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Medical Imaging 2007 Conference

作者： Cho, Seungryong Pan, Xiaochuan Univ Chicago Dept Radiol Chicago IL 60637 USA Univ Chicago Dept Radiat & Cellular Oncol Chicago IL 60637 USA

ISBN: (纸本)9780819466280

We compared data requirements of filtered-backprojection (FBP) and backprojection-filtration (BPF) algorithms based on PI-lines in helical cone-beam CT. Since the filtration process in FBP algorithm needs all the projection data of PI-lines for each view, the required detector size should be bigger than the size that can cover Tam-Danielsson (T-D) window to avoid data truncation. BPF algorithm, however, requires the projection data only within the T-D window, which means smaller detector size can be used to reconstruct the same image than that in FBP. In other words, a longer helical pitch can be obtained by using BPF algorithm without any truncation artifacts when a fixed detector size is given. The purpose of the work is to demonstrate numerically that extended volume coverage in helical cone-beam CT by using PI-line-based BPF algorithm can be achieved.

关键词： Reconstruction algorithms Detection and tracking algorithms Sensors Algorithm development image segmentation image processing algorithms and systems image restoration algorithms Computed tomography Medical imaging

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Automatic multiple threshold, scheme for segmentation of tomograms

Automatic multiple threshold, scheme for segmentation of tom...

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Medical Imaging 2007 Conference

作者： Batenburg, K. J. Sijbers, J. Univ Antwerp Dept Phys Vis Lab Univ Pl 1 B-2610 Antwerp Belgium

ISBN: (纸本)9780819466303

Tomographic reconstructions, which are generally gray-scale images, are often segmented as to extract quantitative information, such as the shape or volume of image objects. At present, segmentation is usually performed by thresholding. However, the process of threshold selection is somewhat arbitrary and requires human interaction. In this paper, we present an algorithmic approach for automatically selecting the segmentation thresholds by using the available tomographic projection data. Assuming that each material (i.e., tissue type) in the sample has a characteristic, approximately constant gray value, thresholds are computed for which the segmented image corresponds optimally with the projection data.

关键词： image segmentation Reconstruction algorithms Tomography Evolutionary algorithms Diamond Optimization (mathematics) Bone image processing algorithms and systems 3D image reconstruction Tissues

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A general theory of image segmentation: level set segmentation in the fuzzy connectedness framework

A general theory of image segmentation: level set segmentati...

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Medical Imaging 2007 Conference

作者： Ciesielski, Krzysztof Chris Udupa, Jayaram K. West Virginia Univ Dept Math Morgantown WV 26506 USA Univ Penn MIPG Dept Radiol Philadelphia PA 19104 USA

ISBN: (纸本)9780819466303

In the current vast image segmentation literature, there is a serious lack of methods that would allow theoretical comparison of the algorithms introduced by using different mathematical methodologies. The main goal of this article is to introduce a general theoretical framework for image segmentation that would allow such comparison. The framework is based on the formal definitions designed to answer the following fundamental questions: What is the relation between an idealized image and its digital representation? What properties a segmentation algorithm must satisfy to be acknowledged as acceptable? What does it mean that a digital image segmentation algorithm truly approximates an idealized segmentation model? We use the formulated framework to analyze the front propagation (FP) level set algorithm of Malladi, Sethian, and Vemuri and compare it with the fuzzy connectedness family of algorithms. In particular, we prove that the FP algorithm is weakly model-equivalent with the absolute fuzzy connectedness algorithm of Udupa and Samarasekera used with gradient based affinity. Experimental evidence of this equivalence is also provided. The presented theoretical framework can be used to analyze any arbitrary segmentation algorithm. This line of investigation is a subject of our forthcoming work.

关键词： image segmentation image processing algorithms and systems Digital imaging algorithms image processing Fuzzy logic Evolutionary algorithms Mathematical modeling image resolution image sensors

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image reconstruction from rebinned helical cone-beam projection data

Image reconstruction from rebinned helical cone-beam project...

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Medical Imaging 2007 Conference

作者： Xia, Dan Yu, Lifeng Bian, Junguo Pan, Xiaochuan Univ Chicago Dept Radiol 5841 S Maryland Ave Chicago IL 60637 USA

ISBN: (纸本)9780819466280

In this work;we introduced an algorithm for image reconstruction in helical cone-beam CT based upon the backprojection-filtration (BPF) algorithm. This algorithm is a backprojection-filtration-type algorithm that reconstructs images from rebinned data. It retains the properties of the original BPF algorithm in that it;requires minimum data and can reconstruct. ROI images from truncated data. More importantly, due to the elimination of the spatially-variant weighting factor in the backprojection, it, may improve the noise properties in reconstructed images. We have performed computer-simulation studies to investigate the ROI-image reconstruction and noise properties of this algorithm, and the;quantitative results verify and demonstrate the proposed algorithm.

关键词： Reconstruction algorithms image segmentation Algorithm development image processing algorithms and systems Data acquisition image restoration 3D image reconstruction Sensors Computed tomography image filtering

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image representation and compression using directionlets

Image representation and compression using directionlets

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Conference on Wavelets XII

作者： Velisavljevic, Vladan Beferull-Lozano, Baltasar Vetterli, Martin Dragotti, Pier Luigi Deutsch Telekom Labs Berlin Germany Univ Valencia Valencia Spain Ecole Polytech Fed Lausanne Lausanne Switzerland Imperial Coll London England

ISBN: (纸本)9780819468499

The standard separable two-dimensional (2-D) wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to capture efficiently one-dimensional (1-D) discontinuities, like edges or contours.' These features, being elongated and characterized by geometrical regularity along different directions, intersect and generate many large magnitude wavelet coefficients. Since contours are very important elements in visual perception of images, to provide a good visual quality of compressed images, it is fundamental to preserve good reconstruction of these directional features. We propose a construction of critically sampled perfect reconstruction transforms with directional vanishing moments (DVMs) imposed in the corresponding basis functions along different directions, called directionlets. We also demonstrate the outperforming non-linear approximation (NLA) results achieved by our transforms and we show how to design and implement a novel efficient space-frequency quantization (SFQ) compression algorithm using directionlets. Our new compression method beats the standard SFQ both in terms of mean-square-error (MSE) and visual quality, especially in the low-rate compression regime. We also show that our compression method, does not increase the order of computational complexity as compared to the standard SFQ algorithm.

关键词： Transform theory image segmentation image compression Visualization Wavelets image quality Visual compression Quantization image filtering image processing algorithms and systems

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Cost-based closed-contour representations

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JOURNAL OF ELECTRONIC IMAGING 2007年第2期16卷 023009.1-023009.9页

作者： Sappa, Angel D. Vintimilla, Boris X. Comp Vis Ctr Barcelona 08193 Spain Escuela Super Politecn Litoral Dept Elect Engn & Comp Sci Vis & Robot Ctr Guayaquil 09015863 Ecuador

This paper presents an efficient technique for linking edge points in order to generate a closed-contour representation. It is based on the consecutive use of global and local schemes. In both cases it is assumed that the original intensity image, as well as its corresponding edge map, are given as inputs to the algorithm. The global scheme computes an initial representation by connecting edge points minimizing a global measure based on spatial information (3D space). It relies on the use of graph theory and exploits the edge points' distribution through the given edge map, as well as their corresponding intensity values. At the same time spurious edge points are removed by a morphological filter The local scheme finally generates closed contours, linking open boundaries, by using a local cost function that takes into account both spatial and topological information. Experimental results with different images, together with comparisons with a previous technique, are presented. (C) 2007 SPIE and IS&T.

关键词： image segmentation image processing image filtering image processing algorithms and systems Sensors 3D image processing Detection and tracking algorithms Algorithm development Edge detection Visualization

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New benchmark for image segmentation evaluation

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JOURNAL OF ELECTRONIC IMAGING 2007年第3期16卷 033011.1-033011.16页

作者： Ge, Feng Wang, Song Liu, Tiecheng Virginia Tech Dept Elect & Comp Engn Blacksburg VA 24061 USA Univ S Carolina Dept Comp Sci & Engn Columbia SC 29208 USA

image segmentation and its performance evaluation are very difficult but important problems in computer vision. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity: For general-purpose segmentation, the ground truth and segmentation accuracy may not be well defined, while embedding the evaluation in a specific application, the evaluation results may not be extensible to other applications. We present a new benchmark to evaluate five different image segmentation methods according to their capability to separate a perceptually salient structure from the background with a relatively small number of segments. This way, we not only find a large variety of images that satisfy the requirement of good generality, but also construct ground-truth segmentations to achieve good objectivity. We also present a special strategy to address two important issues underlying this benchmark: (1) most image-segmentation methods are not developed to directly extract a single salient structure;(2) many real images have multiple salient structures. We apply this benchmark to evaluate and compare the performance of several state-of-the-art image segmentation methods, including the normalized-cut method, the watershed method, the efficient graph-based method, the mean-shift method, and the ratio-cut method. (c) 2007 SPIE and IS&T.

关键词： image segmentation Databases image processing algorithms and systems Gaussian filters Algorithm development Computer vision technology Machine vision MATLAB Medical imaging Video surveillance

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Unsupervised texture segmentation using a nonlinear energy optimization method

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JOURNAL OF ELECTRONIC IMAGING 2006年第3期15卷 033006.1-033006.8页

作者： Mahmoodi, Sasan Sharif, Bayan S. Univ Newcastle Sch Biol & Psychol Psychol Div Newcastle Upon Tyne NE2 4HH Tyne & Wear England Univ Newcastle Sch Elect Elect & Comp Engn Newcastle Upon Tyne NE1 7RU Tyne & Wear England

A nonlinear functional is considered for segmentation of images containing structural textures. A structural texture pattern in an image is characterized by a certain amplitude spectrum, and segmentation of different patterns is obtained by detecting different regions with different amplitude spectra. A gradient-descent-based algorithm is proposed by deriving equations minimizing the functional. This algorithm, implementing the solutions minimizing the functional, is based on the level set method. An effective method employed in this algorithm is shown to be robust in a noisy environment. Experimental results demonstrate that the proposed method outperforms segmentation obtained by using the simulated annealing algorithm based on Gaussian Markov random fields. (c) 2006 SPIE and IS&T.

关键词： image segmentation image processing algorithms and systems Multiplexers Expectation maximization algorithms Detection and tracking algorithms image filtering Reconstruction algorithms algorithms Smoothing Spatial frequencies

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Markovian segmentation and parameter estimation on graphics hardware

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JOURNAL OF ELECTRONIC IMAGING 2006年第3期15卷 033005.1-033005.1页

作者： Jodoin, Pierre-Marc Mignotte, Max Univ Montreal Dept Informat & Rech Operat Montreal PQ H3C 3J7 Canada

In this paper, we show how Markovian strategies used to solve well-known segmentation problems such as motion estimation, motion detection, motion segmentation, stereovision, and color segmentation can be significantly accelerated when implemented on programmable graphics hardware. More precisely, we expose how the parallel abilities of a standard graphics processing unit usually devoted to image synthesis can be used to infer the labels of a segmentation map. The problems we address are stated in the sense of the maximum a posteriori with an energy-based or probabilistic formulation, depending on the application. In every case, the label field is inferred with an optimization algorithm such as iterated conditional mode (ICM) or simulated annealing. In the case of probabilistic segmentation, mixture parameters are estimated with the K-means and the iterative conditional estimation (ICE) procedure. For both the optimization and the parameter estimation algorithms, the graphics processor unit's (GPU's) fragment processor is used to update in parallel every labels of the segmentation map, while rendering passes and graphics textures are used to simulate optimization iterations. The hardware results obtained with a mid-end graphics card, show that these Markovian applications can be accelerated by a factor of 4 to 200 without requiring any advanced skills in hardware programming. (c) 2006 SPIE and IS&T.

关键词： image segmentation Visualization Motion estimation Motion detection Optimization (mathematics) C++ Motion models Computer programming Stochastic processes image processing algorithms and systems

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Non parametric partitioning of SAR images

Non parametric partitioning of SAR images

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Conference on image and Signal processing for Remote Sensing XII

作者： Delyon, G. Galland, F. Refregier, Ph. EGIM CNRS UMR 6133 Fresnel Inst F-13397 Marseille 20 France

ISBN: (纸本)0819464600

We describe and analyse a generalization of a parametric segmentation technique adapted to Gamma distributed SAR images to a simple non parametric noise model. The partition is obtained by minimizing the stochastic complexity of a quantized version on Q levels of the SAR image and lead to a criterion without parameters to be tuned by the user. We analyse the reliability of the proposed approach on synthetic images. The quality of the obtained partition will be studied for different possible strategies. In particular, one will discuss the reliability of the proposed optimization procedure. Finally, we will precisely study the performance of the proposed approach in comparison with the statistical parametric technique adapted to Gamma noise. These studies will be led by analyzing the number of misclassified pixels, the standard Hausdorff distance and the number of estimated regions.

关键词： image segmentation Synthetic aperture radar Statistical analysis Stochastic processes image processing Particle filters Reliability Quantization image processing algorithms and systems Optimization (mathematics)

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