and reproducibility of emphysema scores also decreased when using semi-automated segmentation and had ranges that varied depending on the target lobe and selected threshold of emphysema. Semi-automated segmentation reduces the intra- and interoperator variability of lobar volumetry and provides a more objective tool than manual technique for quantifying lung volumes and severity of emphysema.

Segmentation of liver tumors on CT images

International Nuclear Information System (INIS)

Pescia, D.

2011-01-01

This thesis is dedicated to 3D segmentation of liver tumors in CT images. This is a task of great clinical interest since it allows physicians benefiting from reproducible and reliable methods for segmenting such lesions. Accurate segmentation would indeed help them during the evaluation of the lesions, the choice of treatment and treatment planning. Such a complex segmentation task should cope with three main scientific challenges: (i) the highly variable shape of the structures being sought, (ii) their similarity of appearance compared with their surrounding medium and finally (iii) the low signal to noise ratio being observed in these images. This problem is addressed in a clinical context through a two step approach, consisting of the segmentation of the entire liver envelope, before segmenting the tumors which are present within the envelope. We begin by proposing an atlas-based approach for computing pathological liver envelopes. Initially images are pre-processed to compute the envelopes that wrap around binary masks in an attempt to obtain liver envelopes from estimated segmentation of healthy liver parenchyma. A new statistical atlas is then introduced and used to segmentation through its diffeomorphic registration to the new image. This segmentation is achieved through the combination of image matching costs as well as spatial and appearance prior using a multi-scale approach with MRF. The second step of our approach is dedicated to lesions segmentation contained within the envelopes using a combination of machine learning techniques and graph based methods. First, an appropriate feature space is considered that involves texture descriptors being determined through filtering using various scales and orientations. Then, state of the art machine learning techniques are used to determine the most relevant features, as well as the hyper plane that separates the feature space of tumoral voxels to the ones corresponding to healthy tissues. Segmentation is then

Application of Fluorescence In Situ Hybridization (FISH) Technique for the Detection of Genetic Aberration in Medical Science

Science.gov (United States)

Ratan, Zubair Ahmed; Zaman, Sojib Bin; Haidere, Mohammad Faisal; Runa, Nusrat Jahan; Akter, Nasrin

2017-01-01

Fluorescence in situ hybridization (FISH) is a macromolecule recognition technique, which is considered as a new advent in the field of cytology. Initially, it was developed as a physical mapping tool to delineate genes within chromosomes. The accuracy and versatility of FISH were subsequently capitalized upon in biological and medical research. This visually appealing technique provides an intermediate degree of resolution between DNA analysis and chromosomal investigations. FISH consists of a hybridizing DNA probe, which can be labeled directly or indirectly. In the case of direct labeling, fluorescent nucleotides are used, while indirect labeling is incorporated with reporter molecules that are subsequently detected by fluorescent antibodies or other affinity molecules. FISH is applied to detect genetic abnormalities that include different characteristic gene fusions or the presence of an abnormal number of chromosomes in a cell or loss of a chromosomal region or a whole chromosome. It is also applied in different research applications, such as gene mapping or the identification of novel oncogenes. This article reviews the concept of FISH, its application, and its advantages in medical science.  PMID:28690958

Skill Assessment of An Hybrid Technique To Estimate Quantitative Precipitation Forecast For Galicia (nw Spain)

Science.gov (United States)

Lage, A.; Taboada, J. J.

Precipitation is the most obvious of the weather elements in its effects on normal life. Numerical weather prediction (NWP) is generally used to produce quantitative precip- itation forecast (QPF) beyond the 1-3 h time frame. These models often fail to predict small-scale variations of rain because of spin-up problems and their coarse spatial and temporal resolution (Antolik, 2000). Moreover, there are some uncertainties about the behaviour of the NWP models in extreme situations (de Bruijn and Brandsma, 2000). Hybrid techniques, combining the benefits of NWP and statistical approaches in a flexible way, are very useful to achieve a good QPF. In this work, a new technique of QPF for Galicia (NW of Spain) is presented. This region has a percentage of rainy days per year greater than 50% with quantities that may cause floods, with human and economical damages. The technique is composed of a NWP model (ARPS) and a statistical downscaling process based on an automated classification scheme of at- mospheric circulation patterns for the Iberian Peninsula (J. Ribalaygua and R. Boren, 1995). Results show that QPF for Galicia is improved using this hybrid technique. [1] Antolik, M.S. 2000 "An Overview of the National Weather Service's centralized statistical quantitative precipitation forecasts". Journal of Hydrology, 239, pp:306- 337. [2] de Bruijn, E.I.F and T. Brandsma "Rainfall prediction for a flooding event in Ireland caused by the remnants of Hurricane Charley". Journal of Hydrology, 239, pp:148-161. [3] Ribalaygua, J. and Boren R. "Clasificación de patrones espaciales de precipitación diaria sobre la España Peninsular". Informes N 3 y 4 del Servicio de Análisis e Investigación del Clima. Instituto Nacional de Meteorología. Madrid. 53 pp.

Human exposure assessment in the near field of GSM base-station antennas using a hybrid finite element/method of moments technique.

Science.gov (United States)

Meyer, Frans J C; Davidson, David B; Jakobus, Ulrich; Stuchly, Maria A

2003-02-01

A hybrid finite-element method (FEM)/method of moments (MoM) technique is employed for specific absorption rate (SAR) calculations in a human phantom in the near field of a typical group special mobile (GSM) base-station antenna. The MoM is used to model the metallic surfaces and wires of the base-station antenna, and the FEM is used to model the heterogeneous human phantom. The advantages of each of these frequency domain techniques are, thus, exploited, leading to a highly efficient and robust numerical method for addressing this type of bioelectromagnetic problem. The basic mathematical formulation of the hybrid technique is presented. This is followed by a discussion of important implementation details-in particular, the linear algebra routines for sparse, complex FEM matrices combined with dense MoM matrices. The implementation is validated by comparing results to MoM (surface equivalence principle implementation) and finite-difference time-domain (FDTD) solutions of human exposure problems. A comparison of the computational efficiency of the different techniques is presented. The FEM/MoM implementation is then used for whole-body and critical-organ SAR calculations in a phantom at different positions in the near field of a base-station antenna. This problem cannot, in general, be solved using the MoM or FDTD due to computational limitations. This paper shows that the specific hybrid FEM/MoM implementation is an efficient numerical tool for accurate assessment of human exposure in the near field of base-station antennas.

Rediscovering market segmentation.

Science.gov (United States)

Yankelovich, Daniel; Meer, David

2006-02-01

In 1964, Daniel Yankelovich introduced in the pages of HBR the concept of nondemographic segmentation, by which he meant the classification of consumers according to criteria other than age, residence, income, and such. The predictive power of marketing studies based on demographics was no longer strong enough to serve as a basis for marketing strategy, he argued. Buying patterns had become far better guides to consumers' future purchases. In addition, properly constructed nondemographic segmentations could help companies determine which products to develop, which distribution channels to sell them in, how much to charge for them, and how to advertise them. But more than 40 years later, nondemographic segmentation has become just as unenlightening as demographic segmentation had been. Today, the technique is used almost exclusively to fulfill the needs of advertising, which it serves mainly by populating commercials with characters that viewers can identify with. It is true that psychographic types like "High-Tech Harry" and "Joe Six-Pack" may capture some truth about real people's lifestyles, attitudes, self-image, and aspirations. But they are no better than demographics at predicting purchase behavior. Thus they give corporate decision makers very little idea of how to keep customers or capture new ones. Now, Daniel Yankelovich returns to these pages, with consultant David Meer, to argue the case for a broad view of nondemographic segmentation. They describe the elements of a smart segmentation strategy, explaining how segmentations meant to strengthen brand identity differ from those capable of telling a company which markets it should enter and what goods to make. And they introduce their "gravity of decision spectrum", a tool that focuses on the form of consumer behavior that should be of the greatest interest to marketers--the importance that consumers place on a product or product category.

Fast Appearance Modeling for Automatic Primary Video Object Segmentation.

Science.gov (United States)

Yang, Jiong; Price, Brian; Shen, Xiaohui; Lin, Zhe; Yuan, Junsong

2016-02-01

Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.

A hybrid method based on a new clustering technique and multilayer perceptron neural networks for hourly solar radiation forecasting

International Nuclear Information System (INIS)

Azimi, R.; Ghayekhloo, M.; Ghofrani, M.

2016-01-01

Highlights: • A novel clustering approach is proposed based on the data transformation approach. • A novel cluster selection method based on correlation analysis is presented. • The proposed hybrid clustering approach leads to deep learning for MLPNN. • A hybrid forecasting method is developed to predict solar radiations. • The evaluation results show superior performance of the proposed forecasting model. - Abstract: Accurate forecasting of renewable energy sources plays a key role in their integration into the grid. This paper proposes a hybrid solar irradiance forecasting framework using a Transformation based K-means algorithm, named TB K-means, to increase the forecast accuracy. The proposed clustering method is a combination of a new initialization technique, K-means algorithm and a new gradual data transformation approach. Unlike the other K-means based clustering methods which are not capable of providing a fixed and definitive answer due to the selection of different cluster centroids for each run, the proposed clustering provides constant results for different runs of the algorithm. The proposed clustering is combined with a time-series analysis, a novel cluster selection algorithm and a multilayer perceptron neural network (MLPNN) to develop the hybrid solar radiation forecasting method for different time horizons (1 h ahead, 2 h ahead, …, 48 h ahead). The performance of the proposed TB K-means clustering is evaluated using several different datasets and compared with different variants of K-means algorithm. Solar datasets with different solar radiation characteristics are also used to determine the accuracy and processing speed of the developed forecasting method with the proposed TB K-means and other clustering techniques. The results of direct comparison with other well-established forecasting models demonstrate the superior performance of the proposed hybrid forecasting method. Furthermore, a comparative analysis with the benchmark solar

Optical Character Recognition Using Active Contour Segmentation

Directory of Open Access Journals (Sweden)

Nabeel Oudah

2018-01-01

Full Text Available Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the active contour algorithm could be applied in the segmentation process. The Tesseract OCR Engine was selected in order to evaluate the performance and identification accuracy of the proposed method. The results showed that a more accurate segmentation process shall lead to a more accurate recognition results. The rate of recognition accuracy was 0.95 for the proposed algorithm compared with 0.85 for the Tesseract OCR Engine.

Current status of hybrid coronary revascularization.

Science.gov (United States)

Jaik, Nikhil P; Umakanthan, Ramanan; Leacche, Marzia; Solenkova, Natalia; Balaguer, Jorge M; Hoff, Steven J; Ball, Stephen K; Zhao, David X; Byrne, John G

2011-10-01

Hybrid coronary revascularization combines coronary artery bypass surgery with percutaneous coronary intervention techniques to treat coronary artery disease. The potential benefits of such a technique are to offer the patients the best available treatments for coronary artery disease while minimizing the risks of the surgery. Hybrid coronary revascularization has resulted in the establishment of new 'hybrid operating suites', which incorporate and integrate the capabilities of a cardiac surgery operating room with that of an interventional cardiology laboratory. Hybrid coronary revascularization has greatly augmented teamwork and cooperation between both fields and has demonstrated encouraging as well as good initial outcomes.

Fetal brain volumetry through MRI volumetric reconstruction and segmentation

Science.gov (United States)

Estroff, Judy A.; Barnewolt, Carol E.; Connolly, Susan A.; Warfield, Simon K.

2013-01-01

Purpose Fetal MRI volumetry is a useful technique but it is limited by a dependency upon motion-free scans, tedious manual segmentation, and spatial inaccuracy due to thick-slice scans. An image processing pipeline that addresses these limitations was developed and tested. Materials and methods The principal sequences acquired in fetal MRI clinical practice are multiple orthogonal single-shot fast spin echo scans. State-of-the-art image processing techniques were used for inter-slice motion correction and super-resolution reconstruction of high-resolution volumetric images from these scans. The reconstructed volume images were processed with intensity non-uniformity correction and the fetal brain extracted by using supervised automated segmentation. Results Reconstruction, segmentation and volumetry of the fetal brains for a cohort of twenty-five clinically acquired fetal MRI scans was done. Performance metrics for volume reconstruction, segmentation and volumetry were determined by comparing to manual tracings in five randomly chosen cases. Finally, analysis of the fetal brain and parenchymal volumes was performed based on the gestational age of the fetuses. Conclusion The image processing pipeline developed in this study enables volume rendering and accurate fetal brain volumetry by addressing the limitations of current volumetry techniques, which include dependency on motion-free scans, manual segmentation, and inaccurate thick-slice interpolation. PMID:20625848

CLG for Automatic Image Segmentation

OpenAIRE

Christo Ananth; S.Santhana Priya; S.Manisha; T.Ezhil Jothi; M.S.Ramasubhaeswari

2017-01-01

This paper proposes an automatic segmentation method which effectively combines Active Contour Model, Live Wire method and Graph Cut approach (CLG). The aim of Live wire method is to provide control to the user on segmentation process during execution. Active Contour Model provides a statistical model of object shape and appearance to a new image which are built during a training phase. In the graph cut technique, each pixel is represented as a node and the distance between those nodes is rep...

Scorpion image segmentation system

Science.gov (United States)

Joseph, E.; Aibinu, A. M.; Sadiq, B. A.; Bello Salau, H.; Salami, M. J. E.

2013-12-01

Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital image processing approach based on the floresencing characteristics of Scorpion under Ultra-violet (UV) light for automatic detection and identification of scorpion. The acquired UV-based images undergo pre-processing to equalize uneven illumination and colour space channel separation. The extracted channels are then segmented into two non-overlapping classes. It has been observed that simple thresholding of the green channel of the acquired RGB UV-based image is sufficient for segmenting Scorpion from other background components in the acquired image. Two approaches to image segmentation have also been proposed in this work, namely, the simple average segmentation technique and K-means image segmentation. The proposed algorithm has been tested on over 40 UV scorpion images obtained from different part of the world and results obtained show an average accuracy of 97.7% in correctly classifying the pixel into two non-overlapping clusters. The proposed 1system will eliminate the problem associated with some of the existing manual approaches presently in use for scorpion detection.

Retina image–based optic disc segmentation

Directory of Open Access Journals (Sweden)

Ching-Lin Wang

2016-05-01

Full Text Available The change of optic disc can be used to diagnose many eye diseases, such as glaucoma, diabetic retinopathy and macular degeneration. Moreover, retinal blood vessel pattern is unique for human beings even for identical twins. It is a highly stable pattern in biometric identification. Since optic disc is the beginning of the optic nerve and main blood vessels in retina, it can be used as a reference point of identification. Therefore, optic disc segmentation is an important technique for developing a human identity recognition system and eye disease diagnostic system. This article hence presents an optic disc segmentation method to extract the optic disc from a retina image. The experimental results show that the optic disc segmentation method can give impressive results in segmenting the optic disc from a retina image.

Learning-based automated segmentation of the carotid artery vessel wall in dual-sequence MRI using subdivision surface fitting.

Science.gov (United States)

Gao, Shan; van 't Klooster, Ronald; Kitslaar, Pieter H; Coolen, Bram F; van den Berg, Alexandra M; Smits, Loek P; Shahzad, Rahil; Shamonin, Denis P; de Koning, Patrick J H; Nederveen, Aart J; van der Geest, Rob J

2017-10-01

The quantification of vessel wall morphology and plaque burden requires vessel segmentation, which is generally performed by manual delineations. The purpose of our work is to develop and evaluate a new 3D model-based approach for carotid artery wall segmentation from dual-sequence MRI. The proposed method segments the lumen and outer wall surfaces including the bifurcation region by fitting a subdivision surface constructed hierarchical-tree model to the image data. In particular, a hybrid segmentation which combines deformable model fitting with boundary classification was applied to extract the lumen surface. The 3D model ensures the correct shape and topology of the carotid artery, while the boundary classification uses combined image information of 3D TOF-MRA and 3D BB-MRI to promote accurate delineation of the lumen boundaries. The proposed algorithm was validated on 25 subjects (48 arteries) including both healthy volunteers and atherosclerotic patients with 30% to 70% carotid stenosis. For both lumen and outer wall border detection, our result shows good agreement between manually and automatically determined contours, with contour-to-contour distance less than 1 pixel as well as Dice overlap greater than 0.87 at all different carotid artery sections. The presented 3D segmentation technique has demonstrated the capability of providing vessel wall delineation for 3D carotid MRI data with high accuracy and limited user interaction. This brings benefits to large-scale patient studies for assessing the effect of pharmacological treatment of atherosclerosis by reducing image analysis time and bias between human observers. © 2017 American Association of Physicists in Medicine.

Alveolar bone-loss area localization in periodontitis radiographs based on threshold segmentation with a hybrid feature fused of intensity and the H-value of fractional Brownian motion model.

Science.gov (United States)

Lin, P L; Huang, P W; Huang, P Y; Hsu, H C

2015-10-01

Periodontitis involves progressive loss of alveolar bone around the teeth. Hence, automatic alveolar bone-loss (ABL) measurement in periapical radiographs can assist dentists in diagnosing such disease. In this paper, we propose an effective method for ABL area localization and denote it as ABLIfBm. ABLIfBm is a threshold segmentation method that uses a hybrid feature fused of both intensity and texture measured by the H-value of fractional Brownian motion (fBm) model, where the H-value is the Hurst coefficient in the expectation function of a fBm curve (intensity change) and is directly related to the value of fractal dimension. Adopting leave-one-out cross validation training and testing mechanism, ABLIfBm trains weights for both features using Bayesian classifier and transforms the radiograph image into a feature image obtained from a weighted average of both features. Finally, by Otsu's thresholding, it segments the feature image into normal and bone-loss regions. Experimental results on 31 periodontitis radiograph images in terms of mean true positive fraction and false positive fraction are about 92.5% and 14.0%, respectively, where the ground truth is provided by a dentist. The results also demonstrate that ABLIfBm outperforms (a) the threshold segmentation method using either feature alone or a weighted average of the same two features but with weights trained differently; (b) a level set segmentation method presented earlier in literature; and (c) segmentation methods based on Bayesian, K-NN, or SVM classifier using the same two features. Our results suggest that the proposed method can effectively localize alveolar bone-loss areas in periodontitis radiograph images and hence would be useful for dentists in evaluating degree of bone-loss for periodontitis patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

Science.gov (United States)

Pelikan, Erich; Vogelsang, Frank; Tolxdorff, Thomas

1996-04-01

The texture-based segmentation of x-ray images of focal bone lesions using topological maps is introduced. Texture characteristics are described by image-point correlation of feature images to feature vectors. For the segmentation, the topological map is labeled using an improved labeling strategy. Results of the technique are demonstrated on original and synthetic x-ray images and quantified with the aid of quality measures. In addition, a classifier-specific contribution analysis is applied for assessing the feature space.

Research of a hybrid undulator

International Nuclear Information System (INIS)

Ma Youwu; Wu Bing; Liu Bo

1995-12-01

A 1.5 m tapered hybrid undulator has been designed and built for mid-infrared free electron laser experiments at CIAE. The undulator utilizes the REC-steel hybrid configuration. The magnetic gap and magnetic field taper can be continuously adjusted. The rms error of the peak field is less than 0.53%. The electron trajectory deviation is around 0.03 mm. The design of undulator, sorting of magnets in hybrid undulator using simulated annealing technique, the motion of electron beam in the ideal and measured magnetic field, magnetic field measurement technique and magnetic field adjustment are described. (6 refs., 10 figs., 1 tab)

AUTOMATIC MULTILEVEL IMAGE SEGMENTATION BASED ON FUZZY REASONING

Directory of Open Access Journals (Sweden)

Liang Tang

2011-05-01

Full Text Available An automatic multilevel image segmentation method based on sup-star fuzzy reasoning (SSFR is presented. Using the well-known sup-star fuzzy reasoning technique, the proposed algorithm combines the global statistical information implied in the histogram with the local information represented by the fuzzy sets of gray-levels, and aggregates all the gray-levels into several classes characterized by the local maximum values of the histogram. The presented method has the merits of determining the number of the segmentation classes automatically, and avoiding to calculating thresholds of segmentation. Emulating and real image segmentation experiments demonstrate that the SSFR is effective.

Hybrid silicon mode-locked laser with improved RF power by impedance matching

Science.gov (United States)

Tossoun, Bassem; Derickson, Dennis; Srinivasan, Sudharsanan; Bowers, John

2015-02-01

We design and discuss an impedance matching solution for a hybrid silicon mode-locked laser diode (MLLD) to improve peak optical power coming from the device. In order to develop an impedance matching solution, a thorough measurement and analysis of the MLLD as a function of bias on each of the laser segments was carried out. A passive component impedance matching network was designed at the operating frequency of 20 GHz to optimize RF power delivery to the laser. The hybrid silicon laser was packaged together in a module including the impedance matching circuit. The impedance matching design resulted in a 6 dB (electrical) improvement in the detected modulation spectrum power, as well as approximately a 10 dB phase noise improvement, from the MLLD. Also, looking ahead to possible future work, we discuss a Step Recovery Diode (SRD) driven impulse generator, which wave-shapes the RF drive to achieve efficient injection. This novel technique addresses the time varying impedance of the absorber as the optical pulse passes through it, to provide optimum optical pulse shaping.

Enhancement of Twins Fetal ECG Signal Extraction Based on Hybrid Blind Extraction Techniques

Directory of Open Access Journals (Sweden)

Ahmed Kareem Abdullah

2017-07-01

Full Text Available ECG machines are noninvasive system used to measure the heartbeat signal. It’s very important to monitor the fetus ECG signals during pregnancy to check the heat activity and to detect any problem early before born, therefore the monitoring of ECG signals have clinical significance and importance. For multi-fetal pregnancy case the classical filtering algorithms are not sufficient to separate the ECG signals between mother and fetal. In this paper the mixture consists of mixing from three ECG signals, the first signal is the mother ECG (M-ECG signal, second signal the Fetal-1 ECG (F1-ECG, and third signal is the Fetal-2 ECG (F2-ECG, these signals are extracted based on modified blind source extraction (BSE techniques. The proposed work based on hybridization between two BSE techniques to ensure that the extracted signals separated well. The results demonstrate that the proposed work very efficiently to extract the useful ECG signals

Segmentation of complex document

Directory of Open Access Journals (Sweden)

Souad Oudjemia

2014-06-01

Full Text Available In this paper we present a method for segmentation of documents image with complex structure. This technique based on GLCM (Grey Level Co-occurrence Matrix used to segment this type of document in three regions namely, 'graphics', 'background' and 'text'. Very briefly, this method is to divide the document image, in block size chosen after a series of tests and then applying the co-occurrence matrix to each block in order to extract five textural parameters which are energy, entropy, the sum entropy, difference entropy and standard deviation. These parameters are then used to classify the image into three regions using the k-means algorithm; the last step of segmentation is obtained by grouping connected pixels. Two performance measurements are performed for both graphics and text zones; we have obtained a classification rate of 98.3% and a Misclassification rate of 1.79%.

Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries

Science.gov (United States)

Davuluri, Pavani; Wu, Jie; Tang, Yang; Cockrell, Charles H.; Ward, Kevin R.; Najarian, Kayvan; Hargraves, Rosalyn H.

2012-01-01

Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence medicine, analyzing medical images manually delays the decision-making process. Automated hemorrhage detection and segmentation can significantly help physicians to analyze these images and make fast and accurate decisions. Hemorrhage segmentation is a crucial step in the accurate diagnosis and treatment decision-making process. This paper presents a novel rule-based hemorrhage segmentation technique that utilizes pelvic anatomical information to segment hemorrhage accurately. An evaluation measure is used to quantify the accuracy of hemorrhage segmentation. The results show that the proposed method is able to segment hemorrhage very well, and the results are promising. PMID:22919433

Sb(III)-Imprinted Organic-Inorganic Hybrid Sorbent Prepared by Hydrothermal-Assisted Surface Imprinting Technique for Selective Adsorption of Sb(III)

Science.gov (United States)

Zhang, Dan; Zhao, Yue; Xu, Hong-Bo

2018-03-01

Sb(III)-imprinted organic-inorganic hybrid sorbent was prepared by hydrothermal-assisted surface imprinting technique and was characterized by Fourier transform infrared spectroscopy, scanning electron microscopy coupled to an energy dispersive spectrometer and N2 adsorption/desorption isotherms. Hydrothermal-assisted process can improve the selectivity of the Sb(III)-imprinted hybrid sorbent for Sb(III) due to stable control of temperature and pressure. The Sb(III)-imprinted hybrid sorbent IIS indicated higher selectivity for Sb(III), had high static adsorption capacity of 37.3 mg g-1 for Sb(III), displayed stable adsorption capacity in pH range from 4 to 8, reached an rapid adsorption equilibrium within 30 min. According to the correlation coefficient ( r 2 > 0.99), the experimental data fitted better the pseudo-second-order kinetic model and Langmuir equilibrium isotherm.

A fully automated and reproducible level-set segmentation approach for generation of MR-based attenuation correction map of PET images in the brain employing single STE-MR imaging modality

Energy Technology Data Exchange (ETDEWEB)

Kazerooni, Anahita Fathi; Aarabi, Mohammad Hadi [Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Ay, Mohammadreza [Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Medical Imaging Systems Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Rad, Hamidreza Saligheh [Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of)

2014-07-29

Generating MR-based attenuation correction map (μ-map) for quantitative reconstruction of PET images still remains a challenge in hybrid PET/MRI systems, mainly because cortical bone structures are indistinguishable from proximal air cavities in conventional MR images. Recently, development of short echo-time (STE) MR imaging sequences, has shown promise in differentiating cortical bone from air. However, on STE-MR images, the bone appears with discontinuous boundaries. Therefore, segmentation techniques based on intensity classification, such as thresholding or fuzzy C-means, fail to homogeneously delineate bone boundaries, especially in the presence of intrinsic noise and intensity inhomogeneity. Consequently, they cannot be fully automatized, must be fine-tuned on the case-by-case basis, and require additional morphological operations for segmentation refinement. To overcome the mentioned problems, in this study, we introduce a new fully automatic and reproducible STE-MR segmentation approach exploiting level-set in a clustering-based intensity inhomogeneity correction framework to reliably delineate bone from soft tissue and air.

A fully automated and reproducible level-set segmentation approach for generation of MR-based attenuation correction map of PET images in the brain employing single STE-MR imaging modality

International Nuclear Information System (INIS)

Kazerooni, Anahita Fathi; Aarabi, Mohammad Hadi; Ay, Mohammadreza; Rad, Hamidreza Saligheh

2014-01-01

Generating MR-based attenuation correction map (μ-map) for quantitative reconstruction of PET images still remains a challenge in hybrid PET/MRI systems, mainly because cortical bone structures are indistinguishable from proximal air cavities in conventional MR images. Recently, development of short echo-time (STE) MR imaging sequences, has shown promise in differentiating cortical bone from air. However, on STE-MR images, the bone appears with discontinuous boundaries. Therefore, segmentation techniques based on intensity classification, such as thresholding or fuzzy C-means, fail to homogeneously delineate bone boundaries, especially in the presence of intrinsic noise and intensity inhomogeneity. Consequently, they cannot be fully automatized, must be fine-tuned on the case-by-case basis, and require additional morphological operations for segmentation refinement. To overcome the mentioned problems, in this study, we introduce a new fully automatic and reproducible STE-MR segmentation approach exploiting level-set in a clustering-based intensity inhomogeneity correction framework to reliably delineate bone from soft tissue and air.

Investigation of kinetics and thermodynamics of DNA hybridization by means of 2-D fluorescence spectroscopy and soft/hard modeling techniques

Energy Technology Data Exchange (ETDEWEB)

Ebrahimi, Sara; Kompany-Zareh, Mohsen, E-mail: kmpz@dr.com

2016-02-04

Reversible hybridization reaction plays a key role in fundamental biological processes, in many laboratory techniques, and also in DNA based sensing devices. Comprehensive investigation of this process is, therefore, essential for the development of more sophisticated applications. Kinetics and thermodynamics of the hybridization reaction, as a second order process, are systematically investigated with the aid of the soft and hard chemometric methods. Labeling two complementary 21 mer DNA single strands with FAM and Texas red fluorophores, enabled recording of the florescence excitation−emission matrices during the experiments which led to three-way data sets. The presence of fluorescence resonance energy transfer in excitation and emission modes and the closure in concentration mode, made the three-way data arrays rank deficient. To acquire primary chemical information, restricted Tucker3 as a soft method was employed. Herein a model-based method, hard restricted trilinear decomposition, is introduced for in depth analysis of rank deficient three-way data sets. By employing proposed hard method, the nonlinear model parameters as well as the correct profiles could be estimated. In addition, a simple constraint is presented to extract chemically reasonable output profiles regarding the core elements of restricted Tucker3 model. - Highlights: • Hard restricted trilinear decomposition (HrTD) was introduced for model-based analysis of three-way rank deficient data. • DNA hybridization was investigated by two-dimensional fluorescence spectroscopy and soft/hard multi-way techniques. • Restricted Tucker3 analysis enabled accurate estimation of pure FRET profiles in the hybridized form. • HrTD was successfully employed to estimate kinetic and equilibrium parameters of DNA hybridization system. • The performance of the proposed methods in response to different physical stimuli was successfully evaluated.

SAR Imagery Segmentation by Statistical Region Growing and Hierarchical Merging

Energy Technology Data Exchange (ETDEWEB)

Ushizima, Daniela Mayumi; Carvalho, E.A.; Medeiros, F.N.S.; Martins, C.I.O.; Marques, R.C.P.; Oliveira, I.N.S.

2010-05-22

This paper presents an approach to accomplish synthetic aperture radar (SAR) image segmentation, which are corrupted by speckle noise. Some ordinary segmentation techniques may require speckle filtering previously. Our approach performs radar image segmentation using the original noisy pixels as input data, eliminating preprocessing steps, an advantage over most of the current methods. The algorithm comprises a statistical region growing procedure combined with hierarchical region merging to extract regions of interest from SAR images. The region growing step over-segments the input image to enable region aggregation by employing a combination of the Kolmogorov-Smirnov (KS) test with a hierarchical stepwise optimization (HSWO) algorithm for the process coordination. We have tested and assessed the proposed technique on artificially speckled image and real SAR data containing different types of targets.

Assignment of simian rotavirus SA11 temperature-sensitive mutant groups B and E to genome segments

International Nuclear Information System (INIS)

Gombold, J.L.; Estes, M.K.; Ramig, R.F.

1985-01-01

Recombinant (reassortant) viruses were selected from crosses between temperature-sensitive (ts) mutants of simian rotavirus SA11 and wild-type human rotavirus Wa. The double-stranded genome RNAs of the reassortants were examined by electrophoresis in Tris-glycine-buffered polyacrylamide gels and by dot hybridization with a cloned DNA probe for genome segment 2. Analysis of replacements of genome segments in the reassortants allowed construction of a map correlating genome segments providing functions interchangeable between SA11 and Wa. The reassortants revealed a functional correspondence in order of increasing electrophoretic mobility of genome segments. Analysis of the parental origin of genome segments in ts+ SA11/Wa reassortants derived from the crosses SA11 tsB(339) X Wa and SA11 tsE(1400) X Wa revealed that the group B lesion of tsB(339) was located on genome segment 3 and the group E lesion of tsE(1400) was on segment 8

Assignment of simian rotavirus SA11 temperature-sensitive mutant groups B and E to genome segments

Energy Technology Data Exchange (ETDEWEB)

Gombold, J.L.; Estes, M.K.; Ramig, R.F.

1985-05-01

Recombinant (reassortant) viruses were selected from crosses between temperature-sensitive (ts) mutants of simian rotavirus SA11 and wild-type human rotavirus Wa. The double-stranded genome RNAs of the reassortants were examined by electrophoresis in Tris-glycine-buffered polyacrylamide gels and by dot hybridization with a cloned DNA probe for genome segment 2. Analysis of replacements of genome segments in the reassortants allowed construction of a map correlating genome segments providing functions interchangeable between SA11 and Wa. The reassortants revealed a functional correspondence in order of increasing electrophoretic mobility of genome segments. Analysis of the parental origin of genome segments in ts+ SA11/Wa reassortants derived from the crosses SA11 tsB(339) X Wa and SA11 tsE(1400) X Wa revealed that the group B lesion of tsB(339) was located on genome segment 3 and the group E lesion of tsE(1400) was on segment 8.

Segmental and dynamic intensity-modulated radiotherapy delivery techniques for micro-multileaf collimator

International Nuclear Information System (INIS)

Agazaryan, Nzhde; Solberg, Timothy D.

2003-01-01

A leaf sequencing algorithm has been implemented to deliver segmental and dynamic multileaf collimated intensity-modulated radiotherapy (SMLC-IMRT and DMLC-IMRT, respectively) using a linear accelerator equipped with a micro-multileaf collimator (mMLC). The implementation extends a previously published algorithm for the SMLC-IMRT to include the dynamic MLC-IMRT method and several dosimetric considerations. The algorithm has been extended to account for the transmitted radiation and minimize the leakage between opposing and neighboring leaves. The underdosage problem associated with the tongue-and-groove design of the MLC is significantly reduced by synchronizing the MLC leaf movements. The workings of the leaf sequencing parameters have been investigated and the results of the planar dosimetric investigations show that the sequencing parameters affect the measured dose distributions as intended. Investigations of clinical cases suggest that SMLC and DMLC delivery methods produce comparable results with leaf sequences obtained by root-mean-square (RMS) errors specification of 1.5% and lower, approximately corresponding to 20 or more segments. For SMLC-IMRT, there is little to be gained by using an RMS error specification smaller than 2%, approximately corresponding to 15 segments; however, more segments directly translate to longer treatment time and more strain on the MLC. The implemented leaf synchronization method does not increase the required monitor units while it reduces the measured TG underdoses from a maximum of 12% to a maximum of 3% observed with single field measurements of representative clinical cases studied

Segmentation and Visualisation of Human Brain Structures

Energy Technology Data Exchange (ETDEWEB)

Hult, Roger

2003-10-01

In this thesis the focus is mainly on the development of segmentation techniques for human brain structures and of the visualisation of such structures. The images of the brain are both anatomical images (magnet resonance imaging (MRI) and autoradiography) and functional images that show blood flow (functional magnetic imaging (fMRI), positron emission tomography (PET), and single photon emission tomography (SPECT)). When working with anatomical images, the structures segmented are visible as different parts of the brain, e.g. the brain cortex, the hippocampus, or the amygdala. In functional images, the activity or the blood flow that be seen. Grey-level morphology methods are used in the segmentations to make tissue types in the images more homogenous and minimise difficulties with connections to outside tissue. A method for automatic histogram thresholding is also used. Furthermore, there are binary operations such as logic operation between masks and binary morphology operations. The visualisation of the segmented structures uses either surface rendering or volume rendering. For the visualisation of thin structures, surface rendering is the better choice since otherwise some voxels might be missed. It is possible to display activation from a functional image on the surface of a segmented cortex. A new method for autoradiographic images has been developed, which integrates registration, background compensation, and automatic thresholding to get faster and more reliable results than the standard techniques give.

Segmentation and Visualisation of Human Brain Structures

International Nuclear Information System (INIS)

Hult, Roger

2003-01-01

In this thesis the focus is mainly on the development of segmentation techniques for human brain structures and of the visualisation of such structures. The images of the brain are both anatomical images (magnet resonance imaging (MRI) and autoradiography) and functional images that show blood flow (functional magnetic imaging (fMRI), positron emission tomography (PET), and single photon emission tomography (SPECT)). When working with anatomical images, the structures segmented are visible as different parts of the brain, e.g. the brain cortex, the hippocampus, or the amygdala. In functional images, the activity or the blood flow that be seen. Grey-level morphology methods are used in the segmentations to make tissue types in the images more homogenous and minimise difficulties with connections to outside tissue. A method for automatic histogram thresholding is also used. Furthermore, there are binary operations such as logic operation between masks and binary morphology operations. The visualisation of the segmented structures uses either surface rendering or volume rendering. For the visualisation of thin structures, surface rendering is the better choice since otherwise some voxels might be missed. It is possible to display activation from a functional image on the surface of a segmented cortex. A new method for autoradiographic images has been developed, which integrates registration, background compensation, and automatic thresholding to get faster and more reliable results than the standard techniques give

A hybrid SEA/modal technique for modeling structural-acoustic interior noise in rotorcraft.

Science.gov (United States)

Jayachandran, V; Bonilha, M W

2003-03-01

This paper describes a hybrid technique that combines Statistical Energy Analysis (SEA) predictions for structural vibration with acoustic modal summation techniques to predict interior noise levels in rotorcraft. The method was applied for predicting the sound field inside a mock-up of the interior panel system of the Sikorsky S-92 helicopter. The vibration amplitudes of the frame and panel systems were predicted using a detailed SEA model and these were used as inputs to the model of the interior acoustic space. The spatial distribution of the vibration field on individual panels, and their coupling to the acoustic space were modeled using stochastic techniques. Leakage and nonresonant transmission components were accounted for using space-averaged values obtained from a SEA model of the complete structural-acoustic system. Since the cabin geometry was quite simple, the modeling of the interior acoustic space was performed using a standard modal summation technique. Sound pressure levels predicted by this approach at specific microphone locations were compared with measured data. Agreement within 3 dB in one-third octave bands above 40 Hz was observed. A large discrepancy in the one-third octave band in which the first acoustic mode is resonant (31.5 Hz) was observed. Reasons for such a discrepancy are discussed in the paper. The developed technique provides a method for modeling helicopter cabin interior noise in the frequency mid-range where neither FEA nor SEA is individually effective or accurate.

Produção de híbridos de amendoim forrageiro por meio de hibridação artificial Production of forage peanut hybrids through artificial hybridization

Directory of Open Access Journals (Sweden)

Marilda Augusta Peres Oliveira

2002-06-01

Full Text Available O objetivo deste trabalho foi a obtenção de híbridos de amendoim forrageiro por meio da hibridação artificial. O experimento foi realizado na Embrapa-Centro Nacional de Pesquisa de Recursos Genéticos e Biotecnologia, durante a época de florescimento dos acessos de Arachis pintoi Krap. & W. C. Gregory e de A. repens Handro. Cerca de 700 polinizações produziram 27 segmentos de frutos, com taxas de fecundação que variaram entre 1,1 e 12,9%, considerando-se todas as combinações híbridas. Os híbridos intra-específicos de A. pintoi produziram sementes F2, e os interespecíficos não produziram semente. A técnica de hibridação utilizada nas espécies forrageiras necessitou de ajustes, devido a diferenças observadas em relação ao amendoim cultivado, entre elas o hábito de crescimento.The purpose of this work was to obtain forage peanut hybrids through artificial hybridization. The experiment was conducted in a screenhouse at Embrapa-Centro Nacional de Pesquisa de Recursos Genéticos e Biotecnologia during the flowering period of Arachis pintoi Krap. & W. C. Gregory and A. repens Handro accessions. About 700 pollinations produced 27 fruit segments and the fertilization rates ranged from 1.1 to 12.9% for all cross combinations. The intraspecific hybrids produced F2 seeds, which did not occur to the interspecific hybrids. To effect the hybridization technique, adjustments were necessary to forage Arachis species, in relation to cultivated peanut, since differences in the growth habit were verified.

Evaluation of segmental left ventricular wall motion by equilibrium gated radionuclide ventriculography.

Science.gov (United States)

Van Nostrand, D; Janowitz, W R; Holmes, D R; Cohen, H A

1979-01-01

The ability of equilibrium gated radionuclide ventriculography to detect segmental left ventricular (LV) wall motion abnormalities was determined in 26 patients undergoing cardiac catheterization. Multiple gated studies obtained in 30 degrees right anterior oblique and 45 degrees left anterior oblique projections, played back in a movie format, were compared to the corresponding LV ventriculograms. The LV wall in the two projections was divided into eight segments. Each segment was graded as normal, hypokinetic, akinetic, dyskinetic, or indeterminate. Thirteen percent of the segments in the gated images were indeterminate; 24 out of 27 of these were proximal or distal inferior wall segments. There was exact agreement in 86% of the remaining segments. The sensitivity of the radionuclide technique for detecting normal versus any abnormal wall motion was 71%, with a specificity of 99%. Equilibrium gated ventriculography is an excellent noninvasive technique for evaluating segmental LV wall motion. It is least reliable in assessing the proximal inferior wall and interventricular septum.

A Survey of Spatio-Temporal Grouping Techniques

National Research Council Canada - National Science Library

Megret, Remi; DeMenthon, Daniel

2002-01-01

...) segmentation by trajectory grouping, and (3) joint spatial and temporal segmentation. The first category is the broadest, as it inherits the legacy techniques of image segmentation and motion segmentation...

Hybrid microcircuit technology handbook materials, processes, design, testing and production

CERN Document Server

Licari, James J

1998-01-01

The Hybrid Microcircuit Technology Handbook integrates the many diverse technologies used in the design, fabrication, assembly, and testing of hybrid segments crucial to the success of producing reliable circuits in high yields. Among these are: resistor trimming, wire bonding, die attachment, cleaning, hermetic sealing, and moisture analysis. In addition to thin films, thick films, and assembly processes, important chapters on substrate selections, handling (including electrostatic discharge), failure analysis, and documentation are included. A comprehensive chapter of design guidelines will

STRATEGI SEGMENTING, TARGETING, POSITIONING SERTA STRATEGI HARGA PADA PERUSAHAAN KECAP BLEKOK DI CILACAP

OpenAIRE

Wijaya, Hari; Sirine, Hani

2017-01-01

To win the market competition, companies must have segmenting, targeting, positioning strategy and pricing strategy. This study aims to determine segmenting, targeting, positioning strategy as well as the company's pricing strategies on Kecap Blekok Company in Cilacap. Methods of data collection in this study using interviews and documentation. The analysis technique used is descriptive analysis techniques. The results showed market segment of Kecap Blekok Company is the lower middle class, t...

Patterns of cytosine methylation in an elite rice hybrid and its parental lines, detected by a methylation-sensitive amplification polymorphism technique.

Science.gov (United States)

Xiong, L Z; Xu, C G; Saghai Maroof, M A; Zhang, Q

1999-04-01

DNA methylation is known to play an important role in the regulation of gene expression in eukaryotes. In this study, we assessed the extent and pattern of cytosine methylation in the rice genome, using the technique of methylation-sensitive amplified polymorphism (MSAP), which is a modification of the amplified fragment length polymorphism (AFLP) method that makes use of the differential sensitivity of a pair of isoschizomers to cytosine methylation. The tissues assayed included seedlings and flag leaves of an elite rice hybrid, Shanyou 63, and the parental lines Zhenshan 97 and Minghui 63. In all, 1076 fragments, each representing a recognition site cleaved by either or both of the isoschizomers, were amplified using 16 pairs of selective primers. A total of 195 sites were found to be methylated at cytosines in one or both parents, and the two parents showed approximately the same overall degree of methylation (16.3%), as revealed by the incidence of differential digestion by the isoschizomers. Four classes of patterns were identified in a comparative assay of cytosine methylation in the parents and hybrid; increased methylation was detected in the hybrid compared to the parents at some of the recognition sites, while decreased methylation in the hybrid was detected at other sites. A small proportion of the sites was found to be differentially methylated in seedlings and flag leaves; DNA from young seedlings was methylated to a greater extent than that from flag leaves. Almost all of the methylation patterns detected by MSAP could be confirmed by Southern analysis using the isolated amplified fragments as probes. The results clearly demonstrate that the MSAP technique is highly efficient for large-scale detection of cytosine methylation in the rice genome. We believe that the technique can be adapted for use in other plant species.

Hybrid Simulation of Composite Structures

DEFF Research Database (Denmark)

Høgh, Jacob Herold

experiment. The technique has primarily been used within earthquake engineering but many other fields of engineering have utilized the method with benefit. However, these previous efforts have focused on structures with a simple boundary between the numerical and physical substructure i.e. few degrees...... the transfer system and the control and monitoring techniques in the shared boundary is therefore a key issue in this type of hybrid simulation. During the research, hybrid simulation platforms have been programmed capable of running on different time scales with advanced control and monitoring techniques...

Henkin and Hybrid Logic

DEFF Research Database (Denmark)

Blackburn, Patrick Rowan; Huertas, Antonia; Manzano, Maria

2014-01-01

Leon Henkin was not a modal logician, but there is a branch of modal logic that has been deeply influenced by his work. That branch is hybrid logic, a family of logics that extend orthodox modal logic with special proposition symbols (called nominals) that name worlds. This paper explains why...... Henkin’s techniques are so important in hybrid logic. We do so by proving a completeness result for a hybrid type theory called HTT, probably the strongest hybrid logic that has yet been explored. Our completeness result builds on earlier work with a system called BHTT, or basic hybrid type theory...... is due to the first-order perspective, which lies at the heart of Henin’s best known work and hybrid logic....

Segmentation-less Digital Rock Physics

Science.gov (United States)

Tisato, N.; Ikeda, K.; Goldfarb, E. J.; Spikes, K. T.

2017-12-01

In the last decade, Digital Rock Physics (DRP) has become an avenue to investigate physical and mechanical properties of geomaterials. DRP offers the advantage of simulating laboratory experiments on numerical samples that are obtained from analytical methods. Potentially, DRP could allow sparing part of the time and resources that are allocated to perform complicated laboratory tests. Like classic laboratory tests, the goal of DRP is to estimate accurately physical properties of rocks like hydraulic permeability or elastic moduli. Nevertheless, the physical properties of samples imaged using micro-computed tomography (μCT) are estimated through segmentation of the μCT dataset. Segmentation proves to be a challenging and arbitrary procedure that typically leads to inaccurate estimates of physical properties. Here we present a novel technique to extract physical properties from a μCT dataset without the use of segmentation. We show examples in which we use segmentation-less method to simulate elastic wave propagation and pressure wave diffusion to estimate elastic properties and permeability, respectively. The proposed method takes advantage of effective medium theories and uses the density and the porosity that are measured in the laboratory to constrain the results. We discuss the results and highlight that segmentation-less DRP is more accurate than segmentation based DRP approaches and theoretical modeling for the studied rock. In conclusion, the segmentation-less approach here presented seems to be a promising method to improve accuracy and to ease the overall workflow of DRP.

Investigation of Steel Surfaces Treated by a Hybrid Ion Implantation Technique

International Nuclear Information System (INIS)

Reuther, H.; Richter, E.; Prokert, F.; Ueda, M.; Beloto, A. F.; Gomes, G. F.

2004-01-01

Implantation of nitrogen ions into stainless steel in combination with oxidation often results in a decrease or even complete removal of the chromium in the nitrogen containing outermost surface layer. While iron nitrides can be formed easily by this method, due to the absence of chromium, the formation of chromium nitrides is impossible and the beneficial influence of chromium in the steel for corrosion resistance cannot be used. To overcome this problem we use the following hybrid technique. A thin chromium layer is deposited on steel and subsequently implanted with nitrogen ions. Chromium can be implanted by recoil into the steel surface and thus the formation of iron/chromium nitrides should be possible. Both beam line ion implantation and plasma immersion ion implantation are used. Due to the variation of the process parameters, different implantation profiles and different compounds are produced. The produced layers are characterized by Auger electron spectroscopy, conversion electron Moessbauer spectroscopy and X-ray diffraction. The obtained results show that due to the variation of the implantation parameters, the formation of iron/chromium nitrides can be achieved and that plasma immersion ion implantation is the most suitable technique for the enrichment of chromium in the outermost surface layer of the steel when compared to the beam line implantation.

Variational mesh segmentation via quadric surface fitting

KAUST Repository

Yan, Dongming; Wang, Wen Ping; Liu, Yang; Yang, Zhouwang

2012-01-01

We present a new variational method for mesh segmentation by fitting quadric surfaces. Each component of the resulting segmentation is represented by a general quadric surface (including plane as a special case). A novel energy function is defined to evaluate the quality of the segmentation, which combines both L2 and L2 ,1 metrics from a triangle to a quadric surface. The Lloyd iteration is used to minimize the energy function, which repeatedly interleaves between mesh partition and quadric surface fitting. We also integrate feature-based and simplification-based techniques in the segmentation framework, which greatly improve the performance. The advantages of our algorithm are demonstrated by comparing with the state-of-the-art methods. © 2012 Elsevier Ltd. All rights reserved.

Variational mesh segmentation via quadric surface fitting

KAUST Repository

Yan, Dongming

2012-11-01

We present a new variational method for mesh segmentation by fitting quadric surfaces. Each component of the resulting segmentation is represented by a general quadric surface (including plane as a special case). A novel energy function is defined to evaluate the quality of the segmentation, which combines both L2 and L2 ,1 metrics from a triangle to a quadric surface. The Lloyd iteration is used to minimize the energy function, which repeatedly interleaves between mesh partition and quadric surface fitting. We also integrate feature-based and simplification-based techniques in the segmentation framework, which greatly improve the performance. The advantages of our algorithm are demonstrated by comparing with the state-of-the-art methods. © 2012 Elsevier Ltd. All rights reserved.

Segmentation of fluorescence microscopy cell images using unsupervised mining.

Science.gov (United States)

Du, Xian; Dua, Sumeet

2010-05-28

The accurate measurement of cell and nuclei contours are critical for the sensitive and specific detection of changes in normal cells in several medical informatics disciplines. Within microscopy, this task is facilitated using fluorescence cell stains, and segmentation is often the first step in such approaches. Due to the complex nature of cell issues and problems inherent to microscopy, unsupervised mining approaches of clustering can be incorporated in the segmentation of cells. In this study, we have developed and evaluated the performance of multiple unsupervised data mining techniques in cell image segmentation. We adapt four distinctive, yet complementary, methods for unsupervised learning, including those based on k-means clustering, EM, Otsu's threshold, and GMAC. Validation measures are defined, and the performance of the techniques is evaluated both quantitatively and qualitatively using synthetic and recently published real data. Experimental results demonstrate that k-means, Otsu's threshold, and GMAC perform similarly, and have more precise segmentation results than EM. We report that EM has higher recall values and lower precision results from under-segmentation due to its Gaussian model assumption. We also demonstrate that these methods need spatial information to segment complex real cell images with a high degree of efficacy, as expected in many medical informatics applications.

Transfer learning improves supervised image segmentation across imaging protocols.

Science.gov (United States)

van Opbroek, Annegreet; Ikram, M Arfan; Vernooij, Meike W; de Bruijne, Marleen

2015-05-01

The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore may improve performance over supervised learning for segmentation across scanners and scan protocols. We present four transfer classifiers that can train a classification scheme with only a small amount of representative training data, in addition to a larger amount of other training data with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two magnetic resonance imaging brain-segmentation tasks with multi-site data: white matter, gray matter, and cerebrospinal fluid segmentation; and white-matter-/MS-lesion segmentation. The experiments showed that when there is only a small amount of representative training data available, transfer learning can greatly outperform common supervised-learning approaches, minimizing classification errors by up to 60%.

IMAGE ANALYSIS BASED ON EDGE DETECTION TECHNIQUES

Institute of Scientific and Technical Information of China (English)

纳瑟; 刘重庆

2002-01-01

A method that incorporates edge detection technique, Markov Random field (MRF), watershed segmentation and merging techniques was presented for performing image segmentation and edge detection tasks. It first applies edge detection technique to obtain a Difference In Strength (DIS) map. An initial segmented result is obtained based on K-means clustering technique and the minimum distance. Then the region process is modeled by MRF to obtain an image that contains different intensity regions. The gradient values are calculated and then the watershed technique is used. DIS calculation is used for each pixel to define all the edges (weak or strong) in the image. The DIS map is obtained. This help as priority knowledge to know the possibility of the region segmentation by the next step (MRF), which gives an image that has all the edges and regions information. In MRF model,gray level l, at pixel location i, in an image X, depends on the gray levels of neighboring pixels. The segmentation results are improved by using watershed algorithm. After all pixels of the segmented regions are processed, a map of primitive region with edges is generated. The edge map is obtained using a merge process based on averaged intensity mean values. A common edge detectors that work on (MRF) segmented image are used and the results are compared. The segmentation and edge detection result is one closed boundary per actual region in the image.

Evolutionary Origin of Body Axis Segmentation in Annelids and Arthropods

Science.gov (United States)

Shankland, S. Martin

2003-01-01

During the period of this report, we have made a number of important discoveries. To date this work has led to 4 peer-reviewed publications in primary research journals plus 1 minireview and 1 chapter in the proceedings of a meeting. Publications resulting from this grant support are enumerated at the end of the report. Two additional, on-going studies also described. 1. Using laser cell ablation, we have obtained evidence that an annelid - the leech Helobdella robusta - patterns the anteroposterior (AP) polarity of its nascent segment primordia independent of cell interactions oriented along the AP axis. 2. We cloned a Helobdella homologue (hro-hh) of the Drosophila segment polarity gene hedgehog, and used in situ hybridization and northern blots to characterize its expression in the embryo. 3. We have used laser cell ablations to examine the possible role of cell interactions during the developmental patterning of the 4 rostralmost "head" segments of the leech Helobdella robusta.

Interactive vs. automatic ultrasound image segmentation methods for staging hepatic lipidosis.

Science.gov (United States)

Weijers, Gert; Starke, Alexander; Haudum, Alois; Thijssen, Johan M; Rehage, Jürgen; De Korte, Chris L

2010-07-01

The aim of this study was to test the hypothesis that automatic segmentation of vessels in ultrasound (US) images can produce similar or better results in grading fatty livers than interactive segmentation. A study was performed in postpartum dairy cows (N=151), as an animal model of human fatty liver disease, to test this hypothesis. Five transcutaneous and five intraoperative US liver images were acquired in each animal and a liverbiopsy was taken. In liver tissue samples, triacylglycerol (TAG) was measured by biochemical analysis and hepatic diseases other than hepatic lipidosis were excluded by histopathologic examination. Ultrasonic tissue characterization (UTC) parameters--Mean echo level, standard deviation (SD) of echo level, signal-to-noise ratio (SNR), residual attenuation coefficient (ResAtt) and axial and lateral speckle size--were derived using a computer-aided US (CAUS) protocol and software package. First, the liver tissue was interactively segmented by two observers. With increasing fat content, fewer hepatic vessels were visible in the ultrasound images and, therefore, a smaller proportion of the liver needed to be excluded from these images. Automatic-segmentation algorithms were implemented and it was investigated whether better results could be achieved than with the subjective and time-consuming interactive-segmentation procedure. The automatic-segmentation algorithms were based on both fixed and adaptive thresholding techniques in combination with a 'speckle'-shaped moving-window exclusion technique. All data were analyzed with and without postprocessing as contained in CAUS and with different automated-segmentation techniques. This enabled us to study the effect of the applied postprocessing steps on single and multiple linear regressions ofthe various UTC parameters with TAG. Improved correlations for all US parameters were found by using automatic-segmentation techniques. Stepwise multiple linear-regression formulas where derived and used

The application of fluorescence in situ hybridization (FISH technique for studying the microbial communities in intestinal tissues of white shrimp (Penaeus vannamei

Directory of Open Access Journals (Sweden)

Supamattaya, K.

2005-02-01

Full Text Available Fluorescence in situ hybridization technique is very useful for the evaluation of microbial communities in various environments. It is possible to apply this technique to study the intestinal microflora in white shrimp (Penaeus vannamei. Different fixatives and storage temperature were tested in this technique. It was found that fixation with 10% buffered formalin for 12 hours and changed to 70% ethanol shown positive results when compared to the fixation with Davidson's fixative or RF fixative. The best signaling was obtainedfrom the samples which were stored in -20ºC. By using the DNA probe targeted to the Eubacteria domain (EUB338 probe, 5′-GCT GCC TCC CGT AGG AGT-3′ labeled with fluorescein as a hybridizing probe, it was found that most intestinal microflora were aggregated with the intestinal contents, or dispersed in the lumen. There was not evidence of the attachment of the microflora with the intestinal epithelium in this study.

Contextually guided very-high-resolution imagery classification with semantic segments

Science.gov (United States)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

Quantum chemical approaches: semiempirical molecular orbital and hybrid quantum mechanical/molecular mechanical techniques.

Science.gov (United States)

Bryce, Richard A; Hillier, Ian H

2014-01-01

The use of computational quantum chemical methods to aid drug discovery is surveyed. An overview of the various computational models spanning ab initio, density function theory, semiempirical molecular orbital (MO), and hybrid quantum mechanical (QM)/molecular mechanical (MM) methods is given and their strengths and weaknesses are highlighted, focussing on the challenge of obtaining the accuracy essential for them to make a meaningful contribution to drug discovery. Particular attention is given to hybrid QM/MM and semiempirical MO methods which have the potential to yield the necessary accurate predictions of macromolecular structure and reactivity. These methods are shown to have advanced the study of many aspects of substrate-ligand interactions relevant to drug discovery. Thus, the successful parametrization of semiempirical MO methods and QM/MM methods can be used to model noncovalent substrate-protein interactions, and to lead to improved scoring functions. QM/MM methods can be used in crystal structure refinement and are particularly valuable for modelling covalent protein-ligand interactions and can thus aid the design of transition state analogues. An extensive collection of examples from the areas of metalloenzyme structure, enzyme inhibition, and ligand binding affinities and scoring functions are used to illustrate the power of these techniques.

Hybrid real-code ant colony optimisation for constrained mechanical design

Science.gov (United States)

Pholdee, Nantiwat; Bureerat, Sujin

2016-01-01

This paper proposes a hybrid meta-heuristic based on integrating a local search simplex downhill (SDH) method into the search procedure of real-code ant colony optimisation (ACOR). This hybridisation leads to five hybrid algorithms where a Monte Carlo technique, a Latin hypercube sampling technique (LHS) and a translational propagation Latin hypercube design (TPLHD) algorithm are used to generate an initial population. Also, two numerical schemes for selecting an initial simplex are investigated. The original ACOR and its hybrid versions along with a variety of established meta-heuristics are implemented to solve 17 constrained test problems where a fuzzy set theory penalty function technique is used to handle design constraints. The comparative results show that the hybrid algorithms are the top performers. Using the TPLHD technique gives better results than the other sampling techniques. The hybrid optimisers are a powerful design tool for constrained mechanical design problems.

Conceptual design of hybrid-electric transport aircraft

Science.gov (United States)

Pornet, C.; Isikveren, A. T.

2015-11-01

fuel burn reduction can be achieved; however, this also proves to be detrimental in terms of vehicular efficiency. The potential in block fuel reduction diminishes with increasing design range - especially for low battery gravimetric specific energies. In addition, the narrow shape of the fuselage represents a volumetric constraint for the storage of the battery and typical cargo. It was concluded that the short-range/regional market segment would be the most suited for the application of such concepts. Concerning the influence of HP,USE on flight technique optimization, an increasing HP,USE was found to have a tendency of decreasing the optimum flight speed and altitude. Further investigation of more synergistic design and integration of the hybrid-electric motive power system needs to be conducted in order to explore the full benefit of such technologies.

Study of domain structure in segmented polyether polyurethaneureas by PAT

International Nuclear Information System (INIS)

Yin Chuanyuan; Xu Weizheng; Gu Qingchao

1990-01-01

The domain structure of segmented polyether polyurethaneureas is investigated by means of positron annihilation technique, small angle X-ray scattering and differential scanning calorimetry. The experimental results show that the decrease of domain volume and free volume results from the increase of hard segment contents, and that the increase of domain volume and free volume results from the increase of molecular weight of soft segments

SU-E-J-130: Automating Liver Segmentation Via Combined Global and Local Optimization

Energy Technology Data Exchange (ETDEWEB)

Li, Dengwang; Wang, Jie [College of Physics and Electronics, Shandong Normal University, Jinan, Shandong (China); Kapp, Daniel S.; Xing, Lei [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA (United States)

2015-06-15

Purpose: The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor. Methods: 200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data were segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H-PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate). Results: The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%. Conclusion: The proposed automatic segmentation method provides a sensible technique for segmentation of CT images. This work is

SU-E-J-130: Automating Liver Segmentation Via Combined Global and Local Optimization

International Nuclear Information System (INIS)

Li, Dengwang; Wang, Jie; Kapp, Daniel S.; Xing, Lei

2015-01-01

Purpose: The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor. Methods: 200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data were segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H-PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate). Results: The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%. Conclusion: The proposed automatic segmentation method provides a sensible technique for segmentation of CT images. This work is

Mechanisms of Surface-Mediated DNA Hybridization

Science.gov (United States)

2015-01-01

Single-molecule total internal reflection fluorescence microscopy was employed in conjunction with resonance energy transfer (RET) to observe the dynamic behavior of donor-labeled ssDNA at the interface between aqueous solution and a solid surface decorated with complementary acceptor-labeled ssDNA. At least 100 000 molecular trajectories were determined for both complementary strands and negative control ssDNA. RET was used to identify trajectory segments corresponding to the hybridized state. The vast majority of molecules from solution adsorbed nonspecifically to the surface, where a brief two-dimensional search was performed with a 7% chance of hybridization. Successful hybridization events occurred with a characteristic search time of ∼0.1 s, and unsuccessful searches resulted in desorption from the surface, ultimately repeating the adsorption and search process. Hybridization was reversible, and two distinct modes of melting (i.e., dehybridization) were observed, corresponding to long-lived (∼15 s) and short-lived (∼1.4 s) hybridized time intervals. A strand that melted back onto the surface could rehybridize after a brief search or desorb from the interface. These mechanistic observations provide guidance for technologies that involve DNA interactions in the near-surface region, suggesting a need to design surfaces that both enhance the complex multidimensional search process and stabilize the hybridized state. PMID:24708278

An interactive medical image segmentation framework using iterative refinement.

Science.gov (United States)

Kalshetti, Pratik; Bundele, Manas; Rahangdale, Parag; Jangra, Dinesh; Chattopadhyay, Chiranjoy; Harit, Gaurav; Elhence, Abhay

2017-04-01

Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results for medical images as they contain irregularities. They need to be pre-processed before segmentation. In order to obtain the most suitable method for medical image segmentation, we propose MIST (Medical Image Segmentation Tool), a two stage algorithm. The first stage automatically generates a binary marker image of the region of interest using mathematical morphology. This marker serves as the mask image for the second stage which uses GrabCut to yield an efficient segmented result. The obtained result can be further refined by user interaction, which can be done using the proposed Graphical User Interface (GUI). Experimental results show that the proposed method is accurate and provides satisfactory segmentation results with minimum user interaction on medical as well as natural images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cardiac hybrid imaging

Energy Technology Data Exchange (ETDEWEB)

Gaemperli, Oliver [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); University Hospital Zurich, Nuclear Cardiology, Cardiovascular Center, Zurich (Switzerland); Kaufmann, Philipp A. [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland)

2014-05-15

Hybrid cardiac single photon emission computed tomography (SPECT)/CT imaging allows combined assessment of anatomical and functional aspects of cardiac disease. In coronary artery disease (CAD), hybrid SPECT/CT imaging allows detection of coronary artery stenosis and myocardial perfusion abnormalities. The clinical value of hybrid imaging has been documented in several subsets of patients. In selected groups of patients, hybrid imaging improves the diagnostic accuracy to detect CAD compared to the single imaging techniques. Additionally, this approach facilitates functional interrogation of coronary stenoses and guidance with regard to revascularization procedures. Moreover, the anatomical information obtained from CT coronary angiography or coronary artery calcium scores (CACS) adds prognostic information over perfusion data from SPECT. The use of cardiac hybrid imaging has been favoured by the dissemination of dedicated hybrid systems and the release of dedicated image fusion software, which allow simple patient throughput for hybrid SPECT/CT studies. Further technological improvements such as more efficient detector technology to allow for low-radiation protocols, ultra-fast image acquisition and improved low-noise image reconstruction algorithms will be instrumental to further promote hybrid SPECT/CT in research and clinical practice. (orig.)

Marketing Education Through Benefit Segmentation. AIR Forum 1981 Paper.

Science.gov (United States)

Goodnow, Wilma Elizabeth

The applicability of the "benefit segmentation" marketing technique to education was tested at the College of DuPage in 1979. Benefit segmentation identified target markets homogeneous in benefits expected from a program offering and may be useful in combatting declining enrollments. The 487 randomly selected students completed the 223…

Hybrid intelligent engineering systems

CERN Document Server

Jain, L C; Adelaide, Australia University of

1997-01-01

This book on hybrid intelligent engineering systems is unique, in the sense that it presents the integration of expert systems, neural networks, fuzzy systems, genetic algorithms, and chaos engineering. It shows that these new techniques enhance the capabilities of one another. A number of hybrid systems for solving engineering problems are presented.

Kinematics and strain analyses of the eastern segment of the Pernicana Fault (Mt. Etna, Italy derived from geodetic techniques (1997-2005

Directory of Open Access Journals (Sweden)

M. Mattia

2006-06-01

Full Text Available This paper analyses the ground deformations occurring on the eastern part of the Pernicana Fault from 1997 to 2005. This segment of the fault was monitored with three local networks based on GPS and EDM techniques. More than seventy GPS and EDM surveys were carried out during the considered period, in order to achieve a higher temporal detail of ground deformation affecting the structure. We report the comparisons among GPS and EDM surveys in terms of absolute horizontal displacements of each GPS benchmark and in terms of strain parameters for each GPS and EDM network. Ground deformation measurements detected a continuous left-lateral movement of the Pernicana Fault. We conclude that, on the easternmost part of the Pernicana Fault, where it branches out into two segments, the deformation is transferred entirely SE-wards by a splay fault.

Knee cartilage segmentation using active shape models and local binary patterns

Science.gov (United States)

González, Germán.; Escalante-Ramírez, Boris

2014-05-01

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

Mandatory chromosomal segment balance in aneuploid tumor cells

International Nuclear Information System (INIS)

Kost-Alimova, Maria; Stanbridge, Eric; Klein, George; Imreh, Stefan; Darai-Ramqvist, Eva; Yau, Wing Lung; Sandlund, Agneta; Fedorova, Ludmila; Yang, Ying; Kholodnyuk, Irina; Cheng, Yue; Li Lung, Maria

2007-01-01

Euploid chromosome balance is vitally important for normal development, but is profoundly changed in many tumors. Is each tumor dependent on its own structurally and numerically changed chromosome complement that has evolved during its development and progression? We have previously shown that normal chromosome 3 transfer into the KH39 renal cell carcinoma line and into the Hone1 nasopharyngeal carcinoma line inhibited their tumorigenicity. The aim of the present study was to distinguish between a qualitative and a quantitative model of this suppression. According to the former, a damaged or deleted tumor suppressor gene would be restored by the transfer of a normal chromosome. If so, suppression would be released only when the corresponding sequences of the exogenous normal chromosome are lost or inactivated. According to the alternative quantitative model, the tumor cell would not tolerate an increased dosage of the relevant gene or segment. If so, either a normal cell derived, or, a tumor derived endogenous segment could be lost. Fluorescence in Situ Hybridization based methods, as well as analysis of polymorphic microsatellite markers were used to follow chromosome 3 constitution changes in monochromosomal hybrids. In both tumor lines with introduced supernumerary chromosomes 3, the copy number of 3p21 or the entire 3p tended to fall back to the original level during both in vitro and in vivo growth. An exogenous, normal cell derived, or an endogenous, tumor derived, chromosome segment was lost with similar probability. Identification of the lost versus retained segments showed that the intolerance for increased copy number was particularly strong for 3p14-p21, and weaker for other 3p regions. Gains in copy number were, on the other hand, well tolerated in the long arm and particularly the 3q26-q27 region. The inability of the cell to tolerate an experimentally imposed gain in 3p14-p21 in contrast to the well tolerated gain in 3q26-q27 is consistent with the

Metrics for image segmentation

Science.gov (United States)

Rees, Gareth; Greenway, Phil; Morray, Denise

1998-07-01

An important challenge in mapping image-processing techniques onto applications is the lack of quantitative performance measures. From a systems engineering perspective these are essential if system level requirements are to be decomposed into sub-system requirements which can be understood in terms of algorithm selection and performance optimization. Nowhere in computer vision is this more evident than in the area of image segmentation. This is a vigorous and innovative research activity, but even after nearly two decades of progress, it remains almost impossible to answer the question 'what would the performance of this segmentation algorithm be under these new conditions?' To begin to address this shortcoming, we have devised a well-principled metric for assessing the relative performance of two segmentation algorithms. This allows meaningful objective comparisons to be made between their outputs. It also estimates the absolute performance of an algorithm given ground truth. Our approach is an information theoretic one. In this paper, we describe the theory and motivation of our method, and present practical results obtained from a range of state of the art segmentation methods. We demonstrate that it is possible to measure the objective performance of these algorithms, and to use the information so gained to provide clues about how their performance might be improved.

Segmentation of deformable organs from medical images using particle swarm optimization and nonlinear shape priors

Science.gov (United States)

Afifi, Ahmed; Nakaguchi, Toshiya; Tsumura, Norimichi

2010-03-01

In many medical applications, the automatic segmentation of deformable organs from medical images is indispensable and its accuracy is of a special interest. However, the automatic segmentation of these organs is a challenging task according to its complex shape. Moreover, the medical images usually have noise, clutter, or occlusion and considering the image information only often leads to meager image segmentation. In this paper, we propose a fully automated technique for the segmentation of deformable organs from medical images. In this technique, the segmentation is performed by fitting a nonlinear shape model with pre-segmented images. The kernel principle component analysis (KPCA) is utilized to capture the complex organs deformation and to construct the nonlinear shape model. The presegmentation is carried out by labeling each pixel according to its high level texture features extracted using the overcomplete wavelet packet decomposition. Furthermore, to guarantee an accurate fitting between the nonlinear model and the pre-segmented images, the particle swarm optimization (PSO) algorithm is employed to adapt the model parameters for the novel images. In this paper, we demonstrate the competence of proposed technique by implementing it to the liver segmentation from computed tomography (CT) scans of different patients.

Simultaneous Whole-Brain Segmentation and White Matter Lesion Detection Using Contrast-Adaptive Probabilistic Models

DEFF Research Database (Denmark)

Puonti, Oula; Van Leemput, Koen

2016-01-01

In this paper we propose a new generative model for simultaneous brain parcellation and white matter lesion segmentation from multi-contrast magnetic resonance images. The method combines an existing whole-brain segmentation technique with a novel spatial lesion model based on a convolutional...... restricted Boltzmann machine. Unlike current state-of-the-art lesion detection techniques based on discriminative modeling, the proposed method is not tuned to one specific scanner or imaging protocol, and simultaneously segments dozens of neuroanatomical structures. Experiments on a public benchmark dataset...... in multiple sclerosis indicate that the method’s lesion segmentation accuracy compares well to that of the current state-of-the-art in the field, while additionally providing robust whole-brain segmentations....

Active contour modes Crisp: new technique for segmentation of the lungs in CT images

International Nuclear Information System (INIS)

Reboucas Filho, Pedro Pedrosa; Cortez, Paulo Cesar; Holanda, Marcelo Alcantara

2011-01-01

This paper proposes a new active contour model (ACM), called ACM Crisp, and evaluates the segmentation of lungs in computed tomography (CT) images. An ACM draws a curve around or within the object of interest. This curve changes its shape, when some energy acts on it and moves towards the edges of the object. This process is performed by successive iterations of minimization of a given energy, associated with the curve. The ACMs described in the literature have limitations when used for segmentations of CT lung images. The ACM Crisp model overcomes these limitations, since it proposes automatic initiation and new external energy based on rules and radiological pulmonary densities. The paper compares other ACMs with the proposed method, which is shown to be superior. In order to validate the algorithm a medical expert in the field of Pulmonology of the Walter Cantidio University Hospital from the Federal University of Ceara carried out a qualitative analysis. In these analyses 100 CT lung images were used. The segmentation efficiency was evaluated into 5 categories with the following results for the ACM Crisp: 73% excellent, without errors, 20% acceptable, with small errors, and 7% reasonable, with large errors, 0% poor, covering only a small part of the lung, and 0% very bad, making a totally incorrect segmentation. In conclusion the ACM Crisp is considered a useful algorithm to segment CT lung images, and with potential to integrate medical diagnosis systems. (author)

Micro-segmented flow applications in chemistry and biology

CERN Document Server

Cahill, Brian

2014-01-01

The book is dedicated to the method and application potential of micro segmented flow. The recent state of development of this powerful technique is presented in 12 chapters by leading researchers from different countries. In the first section, the principles of generation and manipulation of micro-fluidic segments are explained. In the second section, the micro continuous-flow synthesis of different types of nanomaterials is shown as a typical example for the use of advantages of the technique in chemistry. In the third part, the particular importance of the technique in biotechnical applications is presented demonstrating the progress for miniaturized cell-free processes, for molecular biology and DNA-based diagnostis and sequencing as well as for the development of antibiotics and the evaluation of toxic effects in medicine and environment.

Biomechanics of Artificial Disc Replacements Adjacent to a 2-Level Fusion in 4-Level Hybrid Constructs: An In Vitro Investigation

Science.gov (United States)

Liao, Zhenhua; Fogel, Guy R.; Wei, Na; Gu, Hongsheng; Liu, Weiqiang

2015-01-01

Background The ideal procedure for multilevel cervical degenerative disc diseases remains controversial. Recent studies on hybrid surgery combining anterior cervical discectomy and fusion (ACDF) and artificial cervical disc replacement (ACDR) for 2-level and 3-level constructs have been reported in the literature. The purpose of this study was to estimate the biomechanics of 3 kinds of 4-level hybrid constructs, which are more likely to be used clinically compared to 4-level arthrodesis. Material/Methods Eighteen human cadaveric spines (C2–T1) were evaluated in different testing conditions: intact, with 3 kinds of 4-level hybrid constructs (hybrid C3–4 ACDR+C4–6 ACDF+C6–7ACDR; hybrid C3–5ACDF+C5–6ACDR+C6–7ACDR; hybrid C3–4ACDR+C4–5ACDR+C5–7ACDF); and 4-level fusion. Results Four-level fusion resulted in significant decrease in the C3–C7 ROM compared with the intact spine. The 3 different 4-level hybrid treatment groups caused only slight change at the instrumented levels compared to intact except for flexion. At the adjacent levels, 4-level fusion resulted in significant increase of contribution of both upper and lower adjacent levels. However, for the 3 hybrid constructs, significant changes of motion increase far lower than 4P at adjacent levels were only noted in partial loading conditions. No destabilizing effect or hypermobility were observed in any 4-level hybrid construct. Conclusions Four-level fusion significantly eliminated motion within the construct and increased motion at the adjacent segments. For all 3 different 4-level hybrid constructs, ACDR normalized motion of the index segment and adjacent segments with no significant hypermobility. Compared with the 4-level ACDF condition, the artificial discs in 4-level hybrid constructs had biomechanical advantages compared to fusion in normalizing adjacent level motion. PMID:26694835

Analysis of Non-binary Hybrid LDPC Codes

OpenAIRE

Sassatelli, Lucile; Declercq, David

2008-01-01

In this paper, we analyse asymptotically a new class of LDPC codes called Non-binary Hybrid LDPC codes, which has been recently introduced. We use density evolution techniques to derive a stability condition for hybrid LDPC codes, and prove their threshold behavior. We study this stability condition to conclude on asymptotic advantages of hybrid LDPC codes compared to their non-hybrid counterparts.

Genetic dissection of hybrid incompatibilities between Drosophila simulans and D. mauritiana. I. Differential accumulation of hybrid male sterility effects on the X and autosomes.

Science.gov (United States)

Tao, Yun; Chen, Sining; Hartl, Daniel L; Laurie, Cathy C

2003-08-01

The genetic basis of hybrid incompatibility in crosses between Drosophila mauritiana and D. simulans was investigated to gain insight into the evolutionary mechanisms of speciation. In this study, segments of the D. mauritiana third chromosome were introgressed into a D. simulans genetic background and tested as homozygotes for viability, male fertility, and female fertility. The entire third chromosome was covered with partially overlapping segments. Many segments were male sterile, while none were female sterile or lethal, confirming previous reports of the rapid evolution of hybrid male sterility (HMS). A statistical model was developed to quantify the HMS accumulation. In comparison with previous work on the X chromosome, we estimate that the X has approximately 2.5 times the density of HMS factors as the autosomes. We also estimate that the whole genome contains approximately 15 HMS "equivalents"-i.e., 15 times the minimum number of incompatibility factors necessary to cause complete sterility. Although some caveats for the quantitative estimate of a 2.5-fold density difference are described, this study supports the notion that the X chromosome plays a special role in the evolution of reproductive isolation. Possible mechanisms of a "large X" effect include selective fixation of new mutations that are recessive or partially recessive and the evolution of sex-ratio distortion systems.

In vitro establishment of the hybrid rootstock ‘Garfi x Nemared’ (Garnem for peach

Directory of Open Access Journals (Sweden)

Limberg Guevara Salguero

2016-04-01

Full Text Available The interspecific hybrid between almond and peach, ‘Garfield x Nemared’ (Prunus dulcis (Mill D.A.Webb x Prunus persica (L. Batsch. has become very important as rootstocks for peach in Bolivia, but propagation by traditional methods of this hybrid has been very difficult. In the present study the aim was to in vitro establishment of this hybrid. As initial explants, nodal segments from mother plants, growing under controlled culture conditions, were used. For disinfection two concentrations of sodium hypochlorite (0.5 and 0.75% and time (10 and 12 min were tested. The greatest percentage of establishment was achieved using 0.75% NaClO for 12 min in an MS culture medium free of growth regulators. A 100% control of the phenols oxidation was achieved with the combination of mother plants growing under 50% shade, young buds, use of 150 mg l-1 citric acid at the end of the disinfection process and into the culture medium and then place the test tubes with the nodal segments one week in the dark.   Keywords: interspecific hybrid, Prunus, tissue culture

Single-Molecule FISH Reveals Non-selective Packaging of Rift Valley Fever Virus Genome Segments.

Directory of Open Access Journals (Sweden)

Paul J Wichgers Schreur

2016-08-01

Full Text Available The bunyavirus genome comprises a small (S, medium (M, and large (L RNA segment of negative polarity. Although genome segmentation confers evolutionary advantages by enabling genome reassortment events with related viruses, genome segmentation also complicates genome replication and packaging. Accumulating evidence suggests that genomes of viruses with eight or more genome segments are incorporated into virions by highly selective processes. Remarkably, little is known about the genome packaging process of the tri-segmented bunyaviruses. Here, we evaluated, by single-molecule RNA fluorescence in situ hybridization (FISH, the intracellular spatio-temporal distribution and replication kinetics of the Rift Valley fever virus (RVFV genome and determined the segment composition of mature virions. The results reveal that the RVFV genome segments start to replicate near the site of infection before spreading and replicating throughout the cytoplasm followed by translocation to the virion assembly site at the Golgi network. Despite the average intracellular S, M and L genome segments approached a 1:1:1 ratio, major differences in genome segment ratios were observed among cells. We also observed a significant amount of cells lacking evidence of M-segment replication. Analysis of two-segmented replicons and four-segmented viruses subsequently confirmed the previous notion that Golgi recruitment is mediated by the Gn glycoprotein. The absence of colocalization of the different segments in the cytoplasm and the successful rescue of a tri-segmented variant with a codon shuffled M-segment suggested that inter-segment interactions are unlikely to drive the copackaging of the different segments into a single virion. The latter was confirmed by direct visualization of RNPs inside mature virions which showed that the majority of virions lack one or more genome segments. Altogether, this study suggests that RVFV genome packaging is a non-selective process.

Probing the transition state for nucleic acid hybridization using phi-value analysis.

Science.gov (United States)

Kim, Jandi; Shin, Jong-Shik

2010-04-27

Genetic regulation by noncoding RNA elements such as microRNA and small interfering RNA (siRNA) involves hybridization of a short single-stranded RNA with a complementary segment in a target mRNA. The physical basis of the hybridization process between the structured nucleic acids is not well understood primarily because of the lack of information about the transition-state structure. Here we use transition-state theory, inspired by phi-value analysis in protein folding studies, to provide quantitative analysis of the relationship between changes in the secondary structure stability and the activation free energy. Time course monitoring of the hybridization reaction was performed under pseudo-steady-state conditions using a single fluorophore. The phi-value analysis indicates that the native secondary structure remains intact in the transition state. The nativelike transition state was confirmed via examination of the salt dependence of the hybridization kinetics, indicating that the number of sodium ions associated with the transition state was not substantially affected by changes in the native secondary structure. These results propose that hybridization between structured nucleic acids undergoes a transition state leading to formation of a nucleation complex and then is followed by sequential displacement of preexisting base pairings involving successive small energy barriers. The proposed mechanism might provide new insight into physical processes during small RNA-mediated gene silencing, which is essential to selection of a target mRNA segment for siRNA design.

Abdomen and spinal cord segmentation with augmented active shape models.

Science.gov (United States)

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

2016-07-01

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

Multiple Vehicle Detection and Segmentation in Malaysia Traffic Flow

Science.gov (United States)

Fariz Hasan, Ahmad; Fikri Che Husin, Mohd; Affendi Rosli, Khairul; Norhafiz Hashim, Mohd; Faiz Zainal Abidin, Amar

2018-03-01

Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. By rapid number of vehicles on the road as well as significant increase on cameras dictated the need for traffic surveillance systems. This system can take over the burden some task was performed by human operator in traffic monitoring centre. The main technique proposed by this paper is concentrated on developing a multiple vehicle detection and segmentation focusing on monitoring through Closed Circuit Television (CCTV) video. The system is able to automatically segment vehicle extracted from heavy traffic scene by optical flow estimation alongside with blob analysis technique in order to detect the moving vehicle. Prior to segmentation, blob analysis technique will compute the area of interest region corresponding to moving vehicle which will be used to create bounding box on that particular vehicle. Experimental validation on the proposed system was performed and the algorithm is demonstrated on various set of traffic scene.

A semi-supervised segmentation algorithm as applied to k-means ...

African Journals Online (AJOL)

Segmentation (or partitioning) of data for the purpose of enhancing predictive modelling is a well-established practice in the banking industry. Unsupervised and supervised approaches are the two main streams of segmentation and examples exist where the application of these techniques improved the performance of ...

3D hybrid profile order technique in a single breath-hold 3D T2-weighted fast spin-echo sequence: Usefulness in diagnosis of small liver lesions.

Science.gov (United States)

Hirata, Kenichiro; Nakaura, Takeshi; Okuaki, Tomoyuki; Tsuda, Noriko; Taguchi, Narumi; Oda, Seitaro; Utsunomiya, Daisuke; Yamashita, Yasuyuki

2018-01-01

We compared the efficacy of three-dimensional (3D) isotropic T2-weighted fast spin-echo imaging using a 3D hybrid profile order technique with a single-breath-hold (3D-Hybrid BH) with a two-dimensional (2D) T2-weighted fast spin-echo conventional respiratory-gated (2D-Conventional RG) technique for visualising small liver lesions. This study was approved by our institutional review board. The requirement to obtain written informed consent was waived. Fifty patients with small (≤15mm) hepatocellular carcinomas (HCC) (n=26), or benign cysts (n=24), had undergone hepatic MRI including both 2D-Conventional RG and 3D-Hybrid BH. We calculated the signal-to-noise ratio (SNR) and tumour-to-liver contrast (TLC). The diagnostic performance of the two protocols was analysed. The image acquisition time was 89% shorter with the 3D-Hybrid BH than with 2D-Conventional RG. There was no significant difference in the SNR between the two protocols. The area under the curve (AUC) of the TLC was significantly higher on 3D-Hybrid BH than on 2D-Conventional RG. The 3D-Hybrid BH sequence significantly improved diagnostic performance for small liver lesions with a shorter image acquisition time without sacrificing accuracy. Copyright © 2017. Published by Elsevier B.V.

Asymmetric similarity-weighted ensembles for image segmentation

DEFF Research Database (Denmark)

Cheplygina, V.; Van Opbroek, A.; Ikram, M. A.

2016-01-01

Supervised classification is widely used for image segmentation. To work effectively, these techniques need large amounts of labeled training data, that is representative of the test data. Different patient groups, different scanners or different scanning protocols can lead to differences between...... the images, thus representative data might not be available. Transfer learning techniques can be used to account for these differences, thus taking advantage of all the available data acquired with different protocols. We investigate the use of classifier ensembles, where each classifier is weighted...... and the direction of measurement needs to be chosen carefully. We also show that a point set similarity measure is robust across different studies, and outperforms state-of-the-art results on a multi-center brain tissue segmentation task....

SEGMENTATION OF MITOCHONDRIA IN ELECTRON MICROSCOPY IMAGES USING ALGEBRAIC CURVES.

Science.gov (United States)

Seyedhosseini, Mojtaba; Ellisman, Mark H; Tasdizen, Tolga

2013-01-01

High-resolution microscopy techniques have been used to generate large volumes of data with enough details for understanding the complex structure of the nervous system. However, automatic techniques are required to segment cells and intracellular structures in these multi-terabyte datasets and make anatomical analysis possible on a large scale. We propose a fully automated method that exploits both shape information and regional statistics to segment irregularly shaped intracellular structures such as mitochondria in electron microscopy (EM) images. The main idea is to use algebraic curves to extract shape features together with texture features from image patches. Then, these powerful features are used to learn a random forest classifier, which can predict mitochondria locations precisely. Finally, the algebraic curves together with regional information are used to segment the mitochondria at the predicted locations. We demonstrate that our method outperforms the state-of-the-art algorithms in segmentation of mitochondria in EM images.

Synchronous Supraglottic and Esophageal Squamous Cell Carcinomas Treated with a Monoisocentric Hybrid Intensity-Modulated Radiation Technique

Directory of Open Access Journals (Sweden)

Christian L. Barney

2018-01-01

Full Text Available Risk factors for squamous cell carcinomas (SCCs of the head and neck (HN and esophagus are similar. As such, synchronous primary tumors in these areas are not entirely uncommon. Definitive chemoradiation (CRT is standard care for locally advanced HNSCC and is a preferred option for inoperable esophageal SCC. Simultaneous treatment of both primaries with CRT can present technical challenges. We report a case of synchronous supraglottic and esophageal SCC primary tumors, highlighting treatment with a monoisocentric hybrid radiation technique and normal tissue toxicity considerations.

Hybrid FOSS Project

Data.gov (United States)

National Aeronautics and Space Administration — Armstrong researchers are continuing their efforts to further develop FOSS technologies. A hybrid FOSS technique (HyFOSS) employs conventional continuous grating...

Stimulation and inhibition of bacterial growth by caffeine dependent on chloramphenicol and a phenolic uncoupler--a ternary toxicity study using microfluid segment technique.

Science.gov (United States)

Cao, Jialan; Kürsten, Dana; Schneider, Steffen; Köhler, J Michael

2012-10-01

A droplet-based microfluidic technique for the fast generation of three dimensional concentration spaces within nanoliter segments was introduced. The technique was applied for the evaluation of the effect of two selected antibiotic substances on the toxicity and activation of bacterial growth by caffeine. Therefore a three-dimensional concentration space was completely addressed by generating large sequences with about 1150 well separated microdroplets containing 216 different combinations of concentrations. To evaluate the toxicity of the ternary mixtures a time-resolved miniaturized optical double endpoint detection unit using a microflow-through fluorimeter and a two channel microflow-through photometer was used for the simultaneous analysis of changes on the endogenous cellular fluorescence signal and on the cell density of E. coli cultivated inside 500 nL microfluid segments. Both endpoints supplied similar results for the dose related cellular response. Strong non-linear combination effects, concentration dependent stimulation and the formation of activity summits on bolographic maps were determined. The results reflect a complex response of growing bacterial cultures in dependence on the combined effectors. A strong caffeine induced enhancement of bacterial growth was found at sublethal chloramphenicol and sublethal 2,4-dinitrophenol concentrations. The reliability of the method was proved by a high redundancy of fluidic experiments. The results indicate the importance of multi-parameter investigations for toxicological studies and prove the potential of the microsegmented flow technique for such requirements.

Human hybrid hybridoma

Energy Technology Data Exchange (ETDEWEB)

Tiebout, R.F.; van Boxtel-Oosterhof, F.; Stricker, E.A.M.; Zeijlemaker, W.P.

1987-11-15

Hybrid hybridomas are obtained by fusion of two cells, each producing its own antibody. Several authors have reported the construction of murine hybrid hybridomas with the aim to obtain bispecific monoclonal antibodies. The authors have investigated, in a model system, the feasibility of constructing a human hybrid hybridoma. They fused two monoclonal cell lines: an ouabain-sensitive and azaserine/hypoxanthine-resistant Epstein-Barr virus-transformed human cell line that produces an IgG1kappa antibody directed against tetanus toxiod and an azaserine/hypoxanthine-sensitive and ouabain-resistant human-mouse xenohybrid cell line that produces a human IgG1lambda antibody directed against hepatitis-B surface antigen. Hybrid hybridoma cells were selected in culture medium containing azaserine/hypoxanthine and ouabain. The hybrid nature of the secreted antibodies was analyzed by means of two antigen-specific immunoassay. The results show that it is possible, with the combined use of transformation and xenohybridization techniques, to construct human hybrid hybridomas that produce bispecific antibodies. Bispecific antibodies activity was measured by means of two radioimmunoassays.

Novel hard mask fabrication method for hybrid plasmonic waveguide and metasurfaces

DEFF Research Database (Denmark)

Choudhury, Sajid; Zenin, Vladimir A.; Saha, Soham

2017-01-01

A hybrid plasmonic waveguide fabrication technique has been developed and waveguides fabricated using this technique have been demonstrated experimentally. The developed technique can be utilized for creating similar hybrid waveguide structures and metasurfaces with an array of material platforms...

GPU accelerated fuzzy connected image segmentation by using CUDA.

Science.gov (United States)

Zhuge, Ying; Cao, Yong; Miller, Robert W

2009-01-01

Image segmentation techniques using fuzzy connectedness principles have shown their effectiveness in segmenting a variety of objects in several large applications in recent years. However, one problem of these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays commodity graphics hardware provides high parallel computing power. In this paper, we present a parallel fuzzy connected image segmentation algorithm on Nvidia's Compute Unified Device Architecture (CUDA) platform for segmenting large medical image data sets. Our experiments based on three data sets with small, medium, and large data size demonstrate the efficiency of the parallel algorithm, which achieves a speed-up factor of 7.2x, 7.3x, and 14.4x, correspondingly, for the three data sets over the sequential implementation of fuzzy connected image segmentation algorithm on CPU.

Performance evaluation of a hybrid-passive landfill leachate treatment system using multivariate statistical techniques

Energy Technology Data Exchange (ETDEWEB)

Wallace, Jack, E-mail: jack.wallace@ce.queensu.ca [Department of Civil Engineering, Queen’s University, Ellis Hall, 58 University Avenue, Kingston, Ontario K7L 3N6 (Canada); Champagne, Pascale, E-mail: champagne@civil.queensu.ca [Department of Civil Engineering, Queen’s University, Ellis Hall, 58 University Avenue, Kingston, Ontario K7L 3N6 (Canada); Monnier, Anne-Charlotte, E-mail: anne-charlotte.monnier@insa-lyon.fr [National Institute for Applied Sciences – Lyon, 20 Avenue Albert Einstein, 69621 Villeurbanne Cedex (France)

2015-01-15

Highlights: • Performance of a hybrid passive landfill leachate treatment system was evaluated. • 33 Water chemistry parameters were sampled for 21 months and statistically analyzed. • Parameters were strongly linked and explained most (>40%) of the variation in data. • Alkalinity, ammonia, COD, heavy metals, and iron were criteria for performance. • Eight other parameters were key in modeling system dynamics and criteria. - Abstract: A pilot-scale hybrid-passive treatment system operated at the Merrick Landfill in North Bay, Ontario, Canada, treats municipal landfill leachate and provides for subsequent natural attenuation. Collected leachate is directed to a hybrid-passive treatment system, followed by controlled release to a natural attenuation zone before entering the nearby Little Sturgeon River. The study presents a comprehensive evaluation of the performance of the system using multivariate statistical techniques to determine the interactions between parameters, major pollutants in the leachate, and the biological and chemical processes occurring in the system. Five parameters (ammonia, alkalinity, chemical oxygen demand (COD), “heavy” metals of interest, with atomic weights above calcium, and iron) were set as criteria for the evaluation of system performance based on their toxicity to aquatic ecosystems and importance in treatment with respect to discharge regulations. System data for a full range of water quality parameters over a 21-month period were analyzed using principal components analysis (PCA), as well as principal components (PC) and partial least squares (PLS) regressions. PCA indicated a high degree of association for most parameters with the first PC, which explained a high percentage (>40%) of the variation in the data, suggesting strong statistical relationships among most of the parameters in the system. Regression analyses identified 8 parameters (set as independent variables) that were most frequently retained for modeling

The small angle neutron scattering study on the segmented polyurethane

International Nuclear Information System (INIS)

Sudirman; Gunawan; Prasetyo, S.M.; Karo Karo, A.; Lahagu, I.M.; Darwinto, Tri

1999-01-01

The distance between hard segment (HS) and soft segment (SS) of segmented polyurethane have been determined using the Small Angle Neutron Scattering (SANS) technique. The segmented Polyurethanes (SPU) are linear multiblock copolymers, which include elastomer thermoplastic. SPU consist of hard segment and soft segment, each has tendency to make a group with similar type to form a domain. The soft segments used were polypropylene glycol (PPG) and 4,4 diphenylmethane diisocyanate (MDI), while l,4 butanediol (BD) was used as hard segment. The characteristic of SPU depends on its phase structure which is affected by several factors, such as type of chemical formula and the composition of the HS and SS, solvent as well as the synthesizing process. The samples used in this study were SPU56 and SPU68. Based on the appearance of SANS profile, it was obtained that domain distances are 12.32 nm for the SPU56 and 19 nm for the SPU68. (author)

Automated brain structure segmentation based on atlas registration and appearance models

DEFF Research Database (Denmark)

van der Lijn, Fedde; de Bruijne, Marleen; Klein, Stefan

2012-01-01

Accurate automated brain structure segmentation methods facilitate the analysis of large-scale neuroimaging studies. This work describes a novel method for brain structure segmentation in magnetic resonance images that combines information about a structure’s location and appearance. The spatial...... with different magnetic resonance sequences, in which the hippocampus and cerebellum were segmented by an expert. Furthermore, the method is compared to two other segmentation techniques that were applied to the same data. Results show that the atlas- and appearance-based method produces accurate results...

SEGMENTING RETAIL MARKETS ON STORE IMAGE USING A CONSUMER-BASED METHODOLOGY

NARCIS (Netherlands)

STEENKAMP, JBEM; WEDEL, M

1991-01-01

Various approaches to segmenting retail markets based on store image are reviewed, including methods that have not yet been applied to retailing problems. It is argued that a recently developed segmentation technique, fuzzy clusterwise regression analysis (FCR), holds high potential for store-image

Segmentation and Quantification for Angle-Closure Glaucoma Assessment in Anterior Segment OCT.

Science.gov (United States)

Fu, Huazhu; Xu, Yanwu; Lin, Stephen; Zhang, Xiaoqin; Wong, Damon Wing Kee; Liu, Jiang; Frangi, Alejandro F; Baskaran, Mani; Aung, Tin

2017-09-01

Angle-closure glaucoma is a major cause of irreversible visual impairment and can be identified by measuring the anterior chamber angle (ACA) of the eye. The ACA can be viewed clearly through anterior segment optical coherence tomography (AS-OCT), but the imaging characteristics and the shapes and locations of major ocular structures can vary significantly among different AS-OCT modalities, thus complicating image analysis. To address this problem, we propose a data-driven approach for automatic AS-OCT structure segmentation, measurement, and screening. Our technique first estimates initial markers in the eye through label transfer from a hand-labeled exemplar data set, whose images are collected over different patients and AS-OCT modalities. These initial markers are then refined by using a graph-based smoothing method that is guided by AS-OCT structural information. These markers facilitate segmentation of major clinical structures, which are used to recover standard clinical parameters. These parameters can be used not only to support clinicians in making anatomical assessments, but also to serve as features for detecting anterior angle closure in automatic glaucoma screening algorithms. Experiments on Visante AS-OCT and Cirrus high-definition-OCT data sets demonstrate the effectiveness of our approach.

Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming

Science.gov (United States)

Chiu, Stephanie J.; Toth, Cynthia A.; Bowes Rickman, Catherine; Izatt, Joseph A.; Farsiu, Sina

2012-01-01

This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique. PMID:22567602

Nanocomposite metal amorphous-carbon thin films deposited by hybrid PVD and PECVD technique.

Science.gov (United States)

Teixeira, V; Soares, P; Martins, A J; Carneiro, J; Cerqueira, F

2009-07-01

Carbon based films can combine the properties of solid lubricating graphite structure and hard diamond crystal structure, i.e., high hardness, chemical inertness, high thermal conductivity and optical transparency without the crystalline structure of diamond. Issues of fundamental importance associated with nanocarbon coatings are reducing stress, improving adhesion and compatibility with substrates. In this work new nanocomposite coatings with improved toughness based in nanocrystalline phases of metals and ceramics embedded in amorphous carbon matrix are being developed within the frame of a research project: nc-MeNxCy/a-C(Me) with Me = Mo, Si, Al, Ti, etc. Carbide forming metal/carbon (Me/C) composite films with Me = Mo, W or Ti possess appropriate properties to overcome the limitation of pure DLC films. These novel coating architectures will be adopted with the objective to decrease residual stress, improve adherence and fracture toughness, obtain low friction coefficient and high wear-resistance. Nanocomposite DLC's films were deposited by hybrid technique using a PVD-Physically Vapor Deposition (magnetron sputtering) and Plasma Enhanced Chemical Vapor Deposition (PECVD), by the use of CH4 gas. The parameters varied were: deposition time, substrate temperature (180 degrees C) and dopant (Si + Mo) of the amorphous carbon matrix. All the depositions were made on silicon wafers and steel substrates precoated with a silicon inter-layer. The characterisation of the film's physico-mechanical properties will be presented in order to understand the influence of the deposition parameters and metal content used within the a-C matrix in the thin film properties. Film microstructure and film hybridization state was characterized by Raman Spectroscopy. In order to characterize morphology SEM and AFM will be used. Film composition was measured by Energy-Dispersive X-ray analysis (EDS) and by X-ray photoelectron spectroscopy (XPS). The contact angle for the produced DLC's on

Hybridization and sequencing of nucleic acids using base pair mismatches

Science.gov (United States)

Fodor, Stephen P. A.; Lipshutz, Robert J.; Huang, Xiaohua

2001-01-01

Devices and techniques for hybridization of nucleic acids and for determining the sequence of nucleic acids. Arrays of nucleic acids are formed by techniques, preferably high resolution, light-directed techniques. Positions of hybridization of a target nucleic acid are determined by, e.g., epifluorescence microscopy. Devices and techniques are proposed to determine the sequence of a target nucleic acid more efficiently and more quickly through such synthesis and detection techniques.

The Technique of Changing the Drive Method of Micro Step Drive and Sensorless Drive for Hybrid Stepping Motor

Science.gov (United States)

Yoneda, Makoto; Dohmeki, Hideo

The position control system with the advantage large torque, low vibration, and high resolution can be obtained by the constant current micro step drive applied to hybrid stepping motor. However loss is large, in order not to be concerned with load torque but to control current uniformly. As the one technique of a position control system in which high efficiency is realizable, the same sensorless control as a permanent magnet motor is effective. But, it was the purpose that the control method proposed until now controls speed. Then, this paper proposed changing the drive method of micro step drive and sensorless drive. The change of the drive method was verified from the simulation and the experiment. On no load, it was checked not producing change of a large speed at the time of a change by making electrical angle and carrying out zero reset of the integrator. On load, it was checked that a large speed change arose. The proposed system could change drive method by setting up the initial value of an integrator using the estimated result, without producing speed change. With this technique, the low loss position control system, which employed the advantage of the hybrid stepping motor, has been built.

Segmentation of the Breast Region in Digital Mammograms and Detection of Masses

OpenAIRE

Armen Sahakyan; Hakop Sarukhanyan

2012-01-01

The mammography is the most effective procedure for an early diagnosis of the breast cancer. Finding an accurate and efficient breast region segmentation technique still remains a challenging problem in digital mammography. In this paper we explore an automated technique for mammogram segmentation. The proposed algorithm uses morphological preprocessing algorithm in order to: remove digitization noises and separate background region from the breast profile region for further edge detection an...

Unsupervised motion-based object segmentation refined by color

Science.gov (United States)

Piek, Matthijs C.; Braspenning, Ralph; Varekamp, Chris

2003-06-01

chance of the wrong position producing a good match. Consequently, a number of methods exist which combine motion and colour segmentation. These methods use colour segmentation as a base for the motion segmentation and estimation or perform an independent colour segmentation in parallel which is in some way combined with the motion segmentation. The presented method uses both techniques to complement each other by first segmenting on motion cues and then refining the segmentation with colour. To our knowledge few methods exist which adopt this approach. One example is te{meshrefine}. This method uses an irregular mesh, which hinders its efficient implementation in consumer electronics devices. Furthermore, the method produces a foreground/background segmentation, while our applications call for the segmentation of multiple objects. NEW METHOD As mentioned above we start with motion segmentation and refine the edges of this segmentation with a pixel resolution colour segmentation method afterwards. There are several reasons for this approach: + Motion segmentation does not produce the oversegmentation which colour segmentation methods normally produce, because objects are more likely to have colour discontinuities than motion discontinuities. In this way, the colour segmentation only has to be done at the edges of segments, confining the colour segmentation to a smaller part of the image. In such a part, it is more likely that the colour of an object is homogeneous. + This approach restricts the computationally expensive pixel resolution colour segmentation to a subset of the image. Together with the very efficient 3DRS motion estimation algorithm, this helps to reduce the computational complexity. + The motion cue alone is often enough to reliably distinguish objects from one another and the background. To obtain the motion vector fields, a variant of the 3DRS block-based motion estimator which analyses three frames of input was used. The 3DRS motion estimator is known

Analysis of prestressed concrete wall segments

International Nuclear Information System (INIS)

Koziak, B.D.P.; Murray, D.W.

1979-06-01

An iterative numerical technique for analysing the biaxial response of reinforced and prestressed concrete wall segments subject to combinations of prestressing, creep, temperature and live loads is presented. Two concrete constitutive relations are available for this analysis. The first is a uniaxially bilinear model with a tension cut-off. The second is a nonlinear biaxial relation incorporating equivalent uniaxial strains to remove the Poissons's ratio effect under biaxial loading. Predictions from both the bilinear and nonlinear model are compared with observations from experimental wall segments tested in tension. The nonlinear model results are shown to be close to those of the test segments, while the bilinear results are good up to cracking. Further comparisons are made between the nonlinear analysis using constant membrane force-moment ratios, constant membrane force-curvature ratios, and a nonlinear finite difference analysis of a test containment structure. Neither nonlinear analysis could predict the reponse of every wall segment within the structure, but the constant membrane force-moment analysis provided lower bound results. (author)

Recent Advances on Hybrid Intelligent Systems

CERN Document Server

Melin, Patricia; Kacprzyk, Janusz

2013-01-01

This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algo...

Development of novel segmented-plate linearly tunable MEMS capacitors

International Nuclear Information System (INIS)

Shavezipur, M; Khajepour, A; Hashemi, S M

2008-01-01

In this paper, novel MEMS capacitors with flexible moving electrodes and high linearity and tunability are presented. The moving plate is divided into small and rigid segments connected to one another by connecting beams at their end nodes. Under each node there is a rigid step which selectively limits the vertical displacement of the node. A lumped model is developed to analytically solve the governing equations of coupled structural-electrostatic physics with mechanical contact. Using the analytical solver, an optimization program finds the best set of step heights that provides the highest linearity. Analytical and finite element analyses of two capacitors with three-segmented- and six-segmented-plate confirm that the segmentation technique considerably improves the linearity while the tunability remains as high as that of a conventional parallel-plate capacitor. Moreover, since the new designs require customized fabrication processes, to demonstrate the applicability of the proposed technique for standard processes, a modified capacitor with flexible steps designed for PolyMUMPs is introduced. Dimensional optimization of the modified design results in a combination of high linearity and tunability. Constraining the displacement of the moving plate can be extended to more complex geometries to obtain smooth and highly linear responses

Application of neural network in market segmentation: A review on recent trends

Directory of Open Access Journals (Sweden)

Manojit Chattopadhyay

2012-04-01

Full Text Available Despite the significance of Artificial Neural Network (ANN algorithm to market segmentation, there is a need of a comprehensive literature review and a classification system for it towards identification of future trend of market segmentation research. The present work is the first identifiable academic literature review of the application of neural network based techniques to segmentation. Our study has provided an academic database of literature between the periods of 2000–2010 and proposed a classification scheme for the articles. One thousands (1000 articles have been identified, and around 100 relevant selected articles have been subsequently reviewed and classified based on the major focus of each paper. Findings of this study indicated that the research area of ANN based applications are receiving most research attention and self organizing map based applications are second in position to be used in segmentation. The commonly used models for market segmentation are data mining, intelligent system etc. Our analysis furnishes a roadmap to guide future research and aid knowledge accretion and establishment pertaining to the application of ANN based techniques in market segmentation. Thus the present work will significantly contribute to both the industry and academic research in business and marketing as a sustainable valuable knowledge source of market segmentation with the future trend of ANN application in segmentation.

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

An improved FSL-FIRST pipeline for subcortical gray matter segmentation to study abnormal brain anatomy using quantitative susceptibility mapping (QSM).

Science.gov (United States)

Feng, Xiang; Deistung, Andreas; Dwyer, Michael G; Hagemeier, Jesper; Polak, Paul; Lebenberg, Jessica; Frouin, Frédérique; Zivadinov, Robert; Reichenbach, Jürgen R; Schweser, Ferdinand

2017-06-01

Accurate and robust segmentation of subcortical gray matter (SGM) nuclei is required in many neuroimaging applications. FMRIB's Integrated Registration and Segmentation Tool (FIRST) is one of the most popular software tools for automated subcortical segmentation based on T 1 -weighted (T1w) images. In this work, we demonstrate that FIRST tends to produce inaccurate SGM segmentation results in the case of abnormal brain anatomy, such as present in atrophied brains, due to a poor spatial match of the subcortical structures with the training data in the MNI space as well as due to insufficient contrast of SGM structures on T1w images. Consequently, such deviations from the average brain anatomy may introduce analysis bias in clinical studies, which may not always be obvious and potentially remain unidentified. To improve the segmentation of subcortical nuclei, we propose to use FIRST in combination with a special Hybrid image Contrast (HC) and Non-Linear (nl) registration module (HC-nlFIRST), where the hybrid image contrast is derived from T1w images and magnetic susceptibility maps to create subcortical contrast that is similar to that in the Montreal Neurological Institute (MNI) template. In our approach, a nonlinear registration replaces FIRST's default linear registration, yielding a more accurate alignment of the input data to the MNI template. We evaluated our method on 82 subjects with particularly abnormal brain anatomy, selected from a database of >2000 clinical cases. Qualitative and quantitative analyses revealed that HC-nlFIRST provides improved segmentation compared to the default FIRST method. Copyright © 2017 Elsevier Inc. All rights reserved.

Using alternative segmentation techniques to examine residential customer`s energy needs, wants, and preferences

Energy Technology Data Exchange (ETDEWEB)

Hollander, C.; Kidwell, S. [Union Electric Co., St. Louis, MO (United States); Banks, J.; Taylor, E. [Cambridge Reports/Research International, MA (United States)

1994-11-01

The primary objective of this study was to examine residential customers` attitudes toward energy usage, conservation, and efficiency, and to examine the implications of these attitudes for how the utility should design and communicate about programs and services in these areas. This study combined focus groups and customer surveys, and utilized several customer segmentation schemes -- grouping customers by geodemographics, as well as customers` energy and environmental values, beliefs, and opinions -- to distinguish different segments of customers.

Stereovision-Based Object Segmentation for Automotive Applications

Directory of Open Access Journals (Sweden)

Fu Shan

2005-01-01

Full Text Available Obstacle detection and classification in a complex urban area are highly demanding, but desirable for pedestrian protection, stop & go, and enhanced parking aids. The most difficult task for the system is to segment objects from varied and complicated background. In this paper, a novel position-based object segmentation method has been proposed to solve this problem. According to the method proposed, object segmentation is performed in two steps: in depth map ( - plane and in layered images ( - planes. The stereovision technique is used to reconstruct image points and generate the depth map. Objects are detected in the depth map. Afterwards, the original edge image is separated into different layers based on the distance of detected objects. Segmentation performed in these layered images can be easier and more reliable. It has been proved that the proposed method offers robust detection of potential obstacles and accurate measurement of their location and size.

A Hybrid Semi-Digital Transimpedance Amplifier With Noise Cancellation Technique for Nanopore-Based DNA Sequencing.

Science.gov (United States)

Hsu, Chung-Lun; Jiang, Haowei; Venkatesh, A G; Hall, Drew A

2015-10-01

Over the past two decades, nanopores have been a promising technology for next generation deoxyribonucleic acid (DNA) sequencing. Here, we present a hybrid semi-digital transimpedance amplifier (HSD-TIA) to sense the minute current signatures introduced by single-stranded DNA (ssDNA) translocating through a nanopore, while discharging the baseline current using a semi-digital feedback loop. The amplifier achieves fast settling by adaptively tuning a DC compensation current when a step input is detected. A noise cancellation technique reduces the total input-referred current noise caused by the parasitic input capacitance. Measurement results show the performance of the amplifier with 31.6 M Ω mid-band gain, 950 kHz bandwidth, and 8.5 fA/ √Hz input-referred current noise, a 2× noise reduction due to the noise cancellation technique. The settling response is demonstrated by observing the insertion of a protein nanopore in a lipid bilayer. Using the nanopore, the HSD-TIA was able to measure ssDNA translocation events.

Hybrid mesons with auxiliary fields

International Nuclear Information System (INIS)

Buisseret, F.; Mathieu, V.

2006-01-01

Hybrid mesons are exotic mesons in which the color field is not in the ground state. Their understanding deserves interest from a theoretical point of view, because it is intimately related to nonperturbative aspects of QCD. Moreover, it seems that some recently detected particles, such as the π 1 (1600) and the Y(4260), are serious hybrid candidates. In this work, we investigate the description of such exotic hadrons by applying the auxiliary fields technique (also known as the einbein field method) to the widely used spinless Salpeter Hamiltonian with appropriate linear confinement. Instead of the usual numerical resolution, this technique allows to find simplified analytical mass spectra and wave functions of the Hamiltonian, which still lead to reliable qualitative predictions. We analyse and compare two different descriptions of hybrid mesons, namely a two-body q system with an excited flux tube, or a three-body qg system. We also compute the masses of the 1 -+ hybrids. Our results are shown to be in satisfactory agreement with lattice QCD and other effective models. (orig.)

Genomic structural variation-mediated allelic suppression causes hybrid male sterility in rice.

Science.gov (United States)

Shen, Rongxin; Wang, Lan; Liu, Xupeng; Wu, Jiang; Jin, Weiwei; Zhao, Xiucai; Xie, Xianrong; Zhu, Qinlong; Tang, Huiwu; Li, Qing; Chen, Letian; Liu, Yao-Guang

2017-11-03

Hybrids between divergent populations commonly show hybrid sterility; this reproductive barrier hinders hybrid breeding of the japonica and indica rice (Oryza sativa L.) subspecies. Here we show that structural changes and copy number variation at the Sc locus confer japonica-indica hybrid male sterility. The japonica allele, Sc-j, contains a pollen-essential gene encoding a DUF1618-domain protein; the indica allele, Sc-i, contains two or three tandem-duplicated ~ 28-kb segments, each carrying an Sc-j-homolog with a distinct promoter. In Sc-j/Sc-i hybrids, the high-expression of Sc-i in sporophytic cells causes suppression of Sc-j expression in pollen and selective abortion of Sc-j-pollen, leading to transmission ratio distortion. Knocking out one or two of the three Sc-i copies by CRISPR/Cas9 rescues Sc-j expression and male fertility. Our results reveal the gene dosage-dependent allelic suppression as a mechanism of hybrid incompatibility, and provide an effective approach to overcome the reproductive barrier for hybrid breeding.

Automatic Image Segmentation Using Active Contours with Univariate Marginal Distribution

Directory of Open Access Journals (Sweden)

I. Cruz-Aceves

2013-01-01

Full Text Available This paper presents a novel automatic image segmentation method based on the theory of active contour models and estimation of distribution algorithms. The proposed method uses the univariate marginal distribution model to infer statistical dependencies between the control points on different active contours. These contours have been generated through an alignment process of reference shape priors, in order to increase the exploration and exploitation capabilities regarding different interactive segmentation techniques. This proposed method is applied in the segmentation of the hollow core in microscopic images of photonic crystal fibers and it is also used to segment the human heart and ventricular areas from datasets of computed tomography and magnetic resonance images, respectively. Moreover, to evaluate the performance of the medical image segmentations compared to regions outlined by experts, a set of similarity measures has been adopted. The experimental results suggest that the proposed image segmentation method outperforms the traditional active contour model and the interactive Tseng method in terms of segmentation accuracy and stability.

Epitaxial growth of hybrid nanostructures

Science.gov (United States)

Tan, Chaoliang; Chen, Junze; Wu, Xue-Jun; Zhang, Hua

2018-02-01

Hybrid nanostructures are a class of materials that are typically composed of two or more different components, in which each component has at least one dimension on the nanoscale. The rational design and controlled synthesis of hybrid nanostructures are of great importance in enabling the fine tuning of their properties and functions. Epitaxial growth is a promising approach to the controlled synthesis of hybrid nanostructures with desired structures, crystal phases, exposed facets and/or interfaces. This Review provides a critical summary of the state of the art in the field of epitaxial growth of hybrid nanostructures. We discuss the historical development, architectures and compositions, epitaxy methods, characterization techniques and advantages of epitaxial hybrid nanostructures. Finally, we provide insight into future research directions in this area, which include the epitaxial growth of hybrid nanostructures from a wider range of materials, the study of the underlying mechanism and determining the role of epitaxial growth in influencing the properties and application performance of hybrid nanostructures.

Japanese migration in contemporary Japan: economic segmentation and interprefectural migration.

Science.gov (United States)

Fukurai, H

1991-01-01

This paper examines the economic segmentation model in explaining 1985-86 Japanese interregional migration. The analysis takes advantage of statistical graphic techniques to illustrate the following substantive issues of interregional migration: (1) to examine whether economic segmentation significantly influences Japanese regional migration and (2) to explain socioeconomic characteristics of prefectures for both in- and out-migration. Analytic techniques include a latent structural equation (LISREL) methodology and statistical residual mapping. The residual dispersion patterns, for instance, suggest the extent to which socioeconomic and geopolitical variables explain migration differences by showing unique clusters of unexplained residuals. The analysis further points out that extraneous factors such as high residential land values, significant commuting populations, and regional-specific cultures and traditions need to be incorporated in the economic segmentation model in order to assess the extent of the model's reliability in explaining the pattern of interprefectural migration.

Assume-Guarantee Abstraction Refinement Meets Hybrid Systems

Science.gov (United States)

Bogomolov, Sergiy; Frehse, Goran; Greitschus, Marius; Grosu, Radu; Pasareanu, Corina S.; Podelski, Andreas; Strump, Thomas

2014-01-01

Compositional verification techniques in the assume- guarantee style have been successfully applied to transition systems to efficiently reduce the search space by leveraging the compositional nature of the systems under consideration. We adapt these techniques to the domain of hybrid systems with affine dynamics. To build assumptions we introduce an abstraction based on location merging. We integrate the assume-guarantee style analysis with automatic abstraction refinement. We have implemented our approach in the symbolic hybrid model checker SpaceEx. The evaluation shows its practical potential. To the best of our knowledge, this is the first work combining assume-guarantee reasoning with automatic abstraction-refinement in the context of hybrid automata.

Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

Directory of Open Access Journals (Sweden)

Jianping Hua

2004-01-01

Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

HARDWARE REALIZATION OF CANNY EDGE DETECTION ALGORITHM FOR UNDERWATER IMAGE SEGMENTATION USING FIELD PROGRAMMABLE GATE ARRAYS

Directory of Open Access Journals (Sweden)

ALEX RAJ S. M.

2017-09-01

Full Text Available Underwater images raise new challenges in the field of digital image processing technology in recent years because of its widespread applications. There are many tangled matters to be considered in processing of images collected from water medium due to the adverse effects imposed by the environment itself. Image segmentation is preferred as basal stage of many digital image processing techniques which distinguish multiple segments in an image and reveal the hidden crucial information required for a peculiar application. There are so many general purpose algorithms and techniques that have been developed for image segmentation. Discontinuity based segmentation are most promising approach for image segmentation, in which Canny Edge detection based segmentation is more preferred for its high level of noise immunity and ability to tackle underwater environment. Since dealing with real time underwater image segmentation algorithm, which is computationally complex enough, an efficient hardware implementation is to be considered. The FPGA based realization of the referred segmentation algorithm is presented in this paper.

Segmentation of dermatoscopic images by frequency domain filtering and k-means clustering algorithms.

Science.gov (United States)

Rajab, Maher I

2011-11-01

Since the introduction of epiluminescence microscopy (ELM), image analysis tools have been extended to the field of dermatology, in an attempt to algorithmically reproduce clinical evaluation. Accurate image segmentation of skin lesions is one of the key steps for useful, early and non-invasive diagnosis of coetaneous melanomas. This paper proposes two image segmentation algorithms based on frequency domain processing and k-means clustering/fuzzy k-means clustering. The two methods are capable of segmenting and extracting the true border that reveals the global structure irregularity (indentations and protrusions), which may suggest excessive cell growth or regression of a melanoma. As a pre-processing step, Fourier low-pass filtering is applied to reduce the surrounding noise in a skin lesion image. A quantitative comparison of the techniques is enabled by the use of synthetic skin lesion images that model lesions covered with hair to which Gaussian noise is added. The proposed techniques are also compared with an established optimal-based thresholding skin-segmentation method. It is demonstrated that for lesions with a range of different border irregularity properties, the k-means clustering and fuzzy k-means clustering segmentation methods provide the best performance over a range of signal to noise ratios. The proposed segmentation techniques are also demonstrated to have similar performance when tested on real skin lesions representing high-resolution ELM images. This study suggests that the segmentation results obtained using a combination of low-pass frequency filtering and k-means or fuzzy k-means clustering are superior to the result that would be obtained by using k-means or fuzzy k-means clustering segmentation methods alone. © 2011 John Wiley & Sons A/S.

Segmentation of the Speaker's Face Region with Audiovisual Correlation

Science.gov (United States)

Liu, Yuyu; Sato, Yoichi

The ability to find the speaker's face region in a video is useful for various applications. In this work, we develop a novel technique to find this region within different time windows, which is robust against the changes of view, scale, and background. The main thrust of our technique is to integrate audiovisual correlation analysis into a video segmentation framework. We analyze the audiovisual correlation locally by computing quadratic mutual information between our audiovisual features. The computation of quadratic mutual information is based on the probability density functions estimated by kernel density estimation with adaptive kernel bandwidth. The results of this audiovisual correlation analysis are incorporated into graph cut-based video segmentation to resolve a globally optimum extraction of the speaker's face region. The setting of any heuristic threshold in this segmentation is avoided by learning the correlation distributions of speaker and background by expectation maximization. Experimental results demonstrate that our method can detect the speaker's face region accurately and robustly for different views, scales, and backgrounds.

Efficient Algorithms for Segmentation of Item-Set Time Series

Science.gov (United States)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

Comparative methods for PET image segmentation in pharyngolaryngeal squamous cell carcinoma

NARCIS (Netherlands)

Zaidi, Habib; Abdoli, Mehrsima; Fuentes, Carolina Llina; El Naqa, Issam M.

Several methods have been proposed for the segmentation of F-18-FDG uptake in PET. In this study, we assessed the performance of four categories of F-18-FDG PET image segmentation techniques in pharyngolaryngeal squamous cell carcinoma using clinical studies where the surgical specimen served as the

Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation

OpenAIRE

Fu, Chichen; Lee, Soonam; Ho, David Joon; Han, Shuo; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2018-01-01

Advances in fluorescence microscopy enable acquisition of 3D image volumes with better image quality and deeper penetration into tissue. Segmentation is a required step to characterize and analyze biological structures in the images and recent 3D segmentation using deep learning has achieved promising results. One issue is that deep learning techniques require a large set of groundtruth data which is impractical to annotate manually for large 3D microscopy volumes. This paper describes a 3D d...

Fuzzy-Based Adaptive Hybrid Burst Assembly Technique for Optical Burst Switched Networks

Directory of Open Access Journals (Sweden)

Abubakar Muhammad Umaru

2014-01-01

Full Text Available The optical burst switching (OBS paradigm is perceived as an intermediate switching technology for future all-optical networks. Burst assembly that is the first process in OBS is the focus of this paper. In this paper, an intelligent hybrid burst assembly algorithm that is based on fuzzy logic is proposed. The new algorithm is evaluated against the traditional hybrid burst assembly algorithm and the fuzzy adaptive threshold (FAT burst assembly algorithm via simulation. Simulation results show that the proposed algorithm outperforms the hybrid and the FAT algorithms in terms of burst end-to-end delay, packet end-to-end delay, and packet loss ratio.

Segmented attenuation correction using artificial neural networks in positron tomography

International Nuclear Information System (INIS)

Yu, S.K.; Nahmias, C.

1996-01-01

The measured attenuation correction technique is widely used in cardiac positron tomographic studies. However, the success of this technique is limited because of insufficient counting statistics achievable in practical transmission scan times, and of the scattered radiation in transmission measurement which leads to an underestimation of the attenuation coefficients. In this work, a segmented attenuation correction technique has been developed that uses artificial neural networks. The technique has been validated in phantoms and verified in human studies. The results indicate that attenuation coefficients measured in the segmented transmission image are accurate and reproducible. Activity concentrations measured in the reconstructed emission image can also be recovered accurately using this new technique. The accuracy of the technique is subject independent and insensitive to scatter contamination in the transmission data. This technique has the potential of reducing the transmission scan time, and satisfactory results are obtained if the transmission data contain about 400 000 true counts per plane. It can predict accurately the value of any attenuation coefficient in the range from air to water in a transmission image with or without scatter correction. (author)

Optimal Performance Monitoring of Hybrid Mid-Infrared Wavelength MIMO Free Space Optical and RF Wireless Networks in Fading Channels

Science.gov (United States)

Schmidt, Barnet Michael

An optimal performance monitoring metric for a hybrid free space optical and radio-frequency (RF) wireless network, the Outage Capacity Objective Function, is analytically developed and studied. Current and traditional methods of performance monitoring of both optical and RF wireless networks are centered on measurement of physical layer parameters, the most common being signal-to-noise ratio, error rate, Q factor, and eye diagrams, occasionally combined with link-layer measurements such as data throughput, retransmission rate, and/or lost packet rate. Network management systems frequently attempt to predict or forestall network failures by observing degradations of these parameters and to attempt mitigation (such as offloading traffic, increasing transmitter power, reducing the data rate, or combinations thereof) prior to the failure. These methods are limited by the frequent low sensitivity of the physical layer parameters to the atmospheric optical conditions (measured by optical signal-to-noise ratio) and the radio frequency fading channel conditions (measured by signal-to-interference ratio). As a result of low sensitivity, measurements of this type frequently are unable to predict impending failures sufficiently in advance for the network management system to take corrective action prior to the failure. We derive and apply an optimal measure of hybrid network performance based on the outage capacity of the hybrid optical and RF channel, the outage capacity objective function. The objective function provides high sensitivity and reliable failure prediction, and considers both the effects of atmospheric optical impairments on the performance of the free space optical segment as well as the effect of RF channel impairments on the radio frequency segment. The radio frequency segment analysis considers the three most common RF channel fading statistics: Rayleigh, Ricean, and Nakagami-m. The novel application of information theory to the underlying physics of the

Segment-based dose optimization using a genetic algorithm

International Nuclear Information System (INIS)

Cotrutz, Cristian; Xing Lei

2003-01-01

Intensity modulated radiation therapy (IMRT) inverse planning is conventionally done in two steps. Firstly, the intensity maps of the treatment beams are optimized using a dose optimization algorithm. Each of them is then decomposed into a number of segments using a leaf-sequencing algorithm for delivery. An alternative approach is to pre-assign a fixed number of field apertures and optimize directly the shapes and weights of the apertures. While the latter approach has the advantage of eliminating the leaf-sequencing step, the optimization of aperture shapes is less straightforward than that of beamlet-based optimization because of the complex dependence of the dose on the field shapes, and their weights. In this work we report a genetic algorithm for segment-based optimization. Different from a gradient iterative approach or simulated annealing, the algorithm finds the optimum solution from a population of candidate plans. In this technique, each solution is encoded using three chromosomes: one for the position of the left-bank leaves of each segment, the second for the position of the right-bank and the third for the weights of the segments defined by the first two chromosomes. The convergence towards the optimum is realized by crossover and mutation operators that ensure proper exchange of information between the three chromosomes of all the solutions in the population. The algorithm is applied to a phantom and a prostate case and the results are compared with those obtained using beamlet-based optimization. The main conclusion drawn from this study is that the genetic optimization of segment shapes and weights can produce highly conformal dose distribution. In addition, our study also confirms previous findings that fewer segments are generally needed to generate plans that are comparable with the plans obtained using beamlet-based optimization. Thus the technique may have useful applications in facilitating IMRT treatment planning

Excluded segmental duct bile leakage: the case for bilio-enteric anastomosis.

Science.gov (United States)

Patrono, Damiano; Tandoi, Francesco; Romagnoli, Renato; Salizzoni, Mauro

2014-06-01

Excluded segmental duct bile leak is the rarest type of post-hepatectomy bile leak and presents unique diagnostic and management features. Classical management strategies invariably entail a significant loss of functioning hepatic parenchyma. The aim of this study is to report a new liver-sparing technique to handle excluded segmental duct bile leakage. Two cases of excluded segmental duct bile leak occurring after major hepatic resection were managed by a Roux-en-Y hepatico-jejunostomy on the excluded segmental duct, avoiding the sacrifice of the liver parenchyma origin of the fistula. In both cases, classical management strategies would have led to the functional loss of roughly 50 % of the liver remnant. Diagnostic and management implications are thoroughly discussed. Both cases had an uneventful postoperative course. The timing of repair was associated with a different outcome: the patient who underwent surgical repair in the acute phase developed no long-term complications, whereas the patient who underwent delayed repair developed a late stenosis requiring percutaneous dilatation. Roux-en-Y hepatico-jejunostomy on the excluded bile duct is a valuable technique in selected cases of excluded segmental duct bile leakage.

Spatially adapted augmentation of age-specific atlas-based segmentation using patch-based priors

Science.gov (United States)

Liu, Mengyuan; Seshamani, Sharmishtaa; Harrylock, Lisa; Kitsch, Averi; Miller, Steven; Chau, Van; Poskitt, Kenneth; Rousseau, Francois; Studholme, Colin

2014-03-01

One of the most common approaches to MRI brain tissue segmentation is to employ an atlas prior to initialize an Expectation- Maximization (EM) image labeling scheme using a statistical model of MRI intensities. This prior is commonly derived from a set of manually segmented training data from the population of interest. However, in cases where subject anatomy varies significantly from the prior anatomical average model (for example in the case where extreme developmental abnormalities or brain injuries occur), the prior tissue map does not provide adequate information about the observed MRI intensities to ensure the EM algorithm converges to an anatomically accurate labeling of the MRI. In this paper, we present a novel approach for automatic segmentation of such cases. This approach augments the atlas-based EM segmentation by exploring methods to build a hybrid tissue segmentation scheme that seeks to learn where an atlas prior fails (due to inadequate representation of anatomical variation in the statistical atlas) and utilize an alternative prior derived from a patch driven search of the atlas data. We describe a framework for incorporating this patch-based augmentation of EM (PBAEM) into a 4D age-specific atlas-based segmentation of developing brain anatomy. The proposed approach was evaluated on a set of MRI brain scans of premature neonates with ages ranging from 27.29 to 46.43 gestational weeks (GWs). Results indicated superior performance compared to the conventional atlas-based segmentation method, providing improved segmentation accuracy for gray matter, white matter, ventricles and sulcal CSF regions.

Incorporation of nano-clay saponite layers in the organo-clay hybrid films using anionic amphiphile stearic acid by Langmuir–Blodgett technique

Energy Technology Data Exchange (ETDEWEB)

Hussain, Syed Arshad, E-mail: sa_h153@hotmail.com [Department of Physics, Tripura University, Suryamaninagar-799022 (India); Chakraborty, S.; Bhattacharjee, D. [Department of Physics, Tripura University, Suryamaninagar-799022 (India); Schoonheydt, R.A. [Centres for Surface Chemistry and Catalysis, K.U. Leuven, Kasteelpark Arenberg 23, 3001 Leuven (Belgium)

2013-06-01

In general cationic amphiphiles are used to prepare organo-clay hybrid film in Langmuir–Blodgett (LB) technique. In this present communication we demonstrated a unique technique to prepare the organo–clay hybrid films using an anionic amphiphile. The T–O–T type clay saponite was incorporated onto a floating stearic acid monolayer via a divalent cation Mg{sup 2+}. Salt MgCl{sub 2} was mixed along with the clay dispersion in the LB trough and amphiphile solution was spread onto the subphase in order to make the organo-clay hybrid films. It was observed that salt (MgCl{sub 2}) concentration on the subphase affects the organization of nano-dimensional clay platelet (saponite) in organo-clay hybrid films at air–water interface as well as in LB films. Noticeable changes in area per molecule and shape of the isotherms were observed and measured at subphases with different salt concentrations. Infrared reflection absorption spectroscopy studies reveal that only an in-plane (996 cm{sup −1}) vibration of ν (Si-O) band occurred when the salt concentration was 10 mM. However, both in-plane (996 cm{sup −1}) and out-of-plane (1063 cm{sup −1}) vibrations of the ν (Si-O) band of saponite occurred when the subphase salt concentration was 100 mM. Also the out-of-plane vibration of ν (OH) of saponite was prominent at higher salt concentration. This is because at lower salt concentration clay sheets remain flat on the surface whereas; at higher MgCl{sub 2} concentration they aggregated and form stacks of saponite layers. Also they may be slightly tilted with a very small tilt angle at higher salt concentration making a favorable condition for both in-plane and out-of-plane vibrations of ν (Si-O) in the hybrid films. Observed decrease in starting area per molecule in the pressure area isotherm measured at higher salt concentration also supports the tilting of clay layers at air–clay dispersion interface. Attentuated total reflectance Fourier transform infrared

Real-time visual communication to aid disaster recovery in a multi-segment hybrid wireless networking system

Science.gov (United States)

Al Hadhrami, Tawfik; Wang, Qi; Grecos, Christos

2012-06-01

When natural disasters or other large-scale incidents occur, obtaining accurate and timely information on the developing situation is vital to effective disaster recovery operations. High-quality video streams and high-resolution images, if available in real time, would provide an invaluable source of current situation reports to the incident management team. Meanwhile, a disaster often causes significant damage to the communications infrastructure. Therefore, another essential requirement for disaster management is the ability to rapidly deploy a flexible incident area communication network. Such a network would facilitate the transmission of real-time video streams and still images from the disrupted area to remote command and control locations. In this paper, a comprehensive end-to-end video/image transmission system between an incident area and a remote control centre is proposed and implemented, and its performance is experimentally investigated. In this study a hybrid multi-segment communication network is designed that seamlessly integrates terrestrial wireless mesh networks (WMNs), distributed wireless visual sensor networks, an airborne platform with video camera balloons, and a Digital Video Broadcasting- Satellite (DVB-S) system. By carefully integrating all of these rapidly deployable, interworking and collaborative networking technologies, we can fully exploit the joint benefits provided by WMNs, WSNs, balloon camera networks and DVB-S for real-time video streaming and image delivery in emergency situations among the disaster hit area, the remote control centre and the rescue teams in the field. The whole proposed system is implemented in a proven simulator. Through extensive simulations, the real-time visual communication performance of this integrated system has been numerically evaluated, towards a more in-depth understanding in supporting high-quality visual communications in such a demanding context.

Segmented block copolymers with monodisperse aramide end-segments

NARCIS (Netherlands)

Araichimani, A.; Gaymans, R.J.

2008-01-01

Segmented block copolymers were synthesized using monodisperse diaramide (TT) as hard segments and PTMO with a molecular weight of 2 900 g · mol-1 as soft segments. The aramide: PTMO segment ratio was increased from 1:1 to 2:1 thereby changing the structure from a high molecular weight multi-block

Brain tumor segmentation in multi-spectral MRI using convolutional neural networks (CNN).

Science.gov (United States)

Iqbal, Sajid; Ghani, M Usman; Saba, Tanzila; Rehman, Amjad

2018-04-01

A tumor could be found in any area of the brain and could be of any size, shape, and contrast. There may exist multiple tumors of different types in a human brain at the same time. Accurate tumor area segmentation is considered primary step for treatment of brain tumors. Deep Learning is a set of promising techniques that could provide better results as compared to nondeep learning techniques for segmenting timorous part inside a brain. This article presents a deep convolutional neural network (CNN) to segment brain tumors in MRIs. The proposed network uses BRATS segmentation challenge dataset which is composed of images obtained through four different modalities. Accordingly, we present an extended version of existing network to solve segmentation problem. The network architecture consists of multiple neural network layers connected in sequential order with the feeding of Convolutional feature maps at the peer level. Experimental results on BRATS 2015 benchmark data thus show the usability of the proposed approach and its superiority over the other approaches in this area of research. © 2018 Wiley Periodicals, Inc.

Joint level-set and spatio-temporal motion detection for cell segmentation.

Science.gov (United States)

Boukari, Fatima; Makrogiannis, Sokratis

2016-08-10

Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan

Crop to wild introgression in lettuce: following the fate of crop genome segments in backcross populations.

Science.gov (United States)

Uwimana, Brigitte; Smulders, Marinus J M; Hooftman, Danny A P; Hartman, Yorike; van Tienderen, Peter H; Jansen, Johannes; McHale, Leah K; Michelmore, Richard W; Visser, Richard G F; van de Wiel, Clemens C M

2012-03-26

After crop-wild hybridization, some of the crop genomic segments may become established in wild populations through selfing of the hybrids or through backcrosses to the wild parent. This constitutes a possible route through which crop (trans)genes could become established in natural populations. The likelihood of introgression of transgenes will not only be determined by fitness effects from the transgene itself but also by the crop genes linked to it. Although lettuce is generally regarded as self-pollinating, outbreeding does occur at a low frequency. Backcrossing to wild lettuce is a likely pathway to introgression along with selfing, due to the high frequency of wild individuals relative to the rarely occurring crop-wild hybrids. To test the effect of backcrossing on the vigour of inter-specific hybrids, Lactuca serriola, the closest wild relative of cultivated lettuce, was crossed with L. sativa and the F(1) hybrid was backcrossed to L. serriola to generate BC(1) and BC(2) populations. Experiments were conducted on progeny from selfed plants of the backcrossing families (BC(1)S(1) and BC(2)S(1)). Plant vigour of these two backcrossing populations was determined in the greenhouse under non-stress and abiotic stress conditions (salinity, drought, and nutrient deficiency). Despite the decreasing contribution of crop genomic blocks in the backcross populations, the BC(1)S(1) and BC(2)S(1) hybrids were characterized by a substantial genetic variation under both non-stress and stress conditions. Hybrids were identified that performed equally or better than the wild genotypes, indicating that two backcrossing events did not eliminate the effect of the crop genomic segments that contributed to the vigour of the BC(1) and BC(2) hybrids. QTLs for plant vigour under non-stress and the various stress conditions were detected in the two populations with positive as well as negative effects from the crop. As it was shown that the crop contributed QTLs with either a positive

Crop to wild introgression in lettuce: following the fate of crop genome segments in backcross populations

Directory of Open Access Journals (Sweden)

Uwimana Brigitte

2012-03-01

Full Text Available Abstract Background After crop-wild hybridization, some of the crop genomic segments may become established in wild populations through selfing of the hybrids or through backcrosses to the wild parent. This constitutes a possible route through which crop (transgenes could become established in natural populations. The likelihood of introgression of transgenes will not only be determined by fitness effects from the transgene itself but also by the crop genes linked to it. Although lettuce is generally regarded as self-pollinating, outbreeding does occur at a low frequency. Backcrossing to wild lettuce is a likely pathway to introgression along with selfing, due to the high frequency of wild individuals relative to the rarely occurring crop-wild hybrids. To test the effect of backcrossing on the vigour of inter-specific hybrids, Lactuca serriola, the closest wild relative of cultivated lettuce, was crossed with L. sativa and the F1 hybrid was backcrossed to L. serriola to generate BC1 and BC2 populations. Experiments were conducted on progeny from selfed plants of the backcrossing families (BC1S1 and BC2S1. Plant vigour of these two backcrossing populations was determined in the greenhouse under non-stress and abiotic stress conditions (salinity, drought, and nutrient deficiency. Results Despite the decreasing contribution of crop genomic blocks in the backcross populations, the BC1S1 and BC2S1 hybrids were characterized by a substantial genetic variation under both non-stress and stress conditions. Hybrids were identified that performed equally or better than the wild genotypes, indicating that two backcrossing events did not eliminate the effect of the crop genomic segments that contributed to the vigour of the BC1 and BC2 hybrids. QTLs for plant vigour under non-stress and the various stress conditions were detected in the two populations with positive as well as negative effects from the crop. Conclusion As it was shown that the crop

Crop to wild introgression in lettuce: following the fate of crop genome segments in backcross populations

Science.gov (United States)

2012-01-01

Background After crop-wild hybridization, some of the crop genomic segments may become established in wild populations through selfing of the hybrids or through backcrosses to the wild parent. This constitutes a possible route through which crop (trans)genes could become established in natural populations. The likelihood of introgression of transgenes will not only be determined by fitness effects from the transgene itself but also by the crop genes linked to it. Although lettuce is generally regarded as self-pollinating, outbreeding does occur at a low frequency. Backcrossing to wild lettuce is a likely pathway to introgression along with selfing, due to the high frequency of wild individuals relative to the rarely occurring crop-wild hybrids. To test the effect of backcrossing on the vigour of inter-specific hybrids, Lactuca serriola, the closest wild relative of cultivated lettuce, was crossed with L. sativa and the F1 hybrid was backcrossed to L. serriola to generate BC1 and BC2 populations. Experiments were conducted on progeny from selfed plants of the backcrossing families (BC1S1 and BC2S1). Plant vigour of these two backcrossing populations was determined in the greenhouse under non-stress and abiotic stress conditions (salinity, drought, and nutrient deficiency). Results Despite the decreasing contribution of crop genomic blocks in the backcross populations, the BC1S1 and BC2S1 hybrids were characterized by a substantial genetic variation under both non-stress and stress conditions. Hybrids were identified that performed equally or better than the wild genotypes, indicating that two backcrossing events did not eliminate the effect of the crop genomic segments that contributed to the vigour of the BC1 and BC2 hybrids. QTLs for plant vigour under non-stress and the various stress conditions were detected in the two populations with positive as well as negative effects from the crop. Conclusion As it was shown that the crop contributed QTLs with either a

Segmentation of consumer's markets and evaluation of market's segments

OpenAIRE

ŠVECOVÁ, Iveta

2013-01-01

The goal of this bachelor thesis was to explain a possibly segmentation of consumer´s markets for a chosen company, and to present a suitable goods offer, so it would be suitable to the needs of selected segments. The work is divided into theoretical and practical part. First part describes marketing, segmentation, segmentation of consumer's markets, consumer's market, market's segments a other terms. Second part describes an evaluation of questionnaire survey, discovering of market's segment...

Segmentation of multiple sclerosis lesions in MR images: a review

International Nuclear Information System (INIS)

Mortazavi, Daryoush; Kouzani, Abbas Z.; Soltanian-Zadeh, Hamid

2012-01-01

Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease. For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past. This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques. Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels. (orig.)

Segmentation of multiple sclerosis lesions in MR images: a review

Energy Technology Data Exchange (ETDEWEB)

Mortazavi, Daryoush; Kouzani, Abbas Z. [Deakin University, School of Engineering, Geelong, Victoria (Australia); Soltanian-Zadeh, Hamid [Henry Ford Health System, Image Analysis Laboratory, Radiology Department, Detroit, MI (United States); University of Tehran, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, Tehran (Iran, Islamic Republic of); School of Cognitive Sciences, Institute for Studies in Theoretical Physics and Mathematics (IPM), Tehran (Iran, Islamic Republic of)

2012-04-15

Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease. For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past. This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques. Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels. (orig.)