Download or read book Understanding Atrial Fibrillation written by Luca Mainardi and published by Springer Nature. This book was released on 2022-05-31 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents recent advances in signal processing techniques for modeling, analysis, and understanding of the heart's electrical activity during atrial fibrillation. This arrhythmia is the most commonly encountered in clinical practice and its complex and metamorphic nature represents a challenging problem for clinicians, engineers, and scientists. Research on atrial fibrillation has stimulated the development of a wide range of signal processing tools to better understand the mechanisms ruling its initiation, maintenance, and termination. This book provides undergraduate and graduate students, as well as researchers and practicing engineers, with an overview of techniques, including time domain techniques for atrial wave extraction, time-frequency analysis for exploring wave dynamics, and nonlinear techniques to characterize the ventricular response and the organization of atrial activity. The book includes an introductory chapter about atrial fibrillation and its mechanisms, treatment, and management. The successive chapters are dedicated to the analysis of atrial signals recorded on the body surface and to the quantification of ventricular response. The rest of the book explores techniques to characterize endo- and epicardial recordings and to model atrial conduction. Under the appearance of being a monothematic book on atrial fibrillation, the reader will not only recognize common problems of biomedical signal processing but also discover that analysis of atrial fibrillation is a unique challenge for developing and testing novel signal processing tools. Table of Contents: Part I / Introduction to Atrial Fibrillation: From Mechanisms to Treatment / Time Domain Analysis of Atrial Fibrillation / Atrial Activity Extraction from the ECG / Time-Frequency Analysis of Atrial Fibrillation

Download or read book Understanding Atrial Fibrillation written by Luca Mainardi and published by Springer Nature. This book was released on 2022-05-31 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents recent advances in signal processing techniques for modeling, analysis, and understanding of the heart's electrical activity during atrial fibrillation. This arrhythmia is the most commonly encountered in clinical practice and its complex and metamorphic nature represents a challenging problem for clinicians, engineers, and scientists. Research on atrial fibrillation has stimulated the development of a wide range of signal processing tools to better understand the mechanisms ruling its initiation, maintenance, and termination. This book provides undergraduate and graduate students, as well as researchers and practicing engineers, with an overview of techniques, including time domain techniques for atrial wave extraction, time-frequency analysis for exploring wave dynamics, and nonlinear techniques to characterize the ventricular response and the organization of atrial activity. The book includes an introductory chapter about atrial fibrillation and its mechanisms, treatment, and management. The successive chapters are dedicated to the analysis of atrial signals recorded on the body surface and to the quantification of ventricular response. The rest of the book explores techniques to characterize endo- and epicardial recordings and to model atrial conduction. Under the appearance of being a monothematic book on atrial fibrillation, the reader will not only recognize common problems of biomedical signal processing but also discover that analysis of atrial fibrillation is a unique challenge for developing and testing novel signal processing tools. Table of Contents: Analysis of Ventricular Response During Atrial Fibrillation / Organization Measures of Atrial Activity During Fibrillation / Modeling Atrial Fibrillation: From Myocardial Cells to ECG / Algorithms for Atrial Tachyarrythmia Detection for Long-Term Monitoring with Implantable Devices

Download or read book Understanding Atrial Fibrillation written by Luca Mainardi and published by Morgan & Claypool Publishers. This book was released on 2008-12-05 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents recent advances in signal processing techniques for modeling, analysis, and understanding of the heart's electrical activity during atrial fibrillation. This arrhythmia is the most commonly encountered in clinical practice and its complex and metamorphic nature represents a challenging problem for clinicians, engineers, and scientists. Research on atrial fibrillation has stimulated the development of a wide range of signal processing tools to better understand the mechanisms ruling its initiation, maintenance, and termination. This book provides undergraduate and graduate students, as well as researchers and practicing engineers, with an overview of techniques, including time domain techniques for atrial wave extraction, time-frequency analysis for exploring wave dynamics, and nonlinear techniques to characterize the ventricular response and the organization of atrial activity. The book includes an introductory chapter about atrial fibrillation and its mechanisms, treatment, and management. The successive chapters are dedicated to the analysis of atrial signals recorded on the body surface and to the quantification of ventricular response. The rest of the book explores techniques to characterize endo- and epicardial recordings and to model atrial conduction. Under the appearance of being a monothematic book on atrial fibrillation, the reader will not only recognize common problems of biomedical signal processing but also discover that analysis of atrial fibrillation is a unique challenge for developing and testing novel signal processing tools. Table of Contents: Analysis of Ventricular Response During Atrial Fibrillation / Organization Measures of Atrial Activity During Fibrillation / Modeling Atrial Fibrillation: From Myocardial Cells to ECG / Algorithms for Atrial Tachyarrythmia Detection for Long-Term Monitoring with Implantable Devices

Download or read book Understanding Atrial Fibrillation written by Luca Mainardi and published by Morgan & Claypool Publishers. This book was released on 2008-01-01 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents recent advances in signal processing techniques for modeling, analysis, and understanding of the heart's electrical activity during atrial fibrillation. This arrhythmia is the most commonly encountered in clinical practice and its complex and metamorphic nature represents a challenging problem for clinicians, engineers, and scientists. Research on atrial fibrillation has stimulated the development of a wide range of signal processing tools to better understand the mechanisms ruling its initiation, maintenance, and termination. This book provides undergraduate and graduate students, as well as researchers and practicing engineers, with an overview of techniques, including time domain techniques for atrial wave extraction, time-frequency analysis for exploring wave dynamics, and nonlinear techniques to characterize the ventricular response and the organization of atrial activity. The book includes an introductory chapter about atrial fibrillation and its mechanisms, treatment, and management. The successive chapters are dedicated to the analysis of atrial signals recorded on the body surface and to the quantification of ventricular response. The rest of the book explores techniques to characterize endo- and epicardial recordings and to model atrial conduction. Under the appearance of being a monothematic book on atrial fibrillation, the reader will not only recognize common problems of biomedical signal processing but also discover that analysis of atrial fibrillation is a unique challenge for developing and testing novel signal processing tools.

Download or read book Atrial Fibrillation from an Engineering Perspective written by Leif Sörnmo and published by Springer. This book was released on 2018-05-15 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Atrial Fibrillation from an Engineering Perspective provides an up-to-date overview of techniques developed for acquisition, modeling, and analysis of noninvasive, bioelectrical signals reflecting this common arrhythmia. Special emphasis is put on emerging technologies for monitoring of atrial fibrillation in connection with ischemic stroke, interventional ablation procedures, and pharmacological treatment, applications which all depend on the availability of techniques for detecting and characterizing episodes of paroxysmal atrial fibrillation. Detectors exploring both rhythm and morphology are described, as well as detectors confined to rhythm and better suited for low power implementation. A wide variety of approaches to modeling and characterization of atrial activity are described, emanating from a statistical and deterministic starting points. This book is suitable for graduate students, researchers, and engineers who want a comprehensive treatise of atrial fibrillation from an engineering perspective. It may be used for self-study, as a supplement to courses in signal processing, or as a modern monograph by researchers in the field of atrial fibrillation.

Download or read book Digital Image Processing for Ophthalmology written by Faraz Oloumi and published by Springer Nature. This book was released on 2022-06-01 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: The monitoring of the effects of retinopathy on the visual system can be assisted by analyzing the vascular architecture of the retina. This book presents methods based on Gabor filters to detect blood vessels in fundus images of the retina. Forty images of the retina from the Digital Retinal Images for Vessel Extraction (DRIVE) database were used to evaluate the performance of the methods. The results demonstrate high efficiency in the detection of blood vessels with an area under the receiver operating characteristic curve of 0.96. Monitoring the openness of the major temporal arcade (MTA) could facilitate improved diagnosis and optimized treatment of retinopathy. This book presents methods for the detection and modeling of the MTA, including the generalized Hough transform to detect parabolic forms. Results obtained with 40 images of the DRIVE database, compared with hand-drawn traces of the MTA, indicate a mean distance to the closest point of about 0.24mm. This book illustrates applications of the methods mentioned above for the analysis of the effects of proliferative diabetic retinopathy and retinopathy of prematurity on retinal vascular architecture.

Download or read book Biomedical Signals and Systems written by Joseph Tranquillo and published by Springer Nature. This book was released on 2022-06-01 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biomedical Signals and Systems is meant to accompany a one-semester undergraduate signals and systems course. It may also serve as a quick-start for graduate students or faculty interested in how signals and systems techniques can be applied to living systems. The biological nature of the examples allows for systems thinking to be applied to electrical, mechanical, fluid, chemical, thermal and even optical systems. Each chapter focuses on a topic from classic signals and systems theory: System block diagrams, mathematical models, transforms, stability, feedback, system response, control, time and frequency analysis and filters. Embedded within each chapter are examples from the biological world, ranging from medical devices to cell and molecular biology. While the focus of the book is on the theory of analog signals and systems, many chapters also introduce the corresponding topics in the digital realm. Although some derivations appear, the focus is on the concepts and how to apply them. Throughout the text, systems vocabulary is introduced which will allow the reader to read more advanced literature and communicate with scientist and engineers. Homework and Matlab simulation exercises are presented at the end of each chapter and challenge readers to not only perform calculations and simulations but also to recognize the real-world signals and systems around them. Table of Contents: Preface / Acknowledgments / Introduction / System Types / System Models / Laplace Transform / Block Diagrams / Stability / Feedback / System Response / Control / Time Domain Analysis / Frequency Domain Analysis / Filters / Author's Biography

Download or read book Analysis of Oriented Texture with application to the Detection of Architectural Distortion in Mammograms written by Fabio Ayres and published by Springer Nature. This book was released on 2022-06-01 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: The presence of oriented features in images often conveys important information about the scene or the objects contained; the analysis of oriented patterns is an important task in the general framework of image understanding. As in many other applications of computer vision, the general framework for the understanding of oriented features in images can be divided into low- and high-level analysis. In the context of the study of oriented features, low-level analysis includes the detection of oriented features in images; a measure of the local magnitude and orientation of oriented features over the entire region of analysis in the image is called the orientation field. High-level analysis relates to the discovery of patterns in the orientation field, usually by associating the structure perceived in the orientation field with a geometrical model. This book presents an analysis of several important methods for the detection of oriented features in images, and a discussion of the phase portrait method for high-level analysis of orientation fields. In order to illustrate the concepts developed throughout the book, an application is presented of the phase portrait method to computer-aided detection of architectural distortion in mammograms. Table of Contents: Detection of Oriented Features in Images / Analysis of Oriented Patterns Using Phase Portraits / Optimization Techniques / Detection of Sites of Architectural Distortion in Mammograms

Download or read book Fractal Analysis of Breast Masses in Mammograms written by Thanh Cabral and published by Springer Nature. This book was released on 2022-06-01 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fractal analysis is useful in digital image processing for the characterization of shape roughness and gray-scale texture or complexity. Breast masses present shape and gray-scale characteristics in mammograms that vary between benign masses and malignant tumors. This book demonstrates the use of fractal analysis to classify breast masses as benign masses or malignant tumors based on the irregularity exhibited in their contours and the gray-scale variability exhibited in their mammographic images. A few different approaches are described to estimate the fractal dimension (FD) of the contour of a mass, including the ruler method, box-counting method, and the power spectral analysis (PSA) method. Procedures are also described for the estimation of the FD of the gray-scale image of a mass using the blanket method and the PSA method. To facilitate comparative analysis of FD as a feature for pattern classification of breast masses, several other shape features and texture measures are described in the book. The shape features described include compactness, spiculation index, fractional concavity, and Fourier factor. The texture measures described are statistical measures derived from the gray-level cooccurrence matrix of the given image. Texture measures reveal properties about the spatial distribution of the gray levels in the given image; therefore, the performance of texture measures may be dependent on the resolution of the image. For this reason, an analysis of the effect of spatial resolution or pixel size on texture measures in the classification of breast masses is presented in the book. The results demonstrated in the book indicate that fractal analysis is more suitable for characterization of the shape than the gray-level variations of breast masses, with area under the receiver operating characteristics of up to 0.93 with a dataset of 111 mammographic images of masses. The methods and results presented in the book are useful for computer-aided diagnosis of breast cancer. Table of Contents: Computer-Aided Diagnosis of Breast Cancer / Detection and Analysis of\newline Breast Masses / Datasets of Images of Breast Masses / Methods for Fractal Analysis / Pattern Classification / Results of Classification of Breast Masses / Concluding Remarks

Download or read book Modeling and Analysis of Shape with Applications in Computer aided Diagnosis of Breast Cancer written by Denise Guliato and published by Springer Nature. This book was released on 2022-05-31 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: Malignant tumors due to breast cancer and masses due to benign disease appear in mammograms with different shape characteristics: the former usually have rough, spiculated, or microlobulated contours, whereas the latter commonly have smooth, round, oval, or macrolobulated contours. Features that characterize shape roughness and complexity can assist in distinguishing between malignant tumors and benign masses. In spite of the established importance of shape factors in the analysis of breast tumors and masses, difficulties exist in obtaining accurate and artifact-free boundaries of the related regions from mammograms. Whereas manually drawn contours could contain artifacts related to hand tremor and are subject to intra-observer and inter-observer variations, automatically detected contours could contain noise and inaccuracies due to limitations or errors in the procedures for the detection and segmentation of the related regions. Modeling procedures are desired to eliminate the artifacts in a given contour, while preserving the important and significant details present in the contour. This book presents polygonal modeling methods that reduce the influence of noise and artifacts while preserving the diagnostically relevant features, in particular the spicules and lobulations in the given contours. In order to facilitate the derivation of features that capture the characteristics of shape roughness of contours of breast masses, methods to derive a signature based on the turning angle function obtained from the polygonal model are described. Methods are also described to derive an index of spiculation, an index characterizing the presence of convex regions, an index characterizing the presence of concave regions, an index of convexity, and a measure of fractal dimension from the turning angle function. Results of testing the methods with a set of 111 contours of 65 benign masses and 46 malignant tumors are presented and discussed. It is shown that shape modeling and analysis can lead to classification accuracy in discriminating between benign masses and malignant tumors, in terms of the area under the receiver operating characteristic curve, of up to 0.94. The methods have applications in modeling and analysis of the shape of various types of regions or objects in images, computer vision, computer graphics, and analysis of biomedical images, with particular significance in computer-aided diagnosis of breast cancer. Table of Contents: Analysis of Shape / Polygonal Modeling of Contours / Shape Factors for Pattern Classification / Classification of Breast Masses

Download or read book Digital Image Processing for Ophthalmology written by Xiaolu Zhu and published by Springer Nature. This book was released on 2022-05-31 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundus images of the retina are color images of the eye taken by specially designed digital cameras. Ophthalmologists rely on fundus images to diagnose various diseases that affect the eye, such as diabetic retinopathy and retinopathy of prematurity. A crucial preliminary step in the analysis of retinal images is the identification and localization of important anatomical structures, such as the optic nerve head (ONH), the macula, and the major vascular arcades. Identification of the ONH is an important initial step in the detection and analysis of the anatomical structures and pathological features in the retina. Different types of retinal pathology may be detected and analyzed via the application of appropriately designed techniques of digital image processing and pattern recognition. Computer-aided analysis of retinal images has the potential to facilitate quantitative and objective analysis of retinal lesions and abnormalities. Accurate identification and localization of retinal features and lesions could contribute to improved diagnosis, treatment, and management of retinopathy. This book presents an introduction to diagnostic imaging of the retina and an overview of image processing techniques for ophthalmology. In particular, digital image processing algorithms and pattern analysis techniques for the detection of the ONH are described. In fundus images, the ONH usually appears as a bright region, white or yellow in color, and is indicated as the convergent area of the network of blood vessels. Use of the geometrical and intensity characteristics of the ONH, as well as the property that the ONH represents the location of entrance of the blood vessels and the optic nerve into the retina, is demonstrated in developing the methods. The image processing techniques described in the book include morphological filters for preprocessing fundus images, filters for edge detection, the Hough transform for the detection of lines and circles, Gabor filters to detect the blood vessels, and phase portrait analysis for the detection of convergent or node-like patterns. Illustrations of application of the methods to fundus images from two publicly available databases are presented, in terms of locating the center and the boundary of the ONH. Methods for quantitative evaluation of the results of detection of the ONH using measures of overlap and free-response receiver operating characteristics are also described. Table of Contents: Introduction / Computer-aided Analysis of Images of the Retina / Detection of Geometrical Patterns / Datasets and Experimental Setup / Detection of the\\Optic Nerve Head\\Using the Hough Transform / Detection of the\\Optic Nerve Head\\Using Phase Portraits / Concluding Remarks

Download or read book Fundamentals of Biomedical Transport Processes written by Gerald Miller and published by Springer Nature. This book was released on 2022-06-01 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transport processes represent important life-sustaining elements in all humans. These include mass transfer processes, including gas exchange in the lungs, transport across capillaries and alveoli, transport across the kidneys, and transport across cell membranes. These mass transfer processes affect how oxygen and carbon dioxide are exchanged in your bloodstream, how metabolic waste products are removed from your blood, how nutrients are transported to tissues, and how all cells function throughout the body. A discussion of kidney dialysis and gas exchange mechanisms is included. Another element in biomedical transport processes is that of momentum transport and fluid flow. This describes how blood is propelled from the heart and throughout the cardiovascular system, how blood elements affect the body, including gas exchange, infection control, clotting of blood, and blood flow resistance, which affects cardiac work. A discussion of the measurement of the blood resistance to flow (viscosity), blood flow, and pressure is also included. A third element in transport processes in the human body is that of heat transfer, including heat transfer inside the body towards the periphery as well as heat transfer from the body to the environment. A discussion of temperature measurements and body protection in extreme heat conditions is also included. Table of Contents: Biomedical Mass Transport / Biofluid Mechanics and Momentum Transport / Biomedical Heat Transport

Download or read book Computerized Analysis of Mammographic Images for Detection and Characterization of Breast Cancer written by Arianna Mencattini and published by Springer Nature. This book was released on 2022-05-31 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: The identification and interpretation of the signs of breast cancer in mammographic images from screening programs can be very difficult due to the subtle and diversified appearance of breast disease. This book presents new image processing and pattern recognition techniques for computer-aided detection and diagnosis of breast cancer in its various forms. The main goals are: (1) the identification of bilateral asymmetry as an early sign of breast disease which is not detectable by other existing approaches; and (2) the detection and classification of masses and regions of architectural distortion, as benign lesions or malignant tumors, in a unified framework that does not require accurate extraction of the contours of the lesions. The innovative aspects of the work include the design and validation of landmarking algorithms, automatic Tabár masking procedures, and various feature descriptors for quantification of similarity and for contour independent classification of mammographic lesions. Characterization of breast tissue patterns is achieved by means of multidirectional Gabor filters. For the classification tasks, pattern recognition strategies, including Fisher linear discriminant analysis, Bayesian classifiers, support vector machines, and neural networks are applied using automatic selection of features and cross-validation techniques. Computer-aided detection of bilateral asymmetry resulted in accuracy up to 0.94, with sensitivity and specificity of 1 and 0.88, respectively. Computer-aided diagnosis of automatically detected lesions provided sensitivity of detection of malignant tumors in the range of [0.70, 0.81] at a range of falsely detected tumors of [0.82, 3.47] per image. The techniques presented in this work are effective in detecting and characterizing various mammographic signs of breast disease.

Download or read book Spatiotemporal Modeling of Influenza written by William E. Schiesser and published by Springer Nature. This book was released on 2022-05-31 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has a two-fold purpose: (1) An introduction to the computer-based modeling of influenza, a continuing major worldwide communicable disease. (2) The use of (1) as an illustration of a methodology for the computer-based modeling of communicable diseases. For the purposes of (1) and (2), a basic influenza model is formulated as a system of partial differential equations (PDEs) that define the spatiotemporal evolution of four populations: susceptibles, untreated and treated infecteds, and recovereds. The requirements of a well-posed PDE model are considered, including the initial and boundary conditions. The terms of the PDEs are explained. The computer implementation of the model is illustrated with a detailed line-by-line explanation of a system of routines in R (a quality, open-source scientific computing system that is readily available from the Internet). The R routines demonstrate the straightforward numerical solution of a system of nonlinear PDEs by the method of lines (MOL), an established general algorithm for PDEs. The presentation of the PDE modeling methodology is introductory with a minumum of formal mathematics (no theorems and proofs), and with emphasis on example applications. The intent of the book is to assist in the initial understanding and use of PDE mathematical modeling of communicable diseases, and the explanation and interpretation of the computed model solutions, as illustrated with the influenza model.

Download or read book Computer Aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer written by Shantanu Banik and published by Springer Nature. This book was released on 2022-05-31 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Architectural distortion is an important and early sign of breast cancer, but because of its subtlety, it is a common cause of false-negative findings on screening mammograms. Screening mammograms obtained prior to the detection of cancer could contain subtle signs of early stages of breast cancer, in particular, architectural distortion. This book presents image processing and pattern recognition techniques to detect architectural distortion in prior mammograms of interval-cancer cases. The methods are based upon Gabor filters, phase portrait analysis, procedures for the analysis of the angular spread of power, fractal analysis, Laws' texture energy measures derived from geometrically transformed regions of interest (ROIs), and Haralick's texture features. With Gabor filters and phase-portrait analysis, 4,224 ROIs were automatically obtained from 106 prior mammograms of 56 interval-cancer cases, including 301 true-positive ROIs related to architectural distortion, and from 52 mammograms of 13 normal cases. For each ROI, the fractal dimension, the entropy of the angular spread of power, 10 Laws' texture energy measures, and Haralick's 14 texture features were computed. The areas under the receiver operating characteristic (ROC) curves obtained using the features selected by stepwise logistic regression and the leave-one-image-out method are 0.77 with the Bayesian classifier, 0.76 with Fisher linear discriminant analysis, and 0.79 with a neural network classifier. Free-response ROC analysis indicated sensitivities of 0.80 and 0.90 at 5.7 and 8.8 false positives (FPs) per image, respectively, with the Bayesian classifier and the leave-one-image-out method. The present study has demonstrated the ability to detect early signs of breast cancer 15 months ahead of the time of clinical diagnosis, on the average, for interval-cancer cases, with a sensitivity of 0.8 at 5.7 FP/image. The presented computer-aided detection techniques, dedicated to accurate detection and localization of architectural distortion, could lead to efficient detection of early and subtle signs of breast cancer at pre-mass-formation stages. Table of Contents: Introduction / Detection of Early Signs of Breast Cancer / Detection and Analysis of Oriented Patterns / Detection of Potential Sites of Architectural Distortion / Experimental Set Up and Datasets / Feature Selection and Pattern Classification / Analysis of Oriented Patterns Related to Architectural Distortion / Detection of Architectural Distortion in Prior Mammograms / Concluding Remarks

Download or read book Content based Retrieval of Medical Images written by Paulo Mazzoncini de Azevedo-Marques and published by Springer Nature. This book was released on 2022-06-01 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Content-based image retrieval (CBIR) is the process of retrieval of images from a database that are similar to a query image, using measures derived from the images themselves, rather than relying on accompanying text or annotation. To achieve CBIR, the contents of the images need to be characterized by quantitative features; the features of the query image are compared with the features of each image in the database and images having high similarity with respect to the query image are retrieved and displayed. CBIR of medical images is a useful tool and could provide radiologists with assistance in the form of a display of relevant past cases. One of the challenging aspects of CBIR is to extract features from the images to represent their visual, diagnostic, or application-specific information content. In this book, methods are presented for preprocessing, segmentation, landmarking, feature extraction, and indexing of mammograms for CBIR. The preprocessing steps include anisotropic diffusion and the Wiener filter to remove noise and perform image enhancement. Techniques are described for segmentation of the breast and fibroglandular disk, including maximum entropy, a moment-preserving method, and Otsu's method. Image processing techniques are described for automatic detection of the nipple and the edge of the pectoral muscle via analysis in the Radon domain. By using the nipple and the pectoral muscle as landmarks, mammograms are divided into their internal, external, upper, and lower parts for further analysis. Methods are presented for feature extraction using texture analysis, shape analysis, granulometric analysis, moments, and statistical measures. The CBIR system presented provides options for retrieval using the Kohonen self-organizing map and the k-nearest-neighbor method. Methods are described for inclusion of expert knowledge to reduce the semantic gap in CBIR, including the query point movement method for relevance feedback (RFb). Analysis of performance is described in terms of precision, recall, and relevance-weighted precision of retrieval. Results of application to a clinical database of mammograms are presented, including the input of expert radiologists into the CBIR and RFb processes. Models are presented for integration of CBIR and computer-aided diagnosis (CAD) with a picture archival and communication system (PACS) for efficient workflow in a hospital. Table of Contents: Introduction to Content-based Image Retrieval / Mammography and CAD of Breast Cancer / Segmentation and Landmarking of Mammograms / Feature Extraction and Indexing of Mammograms / Content-based Retrieval of Mammograms / Integration of CBIR and CAD into Radiological Workflow

Download or read book The Graph Theoretical Approach in Brain Functional Networks written by Fabrizio Fallani and published by Springer Nature. This book was released on 2022-06-01 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present book illustrates the theoretical aspects of several methodologies related to the possibility of i) enhancing the poor spatial information of the electroencephalographic (EEG) activity on the scalp and giving a measure of the electrical activity on the cortical surface. ii) estimating the directional influences between any given pair of channels in a multivariate dataset. iii) modeling the brain networks as graphs. The possible applications are discussed in three different experimental designs regarding i) the study of pathological conditions during a motor task, ii) the study of memory processes during a cognitive task iii) the study of the instantaneous dynamics throughout the evolution of a motor task in physiological conditions. The main outcome from all those studies indicates clearly that the performance of cognitive and motor tasks as well as the presence of neural diseases can affect the brain network topology. This evidence gives the power of reflecting cerebral "states" or "traits" to the mathematical indexes derived from the graph theory. In particular, the observed structural changes could critically depend on patterns of synchronization and desynchronization - i.e. the dynamic binding of neural assemblies - as also suggested by a wide range of previous electrophysiological studies. Moreover, the fact that these patterns occur at multiple frequencies support the evidence that brain functional networks contain multiple frequency channels along which information is transmitted. The graph theoretical approach represents an effective means to evaluate the functional connectivity patterns obtained from scalp EEG signals. The possibility to describe the complex brain networks sub-serving different functions in humans by means of "numbers" is a promising tool toward the generation of a better understanding of the brain functions. Table of Contents: Introduction / Brain Functional Connectivity / Graph Theory / High-Resolution EEG / Cortical Networks in Spinal Cord Injured Patients / Cortical Networks During a Lifelike Memory Task / Application to Time-varying Cortical Networks / Conclusions