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Lecture Notes in computer Science

作者： O'Donnell, Thomas Kaftan, Jens N. Schuh, Andreas Tietjen, Christian Soza, Grzegorz Aach, Til Siemens Corporate Research 755 College Rd East Princeton NJ 08540 United States Institute of Imaging and Computer Vision RWTH Aachen University 52056 Aachen Germany Section of Biomedical Image Analysis Department of Radiology University of Pennsylvania Philadelphia PA 19104 United States Siemens Healthcare Sector Computed Tomography 91301 Forchheim Germany

ISBN: (纸本)9783642220913

Entangled tree-like vascular systems are commonly found in the body (e.g., in the peripheries and lungs). Separation of these systems in medical images may be formulated as a graph partitioning problem given an imperfect segmentation and specification of the tree roots. In this work, we show that the ubiquitous Ising-model approaches (e.g., Graph Cuts, Random Walker) are not appropriate for tackling this problem and propose a novel method based on recursive minimal paths for doing so. To motivate our method, we focus on the intertwined portal and hepatic venous systems in the liver. Separation of these systems is critical for liver intervention planning, in particular when resection is involved. We apply our method to 34 clinical datasets, each containing well over a hundred vessel branches, demonstrating its effectiveness. © 2011 Springer-Verlag.

关键词： Separation

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3D vertebrae segmentation using graph cuts with shape prior constraints

3D vertebrae segmentation using graph cuts with shape prior ...

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IEEE International Conference on image Processing

作者： Melih S. Aslan Asem Ali Dongqing Chen Ben Arnold Aly A. Farag Ping Xiang University of Louisville Computer Vision and Image Processing Laboratory Louisville KY USA Image Analysis Inc Columbia KY USA

Osteoporosis is a bone disease characterized by a reduction in bone mass, resulting in an increased risk of fractures. To diagnose the osteoporosis accurately, bone mineral density (BMD) measurements and fracture analysis (FA) of the Vertebral bodies (VBs) are required. In this paper, we propose a robust and 3D shape based method to segment VBs in clinical computed tomography (CT) images in order to make BMD measurements and FA accurately. In this experiment, image appearance and shape information of VBs are used. In the training step, 3D shape information is obtained from a set of data sets. Then, we estimate the shape variations using a distance probabilistic model which approximates the marginal densities of the VB and background in the variability region. In the segmentation step, the Matched filter is used to detect the VB region automatically. We align the detected volume with 3D shape prior in order to be used in distance probabilistic model. Then, the graph cuts method which integrates the linear combination of Gaussians (LCG), Markov Gibbs Random Field (MGRF), and distance probabilistic model obtained from 3D shape prior is used.

关键词： Shape image segmentation Three dimensional displays Computed tomography Bones Solid modeling image color analysis

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A novel, fast, and complete 3D segmentation of vertebral bones

A novel, fast, and complete 3D segmentation of vertebral bon...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Melih S. Aslan Asem Ali Ham Rara Ben Arnold Rachid Fahmi Aly A. Farag Ping Xiang Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Image Analysis Inc. Columbia KY USA

Bone mineral density (BMD) measurements and fracture analysis of the spine bones are restricted to the Vertebral bodies (VBs), especially the trabecular bones (TBs). In this paper, we propose a novel, fast, and robust 3D framework to segment VBs and trabecular bones in clinical computed tomography (CT) images without any user intervention. The Matched filter is employed to detect the VB region automatically. To segment the whole VB, the graph cuts method which integrates a linear combination of Gaussians (LCG) and Markov Gibbs Random Field (MGRF) is used. Then, the cortical and trabecular bones are segmented using local volume growing methods. Validity was analyzed using ground truths of data sets (expert segmentation) and the European Spine Phantom (ESP) as a known reference. Experiments on the data sets show that the proposed segmentation approach is more accurate than other known alternatives.

关键词： Bones image segmentation Computed tomography Three dimensional displays Accuracy Level set Spine

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Elastic modulus imaging using optical flow and image registration

Elastic modulus imaging using optical flow and image registr...

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IEEE International Conference on image Processing

作者： Robert Martí Alison Noble Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Spain Biomedical Image Analysis Laboratory Institute of Biomedical Engineering University of Oxford UK

Elastography, the imaging technique for estimating the elastic tissue properties, or more specifically elastic modulus imaging, are becoming important diagnosis tools in computer aided diagnosis system, specially focusing on ultrasound and MRI images. This technique still presents unsolved challenges in the analysis of deformations in sequences of images. The aim of this paper is twofold: to evaluate the applicability of the deformation field obtained by state of the art optical flow and image registration algorithms for elastic modulus imaging and to quantitatively evaluate two different methods for estimation of the elastic modulus distribution. Results show that optical-flow methods provide a slightly better reconstruction and that the reconstruction has been shown to be more accurate using the method proposed by Sumi et al.

关键词： image reconstruction Optical imaging Strain Young's modulus image registration Lesions

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Tracking the invisible: Learning where the object might be

Tracking the invisible: Learning where the object might be

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Helmut Grabner Jiri Matas Luc Van Gool Philippe Cattin Computer Vision Laboratory ETH Zurich Switzerland Center for Machine Perception Czech Technical University Prague Czech Republic ESAT-PSI / IBBT K.U. Leuven Belgium Medical Image Analysis Center University of Basel Switzerland

Objects are usually embedded into context. Visual context has been successfully used in object detection tasks, however, it is often ignored in object tracking. We propose a method to learn supporters which are, be it only temporally, useful for determining the position of the object of interest. Our approach exploits the General Hough Transform strategy. It couples the supporters with the target and naturally distinguishes between strongly and weakly coupled motions. By this, the position of an object can be estimated even when it is not seen directly (e.g., fully occluded or outside of the image region) or when it changes its appearance quickly and significantly. Experiments show substantial improvements in model-free tracking as well as in the tracking of “virtual” points, e.g., in medical applications.

关键词： Target tracking Object detection Medical services Biomedical equipment Face detection Context modeling Voting computer vision Laboratories Biomedical imaging

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Contrast enhancement with dual energy CT for the assessment of atherosclerosis

Contrast enhancement with dual energy CT for the assessment ...

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Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2009 - Workshop on image Processing for Medicine: Algorithms - Systems - Applications, BVM 2009

作者： Saur, Stefan C. Alkadhi, Hatem Regazzoni, Luca Eugster, Simon Székely, Gábor Cattin, Philippe Computer Vision Laboratory ETH Zurich Switzerland Institute of Diagnostic Radiology University Hospital Zurich Switzerland Medical Image Analysis Center University of Basel Switzerland

ISBN: (纸本)9783540938590

A drawback of the commonly used single source computed tomography systems (CT) is that different materials might show very similar attenuation at any selected radiation energy. However, the assessment of atherosclerosis requires good differentiation between vessel lumen, calcium, adipose, and surrounding tissue. Dual energy CT (DECT) simultaneously measures attenuations at two energies and therefore can improve the differentiation to some extent. A tissue cancelation and enhancement algorithm for dual energy data was already proposed in 1981 and evaluated on experimental settings with a stationary X-ray source. For this study, we adapted this algorithm for DECT and propose its usage as a pre-processing step for the assessment of atherosclerosis. On clinical DECT patient data and with fixed parameters we could show a simultaneous contrast enhancement between 8% and 67% among all targeted tissues.

关键词： Tissue

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Segmentation of trabecular bones from Vertebral bodies in volumetric CT spine images

Segmentation of trabecular bones from Vertebral bodies in vo...

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IEEE International Conference on image Processing

作者： Melih S. Aslan Asem Ali Ben Arnold Rachid Fahmi Aly A. Farag Ping Xiang Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Image Analysis Inc. Columbia KY USA

We present a 3D segmentation technique of trabecular (cancellous) bones in CT images of Vertebral bodies (VBs). In order to be used for Bone Mineral Density (BMD) measurements, the cortical and trabecular bones are subsequently segmented using graph cuts method and local volume growing methods separately. In the final step, we measure our segmentation accuracy for each method. Validity was analyzed using ground truths of data sets and the European Spine Phantom (ESP). Preliminary results are very encouraging and a reproducibility of the results was achieved for 16 data sets. The average segmentation error is below 2.0% for both methods.

关键词： image segmentation Cancellous bone Computed tomography Spine Minerals Density measurement Imaging phantoms Electrostatic precipitators Labeling Timing

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Markerless Motion Capture of Man-Machine Interaction

Markerless Motion Capture of Man-Machine Interaction

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26th IEEE Conference on computer vision and Pattern Recognition (CVPR 2008), vol.5

作者： Bodo Rosenhahn Christian Schmaltz Thomas Brox Joachim Weickert Daniel Cremers Hans-Peter Seidel MPI Computer Science Saarbrucken Germany Mathematical Image Analysis University of Saarland Saarbrucken Germany Intelligent Systems University of Dresden Dresden Germany Computer Vision University of Bonn Bonn Germany

This work deals with modeling and markerless tracking of athletes interacting with sports gear. In contrast to classical markerless tracking, the interaction with sports gear comes along with joint movement restrictions due to additional constraints: while humans can generally use all their joints, interaction with the equipment imposes a coupling between certain joints. A cyclist who performs a cycling pattern is one example: The feet are supposed to stay on the pedals, which are again restricted to move along a circular trajectory in 3D-space. In this paper, we present a markerless motion capture system that takes the lower-dimensional pose manifold into account by modeling the motion restrictions via soft constraints during pose optimization. Experiments with two different models, a cyclist and a snowboarder, demonstrate the applicability of the method. Moreover, we present motion capture results for challenging outdoor scenes including shadows and strong illumination changes.

关键词： Man machine systems Kinematics Mathematical model Tracking Humans Layout Joints Biological system modeling computer vision Gears

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Impact of anthropogenic disturbance on a mangrove forest assessed by a id cellular automaton model using lotka-volterra-type competition

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International Journal of Design and Nature and Ecodynamics 2008年第4期3卷 296-320页

作者： Obade, P.T. Koedam, N. Soetaert, K. Neukermans, G. Bogaert, J. Nyssen, E. Van Nedervelde, F. Berger, U. Dahdouh-Guebas, F. Belgium Kenya Marine and Fisheries Research Institute Kenya Netherlands Belgium Department of Electronics and Informatics Image Processing and Machine Vision Group VUB Belgium Département de Biologie des Organismes Faculté des Sciences Complexité et Dynamique des Systèmes Tropicaux Belgium Department of Forest Biometry and Systems Analysis Institute of Forest Growth and Forest Computer Sciences Technische Universität Dresden Germany

Mangrove forests are ecologically and economically important and frequently dominating protected coastal areas in the tropics and subtropics at suitable intertidal zones and are often subjected to disturbances that disrupt the structure of an ecosystem, that change resource availability and that create patterns in vegetation by producing a mosaic of serai stages that ecologists have long recognised as important to landscape-level patch mosaics. Several good reasons justify the need for pursuing a predictive understanding of the ecology of mangrove species competition including the role of disturbance events and the aftermath. A predictive understanding can challenge our assumptions concerning the factors that control plant distribution and abundance and provide techniques for predicting rates of species change ranges in response to disturbances. The aim of this study was to evaluate and predict the impact of canopy disturbances on Gazi Bay mangrove forests and the subsequent vegetation patterns both spatially and temporally. The use of a simple 1D cellular automaton provided a detailed and nearly comprehensive parameterisation of the model by forest structure parameters belonging to the standard measurements of mangrove field surveys. In the study presented, the field data were obtained for disturbance impacts at various spatial scales considering not only the spatial extent of the disturbance but also its particular location. For this, multiple sampling transects were selected a priori, based on the vegetation patterns observed on Quickbird satellite image (2002) of Gazi, to reflect major ecological zones and vegetation transitions in space. Earlier field studies already revealed different population trajectories in some cases for the same pairwise species interactions, which are consistent with the hypothesis that different scales of disturbances may affect succession trends. Simulation experiments supported these findings by demonstrating that varying disturbance

关键词： Forecasting

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Two-way Clustering using Fuzzy ASI for Knowledge Discovery in Microarrays

Two-way Clustering using Fuzzy ASI for Knowledge Discovery i...

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IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology (CIBCB)

作者： J. Shaik M. Yeasin Computer Vision Pattern and Image Analysis Lab Electrical and Computer Engineering University of Memphis Memphis TN USA

This paper presents two-way clustering of microarray data using fuzzy adaptive subspace iteration (ASI) based algorithm for knowledge discovery in microarrays. It is widely believed that each gene is involved in more than one cellular function or biological process. The proposed fuzzy ASI assigns a relevance value to each gene associated with each cluster. These functional categories are ranked based on their potential in providing maximal separation between the two tissues classes; which is an indication of differentially expressed genes (DEGs). Empirical analyses on simulated, 100 artificial microarray datasets are used to quantify the results obtained using the fuzzy-ASI algorithm. Further analyses on different microarray cancer datasets revealed several important genes that are relevant with various cancers.

关键词： Clustering algorithms Biological processes computer vision Algorithm design and analysis Cancer Computational intelligence Bioinformatics Computational biology image analysis Biology computing

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