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Modeling and Analysis of Shape with Applications in Computer-aided Diagnosis of Breast Cancer

Modeling and Analysis of Shape with Applications in Computer-aided Diagnosis of Breast Cancer PDF Author: Denise Guliato
Publisher: Springer Nature
ISBN: 303179429X
Category : Technology & Engineering
Languages : en
Pages : 75

Book Description
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

Modeling and Analysis of Shape with Applications in Computer-aided Diagnosis of Breast Cancer

Modeling and Analysis of Shape with Applications in Computer-aided Diagnosis of Breast Cancer PDF Author: Denise Guliato
Publisher: Springer Nature
ISBN: 303179429X
Category : Technology & Engineering
Languages : en
Pages : 75

Book Description
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

Medical Image Analysis and Informatics

Medical Image Analysis and Informatics PDF Author: Paulo Mazzoncini de Azevedo-Marques
Publisher: CRC Press
ISBN: 1498753205
Category : Technology & Engineering
Languages : en
Pages : 518

Book Description
With the development of rapidly increasing medical imaging modalities and their applications, the need for computers and computing in image generation, processing, visualization, archival, transmission, modeling, and analysis has grown substantially. Computers are being integrated into almost every medical imaging system. Medical Image Analysis and Informatics demonstrates how quantitative analysis becomes possible by the application of computational procedures to medical images. Furthermore, it shows how quantitative and objective analysis facilitated by medical image informatics, CBIR, and CAD could lead to improved diagnosis by physicians. Whereas CAD has become a part of the clinical workflow in the detection of breast cancer with mammograms, it is not yet established in other applications. CBIR is an alternative and complementary approach for image retrieval based on measures derived from images, which could also facilitate CAD. This book shows how digital image processing techniques can assist in quantitative analysis of medical images, how pattern recognition and classification techniques can facilitate CAD, and how CAD systems can assist in achieving efficient diagnosis, in designing optimal treatment protocols, in analyzing the effects of or response to treatment, and in clinical management of various conditions. The book affirms that medical imaging, medical image analysis, medical image informatics, CBIR, and CAD are proven as well as essential techniques for health care.

Computer-Aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer

Computer-Aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer PDF Author: Shantanu Banik
Publisher: Springer Nature
ISBN: 3031016564
Category : Technology & Engineering
Languages : en
Pages : 176

Book Description
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

Models of Horizontal Eye Movements

Models of Horizontal Eye Movements PDF Author: Alireza Ghahari
Publisher: Morgan & Claypool Publishers
ISBN: 1627055479
Category : Technology & Engineering
Languages : en
Pages : 160

Book Description
There are five different types of eye movements: saccades, smooth pursuit, vestibular ocular eye movements, optokinetic eye movements, and vergence eye movements. The purpose of this book series is focused primarily on mathematical models of the horizontal saccadic eye movement system and the smooth pursuit system, rather than on how visual information is processed. A saccade is a fast eye movement used to acquire a target by placing the image of the target on the fovea. Smooth pursuit is a slow eye movement used to track a target as it moves by keeping the target on the fovea. The vestibular ocular movement is used to keep the eyes on a target during brief head movements. The optokinetic eye movement is a combination of saccadic and slow eye movements that keeps a full-field image stable on the retina during sustained head rotation. Each of these movements is a conjugate eye movement, that is, movements of both eyes together driven by a common neural source. A vergence movement is a non-conjugate eye movement allowing the eyes to track targets as they come closer or farther away. In Part 1, early models of saccades and smooth pursuit are presented. A number of oculomotor plant models are described therein beginning with the Westheimer model published in 1954, and up through our 1995 model involving a 4th-order oculomotor plant model. In Part 2, a 2009 version of a state-of-the-art model is presented for horizontal saccades that is 3rd-order and linear, and controlled by a physiologically based time-optimal neural network. In this book, a multiscale model of the saccade system is presented, focusing on the neural network. Chapter 1 summarizes a whole muscle model of the oculomotor plant based on the 2009 3rd-order and linear, and controlled by a physiologically based time-optimal neural network. Chapter 2 presents a neural network model of biophysical neurons in the midbrain for controlling oculomotor muscles during horizontal human saccades. To investigate horizontal saccade dynamics, a neural circuitry, including omnipause neuron, premotor excitatory and inhibitory burst neurons, long lead burst neuron, tonic neuron, interneuron, abducens nucleus, and oculomotor nucleus, is developed. A generic neuron model serves as the basis to match the characteristics of each type of neuron in the neural network. We wish to express our thanks to William Pruehsner for drawing many of the illustrations in this book.

Digital Image Processing for Ophthalmology

Digital Image Processing for Ophthalmology PDF Author: Faraz Oloumi
Publisher: Springer Nature
ISBN: 3031016602
Category : Technology & Engineering
Languages : en
Pages : 151

Book Description
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.

Exosomes and MicroRNAs in Biomedical Science

Exosomes and MicroRNAs in Biomedical Science PDF Author: Hamed Mirzaei
Publisher: Springer Nature
ISBN: 3031791770
Category : Technology & Engineering
Languages : en
Pages : 171

Book Description
MicroRNAs (miRNAs) are a member of the family of non-coding RNA molecules, and consist of small conserved sequences between 19–25 nucleotides in length that are responsible for regulating many cellular functions by affecting a wide range of messenger RNAs in a sequence specific manner. Fundamental biological processes like cell proliferation and growth, stress resistance, tumorigenesis, fat metabolism, and neural development have all been shown to be governed by miRNAs. miRNAs carry out the post-transcriptional silencing of gene expression via targeting the 30-untranslated region (UTR) of the complementary mRNA sequence. The dysregulation of the expression levels of various miRNAs is typical of tumor cells, and has been associated with tumor progression and poor prognosis. Many miRNAs are up-regulated in cancer, where they can silence tumor suppressor genes such as apoptosis and immune response associated genes. Therefore, it is possible to profile the expression levels of miRNAs as biomarkers, in order to diagnose cancer and noncancerous diseases. Moreover, cancer detection in the early stages is crucial in clinical situations. Characterization of miRNAs in serum, plasma, and other bodily fluids, and understanding their stability against RNase degradation, is important to assess their suitability as biomarkers and diagnostic tools. Exosomes play an important role in inter-cellular communications, and these nanosized particles have various functions in diverse physiological pathways, in normal as well as abnormal cells. Exosomes can carry diverse cargos such as mRNAs, miRNAs, and proteins that transfer information between donor and recipient cells. Furthermore, uptake of exosomes and their cargos may promote or suppress various molecular and cellular pathways, which alter the cellular behavior. Many reports have discussed the role of exosomes released from cancer cells on the progression of cancer at various stages. Exosomes and their cargos may affect the growth of the tumor, metastasis, drug resistance, immune system function, as well as angiogenesis. Therefore, exosomes have been explored as diagnostic biomarkers in many cancers. Moreover, exosomes can be used as biological vehicles to deliver different drugs and agents like doxorubicin (DOX), miRNAs, and siRNAs. The present book covers the role of exosomes and micro-RNAs in the pathogenesis and treatment of various diseases.

Content-based Retrieval of Medical Images

Content-based Retrieval of Medical Images PDF Author: Paulo Mazzoncini de Azevedo-Marques
Publisher: Springer Nature
ISBN: 3031016513
Category : Technology & Engineering
Languages : en
Pages : 125

Book Description
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

Digital Image Processing for Ophthalmology

Digital Image Processing for Ophthalmology PDF Author: Xiaolu Zhu
Publisher: Springer Nature
ISBN: 3031016491
Category : Technology & Engineering
Languages : en
Pages : 95

Book Description
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

Nanotechnology for Bioengineers

Nanotechnology for Bioengineers PDF Author: Wujie Zhang
Publisher: Springer Nature
ISBN: 3031016688
Category : Technology & Engineering
Languages : en
Pages : 95

Book Description
Nanotechnology is an interdisciplinary field that is rapidly evolving and expanding. Significant advancements have been made in nanotechnology-related disciplines in the past few decades and continued growth and progression in the field are anticipated. Moreover, nanotechnology, omnipresent in innovation, has been applied to resolve critical challenges in nearly every field, especially those related to biological technologies and processes. This book, used as either a textbook for a short course or a reference book, provides state-of-the-art analysis of essential topics in nanotechnology for bioengineers studying and working in biotechnology, chemical/biochemical, pharmaceutical, biomedical, and other related fields. The book topics range from introduction to nanotechnology and nanofabrication to applications of nanotechnology in various biological fields. This book not only intends to introduce bioengineers to the amazing world of nanotechnology, but also inspires them to use nanotechnology to address some of the world's biggest challenges.

Biomedical Signals and Systems

Biomedical Signals and Systems PDF Author: Joseph Tranquillo
Publisher: Springer Nature
ISBN: 3031016599
Category : Technology & Engineering
Languages : en
Pages : 211

Book Description
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