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Rule-based decision-making framework for knowledge-based anatomical landmark localization (K-BALL)

Rule-based decision-making framework for knowledge-based ana...

引用

IEEE International Symposium on Biomedical Imaging

作者： M.-R. Siadat H. Soltanian-Zadeh K. Elisevich Henry Ford Health System Radiology Image Analysis Laboratory Detroit MI USA Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Neurosurgery Henry Ford Health System Detroit MI USA

K-BALL is a general method for localization of anatomical phenomena of the same origin with natural discrepancies distributed over a reference space, e.g., human brain anatomical structures. In this paper, we focus on information analysis step (2nd step) of K-BALL during which landmarks extracted in its first step are evaluated. We provide a framework in which rules are automatically generated based on estimated and derived models. We show that the rules based on the derived models can improve the overall success rate of K-BALL. Each rule evaluates the extracted points by producing an intermediate confidence factor (ICNF). A total confidence factor is calculated using ICNF's to facilitate the acceptance or rejection of a set of points as landmarks of interest. Using the rules merely based on the estimated models, simulation study produced an overall success rate of 91.8%. Using the rules based on both of the estimated and derived models, this rate increased to 92.5%

关键词： Decision making Hippocampus Information analysis Data mining Humans Radiology image analysis Radio control Process control Control systems

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Determination of the Grey Level Ranks for the Segmentation of Textured images

Determination of the Grey Level Ranks for the Segmentation o...

引用

IEEE International Symposium on Industrial Electronics (ISIE)

作者： Z. Ameur A. Adane S. Ameur Faculty of Electrical Engineering and Computer Science Department of Electronics Laboratory of Random Phenomena Analysis and Modeling LAMPA Mouloud Mammeri University Tizi Ouzou Algeria Faculty of Electronics and Computer Science Department of Telecommunications Laboratory of Image Processing and Radiation University of Sciences and Technology of Algiers U. S. T. H. B. Bab-Ezzouar Algeria

In many cases, an image is made of various types of texture. Such diversity can be usefully exploited to get a suitable decomposition of the image into typical classes and then, identify its constitutive elements. Among the approaches used to segment textured images, those based on the statistical analysis of the neighborhood of each pixel seem to be most efficient. In this paper, this kind of method is implemented, which consists in coding the pixels surrounding each point of the image by taking into account the path traveling through them and their grey levels. The rank vectors namely the codes obtained for all the possible paths, are then classified using the K-means algorithm. Considering the 24- rank vectors, this method is tested on different images of the Brodatz album and compared with Laws filters and GLCM. It yields a satisfactory reproduction of the image contours and a classification ratio exceeding 98 %. The 24 rank based-method is also applied to meteorological images collected by Meteosat over Europe and North Africa during December 1994. It is found that these images can be segmented into eight typical classes assignable to the soils, the seas and the clouds observed in the regions under study.

关键词： image segmentation Pixel Statistical analysis image coding Testing Filters Meteorology Europe Africa Soil

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Medical Data Mining using Particle Swarm Optimization for Temporal Lobe Epilepsy

Medical Data Mining using Particle Swarm Optimization for Te...

引用

Congress on Evolutionary Computation

作者： M. Ghannad-Rezaie H. Soltanain-Zadeh M.-R. Siadat K.V. Elisevich Henry Ford Health System and Wayne State University Detroit MI USA Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Neurosurgery Department Henry Ford Health System Detroit MI USA

In clinical problems, numerous factors are usually involved in a medical syndrome. New advances in medicine provide a broad range of diagnosis methods to cover all aspects of a disease. However, huge amounts of raw information may confuse clinicians and decrease decision accuracy. computerized knowledge extraction is an active area of research in medical informatics. This paper suggests a new medical data mining approach using an advanced swarm intelligence data mining algorithm. Considering medical knowledge discovery difficulties, this approach addresses common issues such as missing value management and interactive rule extraction. Here, surgery candidate selection in temporal lobe epilepsy is the main target application. However, the general idea can be applied to other medical knowledge discovery problems. Experimental results show noticeable performance improvement in the final rule-set quality while the method is flexible and fast.

关键词： Data mining Particle swarm optimization Temporal lobe Epilepsy Medical diagnostic imaging Biomedical imaging Coronary arteriosclerosis Diseases Surgery Medical services

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Approximation of a linear shift-variant system by a set of linear shift-invariant systems

Approximation of a linear shift-variant system by a set of l...

引用

ISSCS 2005: International Symposium on Signals, Circuits and Systems

作者： Buzuloiu, Vasile Malciu, Marius Mitra, Sanjit K. Image Processing and Analysis Laboratory University Politehnica of Bucharest Bucharest Romania CERN Geneva Department of Electrical and Computer Engineering University of California Santa Barbara

ISBN: (纸本)0780390296

This paper describes a method to approximate the impulse response or a linear shift-variant system by the impulse responses of a set of linear shift-invariant systems which process in parallel on various windowed versions of the input signal The method is outlined for one-dimensional systems but the extension to multidimensional case is straightforward. © 2005 IEEE.

关键词： Linear systems

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Uncertain decision-making schemes for knowledge based anatomical landmark localization (K-BALL)

Uncertain decision-making schemes for knowledge based anatom...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： M.R. Siadat H. Soltanian-Zadeh K. Elisevich Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Department of Electrical and Computer Engineering University of Tehran Tehran Iran

We have proposed a method for localization of anatomical landmarks comprised of two steps: 1) information extraction, and 2) information analysis. The focus of this paper is on the second step during which a set of points, found in the first step, is evaluated. This step utilizes a set of rules and eventually generates a confidence factor (CNF) for each set of points that indicates as to what degree they are good representatives of the "landmarks of interest". We also propose two alternative decision-making schemes: 1) Bayesian networks, and 2) possibilistic inference methods. The latter design is expected to outperform the other two as it utilizes both desired and undesired information. Our simulation study resulted in very similar performance for the rule-based and Bayesian schemes. The overall success rate (average of sensitivity and specificity) of the entire proposed method in localization of the hippocampus on MRI images was 83.3% with an accuracy of 99.2% (using rule-based decision-making scheme).

关键词： Decision making Data mining Information analysis Bayesian methods Hippocampus Sensitivity and specificity Brain modeling Deformable models Anatomical structure image analysis

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Approximation of a linear shift-variant system by a set of linear shift-invariant systems

Approximation of a linear shift-variant system by a set of l...

引用

International Symposium on Signals, Circuits and Systems (ISSCS)

作者： V. Buzuloiu M. Malciu S.K. Mitra Image Processing and Analysis Laboratory University “Politehnica” of Bucharest Bucharest Romania CERN Geneva Department of Electrical and Computer Engineering University of California at Santa Barbara USA

This paper describes a method to approximate the impulse response of a linear shift-variant system by the impulse responses of a set of linear shift-invariant systems which process in parallel on various windowed versions of the input signal. The method is outlined for one-dimensional systems but the extension to multidimensional case is straightforward.

关键词： Linear approximation Large scale integration image processing image analysis Laboratories Multidimensional systems Linearity image restoration Signal restoration Transfer functions

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A robust multi-view freehand three-dimensional ultrasound imaging system using volumetric registration

A robust multi-view freehand three-dimensional ultrasound im...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Honggang Yu M.S. Pattichis M.B. Goens Department of Electrical and Computer Engineering Image and Video Processing and Communications Laboratory USA Childrens Hospital Heart Center University of New Mexico Albuquerque NM USA

In this paper, we describe a freehand, three-dimensional ultrasound imaging system. The system uses an electromagnetic position and orientation measurement device to capture two-dimensional ultrasound images at arbitrary planar orientations in space. For robust performance, we use a novel electromagnetic interference detection algorithm that can be used to estimate the probability density function of position and orientation measurement errors. Another important contribution of the proposed system is its ability to reconstruct from multiple standard views. The multi-view reconstruction procedure results in significant reduction in reconstruction error. The system uses object-based 3D volume registration, allowing for arbitrary rigid object movements in inter-view acquisition. The proposed system has been validated on simulated data and a physical, 3D ultrasound calibration phantom. Quantitative experimental results demonstrate the effectiveness of the 3D registration system, and a significant reduction in the mean-squared error via the use of the proposed multi-view reconstruction method.

关键词： Ultrasonic imaging Robustness image reconstruction Position measurement Electromagnetic devices Extraterrestrial measurements Electromagnetic interference Detection algorithms Probability density function Calibration

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Soft computing approaches to computer aided decision making for temporal lobe epilepsy

Soft computing approaches to computer aided decision making ...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： M.G. Rezaie H. Soltanian-Zadeh M.R. Siadat K.V. Elisevich Department of Electrical and Computer Engineering University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Department of Neurosurgery Henry Ford Health System Detroit MI USA

This paper presents and compares soft computing approaches for prediction of surgery outcome in temporal lobe epilepsy. Because of a wide range of effective parameters in epilepsy and unclear exact contribution of each, determination of the best treatment is difficult. We have implemented and compared data fusion methods and decision support algorithms to overcome this difficulty. Our simulation studies and experimental results using HBIDS (human brain image database system) data show the power of LS-SVM (least squared support vector machine) classifiers for this purpose.

关键词： Decision making Temporal lobe Epilepsy Surgery Brain modeling Support vector machines Biomedical imaging image analysis Humans image databases

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Bit-rate allocation control and quality improvement for color channels in HMVQ image compression

Bit-rate allocation control and quality improvement for colo...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Jiangling Guo P. Shrivastava K. Kepley Shuyu Yang S. Mitra B. Nutter Department of Electrical and Computer Engineering Computer Vision and Image Analysis Laboratory Texas Tech University USA Computer Vision and Image Analysis Lab Department of Electrical and Computer Engineering Texas Tech University USA

Medical images usually require higher fidelity than commonly used natural images, especially with respect to detail preservation. Color medical images also require a higher degree of color preservation. In this paper, we present the extension of the novel gray-scale image compression technique, hybrid multi-scale vector quantization (HMVQ) to color image compression. Limitations of common color image compression methods in controlling bit-rate allocation for color channels are discussed, and the ability of HMVQ in overcoming such limitations while improving the color quality is demonstrated.

关键词： image coding Biomedical imaging Medical diagnostic imaging Entropy image color analysis Gray-scale Pixel image storage Transform coding Quantization

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Multiresolution automatic segmentation of T1-weighted brain MR images

Multiresolution automatic segmentation of T1-weighted brain ...

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IEEE International Symposium on Biomedical Imaging

作者： M. Zeydabadi R.A. Zoroofi H. Soltanian-Zadeh Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA

Automatic segmentation of brain tissues is crucial to many medical imaging applications. We use a multi-resolution analysis and a power transform to extend the well-known Gaussian mixture model expectation maximization based algorithm for segmentation of white matter, gray matter, and cerebrospinal fluid from T1-weighted magnetic resonance images (MRI) of the brain. Experimental results with near 4000 synthetic and real images are included. The results illustrate that the proposed method outperforms six existing methods.

关键词： image resolution image segmentation Biomedical imaging Multiresolution analysis image analysis Magnetic analysis Algorithm design and analysis Brain modeling Magnetic liquids Magnetic resonance

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