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computing the Local Continuity Order of Optical Flow Using Fractional Variational Method

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7th international conference on Energy Minimization Methods in Computer Vision and pattern recognition

作者： Kashu, K. Kameda, Y. Imiya, A. Sakai, T. Mochizuki, Y. Chiba Univ Sch Adv Integrat Sci Chiba Japan Chiba Univ Inst Media & Informat Technol Inage Ku Chiba 263 Japan

ISBN: (纸本)9783642036408

We introduce variational optical flow computation involving priors with fractional order differentiations. Fractional order differentiations are typical tools in signal processing and image analysis. the zero-crossing of a fractional order Laplacian yields better performance for edge detection than the zero-crossing of the usual Laplacian. the order of the differentiation of the prior controls the continuity class of the solution. therefore, using the square norm of the fractional order differentiation of optical flow field as the prior;we develop a method to estimate the local continuity order of the optical flow held at each point. the method detects the optimal continuity order of optical flow and corresponding optical flow vector at each point. Numerical results show that the Horn-Schunck type prior involving the n + epsilon order differentiation for 0 < epsilon < 1 and an integer n is suitable for accurate optical flow computation.

关键词： Optical flows

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Weakly Supervised Group-Wise Model Learning Based on Discrete Optimization

Weakly Supervised Group-Wise Model Learning Based on Discret...

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12th international conference on Medical Image computing and Computer-Assisted Intervention (MICCAI2009)

作者： Donner, Rene Wildenauer, Horst Bischof, Horst Langs, Georg Med Univ Vienna Dept Radiol Computat Image Anal & Radiol Lab Vienna Austria Graz Univ Technol Inst Compu Graph & Vis A-8010 Graz Austria Vienna Univ Technol Pattern Recognit & Image Proc Grp A-1040 Vienna Austria

ISBN: (纸本)9783642042706

In this paper we propose a method for the weakly supervised learning of sparse appearance models from medical image data based oil Markov random fields (MRF). the models are learnt, from a sing-le annotated example and additional training samples without annotations. the approach formulates the model learning as solving a set of MRFs. Both the model training and the resulting model are able to cope with complex and repetitive structures. the weakly supervised model learning yields sparse MRF appearance models that perform equally well as those trained with manual annotations, thereby eliminating the need for tedious manual training supervision. Evaluation results are reported for hand radiographs and cardiac MRI slices.

关键词： Markov processes

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A Generic Probabilistic Active Shape Model for Organ Segmentation

A Generic Probabilistic Active Shape Model for Organ Segment...

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12th international conference on Medical Image computing and Computer-Assisted Intervention (MICCAI2009)

作者： Wimmer, Andreas Soza, Grzegorz Hornegger, Joachim Univ Erlangen Nurnberg Dept Comp Sci Chair Pattern Recognit D-8520 Erlangen Germany Siemens Healthcare Sect Comp Tomography Forchheim Germany

ISBN: (纸本)9783642042706

Probabilistic models are extensively used in medical image segmentation. Most of them employ parametric representations of densities and make idealizing assumptions, e.g. normal distribution of data. Often, such assumptions are inadequate and limit a broader application. We propose here a novel probabilistic active shape model for organ segmentation;which is entirely built upon non-parametric density estimates. In particular, a nearest neighbor boundary appearance model is complemented by a cascade of boosted classifiers for region information and combined with a shape model based on Parzen density estimation. Image and shape terms are integrated into a single level set equation. Our approach has been evaluated for 3-D liver segmentation using a public data originating from a competition (http://***). With an average surface distance of 1.0 mm and an average volume overlap error of 6.5 %, it, outperforms other automatic methods and provides accuracy close to interactive ones. Since no adaptions specific to liver segmentation have been made, our probabilistic active shape model can be applied to other segmentation tasks easily.

关键词： Normal distribution

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An Efficient Prediction Model for Diabetic Database Using Soft computing Techniques 1

引用

12th international conference on Rough Sets, Fuzzy Sets, Data Mining and Granular computing

作者： Bhat, Veena H. Rao, Prasanth G. Shenoy, P. Deepa Venugopal, K. R. Patnaik, L. M. Bangalore Univ Univ Visvesvaraya Coll Engn Bangalore 560056 Karnataka India Deemed Univ Def Inst Adv Technol Pune Maharashtra India

ISBN: (数字)9783642106460

ISBN: (纸本)9783642106453

Organizations aim at harnessing predictive insights, using the vast real-time data stores that they have accumulated through the years, using data mining techniques. Health sector, has an extremely large source of digital data - patient-health related data-store, which can be effectively used for predictive analytics. this data, may consists of missing, incorrect and sometimes incomplete values sets that can have a detrimental effect on the decisions that are outcomes of data analytics. Using the PIMA Indians Diabetes dataset, we have proposed an efficient imputation method using a hybrid combination of CART and Genetic Algorithm, as a preprocessing step. the classical neural network model is used for prediction, on the preprocessed dataset. the accuracy achieved by the proposed model far exceeds the existing models, mainly because of the soft computing preprocessing adopted. this approach is simple, easy to understand and implement and practical in its approach.

关键词： Predictive analytics

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Local Trinary patterns for human action recognition

Local Trinary Patterns for human action recognition

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international conference on Computer Vision (ICCV)

作者： Lahav Yeffet Lior Wolf Blavatnik School of Computer Science Tel-Aviv University Israel

We present a novel action recognition method which is based on combining the effective description properties of Local Binary patterns with the appearance invariance and adaptability of patch matching based methods. the resulting method is extremely efficient, and thus is suitable for real-time uses of simultaneous recovery of human action of several lengths and starting points. Tested on all publicity available datasets in the literature known to us, our system repeatedly achieves state of the art performance. Lastly, we present a new benchmark that focuses on uncut motion recognition in broadcast sports video.

关键词： Humans pattern recognition Histograms Optical computing Atom optics Concatenated codes Computer science pattern matching System testing Benchmark testing

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Computer-Aided Assessment of Anomalies in the Scoliotic Spine in 3-D MRI Images

Computer-Aided Assessment of Anomalies in the Scoliotic Spin...

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12th international conference on Medical Image computing and Computer-Assisted Intervention (MICCAI2009)

作者： Jaeger, Florian Hornegger, Joachim Schwab, Siegfried Janka, Rolf Univ Erlangen Nurnberg Dept Comp Sci Chair Pattern Recognit Erlangen Germany Univ Erlangen Nurnberg Radiol Inst Erlangen Germany

ISBN: (纸本)9783642042706

the assessment of anomalies in the scoliotic spine using Magnetic Resonance Imaging (MRI) is an essential task during the planning phase of a patient's treatment and operations. Due to the pathologic bending of the spine, this is an extremely time consuming process as an orthogonal view onto every vertebra is required. In this article we present a system for computer-aided assessment (CAA) of anomalies in 3-D MRI images of the spine relying on curved planar reformations (CPR). We introduce all necessary steps, from the pre-processing of the data to the visualization component. As the core part of the framework is based oil a segmentation of the spinal cord we focus on this. the proposed segmentation method is an iterative process. In every iteration the segmentation is updated by an energy based scheme derived from Markov random field (MRF) theory. We evaluate the segmentation results on public available clinical relevant 3-D MRI data sets of scoliosis patients. In order to assess the quality of the segmentation we use the angle between automatically computed planes through the vertebra and planes estimated by medical experts. this results in a mean angle difference of less than six degrees.

关键词： Magnetic resonance imaging

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Time-of-Flight 3-D Endoscopy

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12th international conference on Medical Image computing and Computer-Assisted Intervention (MICCAI2009)

作者： Penne, Jochen Hoeller, Kurt Stuermer, Michael Schrauder, thomas Schneider, Armin Engelbrecht, Rainer Feussner, Hubertus Schmauss, Bernhard Hornegger, Joachim Univ Erlangen Nurnberg Chair Pattern Recognit D-8520 Erlangen Germany Univ Erlangen Nurnberg Erlangen Grad Sch Adv Optical Technolo SAOT D-8520 Erlangen Germany Univ Erlangen Nurnberg Chair Microwave Engn & High Freq Technol D-8520 Erlangen Germany Tech Univ Munich Workgrp Minimal Invas Therapy & Intervent D-80290 Munich Germany

ISBN: (纸本)9783642042676

this paper describes the first;accomplishment of the Time-of-Flight (ToF) measurement principle via endoscope optics. the applicability of the approach is verified by in-vitro experiments. Off-the-shelf ToF camera, sensors enable the per-pixel, on-chip, real-time, marker-less acquisition of distance information. the transfer of the emerging ToF measurement technique to endoscope optics is the basis for a new generation of ToF rigid or flexible 3-D endoscopes. No modification of the endoscope optic itself is necessary as only in enhancement of illumination unit and image sensors is necessary. the major contribution of this paper is threefold: First, the accomplishment of the ToF measurement principle via endoscope optics;second, the development and validation of a complete calibration and post-processing routine;third, accomplishment of extensive in-vitro experiments. Currently, a depth measurement precision of 0.89 mm at 20 fps with 3072 3-D points is achieved.

关键词： Endoscopy

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Rough set year in India 2009 1

引用

12th international conference on Rough Sets, Fuzzy Sets, Data Mining and Granular computing, RSFDGrC 2009

作者： Joshi, Manish Bhaumik, Rabi N. Lingras, Pawan Patil, Nitin Salgaonkar, Ambuja Ślȩzak, Dominik Department of Computer Science North Maharashtra University Jalgaon Maharashtra 425 001 India Department of Mathematics Tripura University Suryamaninagar Tripura 799 130 India Department of Mathematics and Computing Science Saint Mary's University Halifax NS B3H 3C3 Canada Department of Computer Science University of Pune Pune 411 007 India Department of Computer Science University of Mumbai Mumbai 400 098 India Institute of Mathematics University of Warsaw Banacha 2 Warsaw 02-097 Poland Infobright Inc. Poland Krzywickiego 34 pok. 219 Warsaw 02-078 Poland

ISBN: (数字)9783642106460

ISBN: (纸本)3642106455

Since its inception in early 80's, the rough set theory has attracted a lot of interest from global research community. It turns out as useful in building classification and prediction models. It complements a number of other soft computing paradigms. It may be combined with fuzzy logic and probabilistic data analysis. It has led towards enhancements of neural networks, genetic algorithms, clustering, support vector machines, regressionmodels, et cetera. Its application domains include pattern recognition, feature selection, information retrieval, bioinformatics, computer vision, multimedia, medicine, retail data mining, web mining, control, traffic engineering, data warehousing, and many others. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Rough set theory

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Fast Automatic Segmentation of the Esophagus from 3D CT Data Using a Probabilistic Model

引用

12th international conference on Medical Image computing and Computer-Assisted Intervention (MICCAI2009)

作者： Feulner, Johannes Zhou, S. Kevin Cavallaro, Alexander Seifert, Sascha Hornegger, Joachim Comaniciu, Dorin Univ Erlangen Nurnberg Chair Pattern Recognit Nurnberg Germany Siemens Corp Res Princeton NJ USA Siemens Corp Technol Erlangen Germany Univ Hosp Erlangen Inst Radiol Erlangen Germany Erlangen Grad Sch Adv Opt Tech SAOT Erlangen Germany

ISBN: (纸本)9783642042676

Automated segmentation of the esophagus in CT images is of high value to radiologists for oncological examinations of the mediastinum. It can serve as a. guideline and prevent;confusion with pathological tissue. However, segmentation is a challenging problem due to low contrast and versatile appearance of the esophagus. lit this paper, a two step method is proposed which first finds the approximate shape using a "detect and connect" approach. A classifier is trained to find short, segments of esophagus, which are approximated by an elliptical model. Recently developed techniques ill discriminative learning and printing of the search space enable a rapid detection of possible esophagus segments. Prior shape knowledge of the complete esophagus is modeled using a Markov chain framework, which allows efficient inferrence of the approximate shape from the detected candidate segments. In a refinement step, the surface of the detected shape is non-rigidly deformed to better fit the organ boundaries. lit contrast, to previously proposed methods, no user interaction is required. It was evaluated oil 117 datasets and achieves a mean segmentation error of 2.28mm with less than 9s computation time.

关键词： Markov processes

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3-D Respiratory Motion Compensation during EP Procedures by Image-Based 3-D Lasso Catheter Model Generation and Tracking

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12th international conference on Medical Image computing and Computer-Assisted Intervention (MICCAI2009)

作者： Brost, Alexander Liao, Rui Hornegger, Joachim Strobel, Norbert Friedrich Alexander Univ Erlangen Nuremberg Dept Comp Sci Chair Pattern Recognit Erlangen Germany Siemens Corp Res Imaging & Visualizat Princeton NJ USA Siemens AG Healthcare Sect Forchheim Germany

ISBN: (纸本)9783642042676

Radio-frequency catheter ablation of the pulmonary veins attached to the left atrium is usually carried out under fluoroscopy guidance. Two-dimensional X-ray navigation may involve overlay images derived from a static pre-operative 3-D volumetric data set to add anatomical details. However, respiratory motion may impair the utility of static overlay images for catheter navigation. We developed a, system for image-based 3-D motion estimation and compensation as a solution to this problem for which no previous solution is yet known. It is based on 3-D catheter tracking involving 2-D/3-D registration. A biplane X-ray C-arm system is used to image a. special circumferential (lasso) catheter from two directions. In the first step of the method, a 3-D model of the device is reconstructed. 3-D respiratory motion at the site of ablation is then estimated by tracking the reconstructed model in 3-D from biplane fluoroscopy. In our experiments, the circumferential catheter was tracked in 231 biplane fluoro frames (462 monoplane fluoro frames) with an average 2-D tracking error of 1.0 mm +/- 0.5 mm.

关键词： Catheters

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