Classification Of Mammogram Images
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Classification Of Mammogram Images
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Author : Supriya Salve
language : en
Publisher: diplom.de
Release Date : 2017-03-23
Classification Of Mammogram Images written by Supriya Salve and has been published by diplom.de this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-23 with Medical categories.
Breast cancer is the most common type of cancer in women, which also causes the most cancer deaths among them today. Mammography is the only reliable method to detect breast cancer in the early stage among all diagnostic methods available currently. Breast cancer can occur in both men and women and is defined as an abnormal growth of cells in the breast that multiply uncontrollably. The main factors which cause breast cancer are either hormonal or genetic. Masses are quite subtle, and have many shapes such as circumscribed, speculated or ill-defined. These tumors can be either benign or malignant. Computer-aided methods are powerful tools to assist the medical staff in hospitals and lead to better and more accurate diagnosis. The main objective of this research is to develop a Computer Aided Diagnosis (CAD) system for finding the tumors in the mammographic images and classifying the tumors as benign or malignant. There are five main phases involved in the proposed CAD system: image pre-processing, extraction of features from mammographic images using Gabor Wavelet and Discrete Wavelet Transform (DWT), dimensionality reduction using Principal Component Analysis (PCA) and classification using Support Vector Machine (SVM) classifier.
Computerized Analysis Of Mammographic Images For Detection And Characterization Of Breast Cancer
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Author : Paola Casti
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2017-07-06
Computerized Analysis Of Mammographic Images For Detection And Characterization Of Breast Cancer written by Paola Casti and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-06 with Technology & Engineering categories.
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.
Emerging Trends In Intelligent Computing And Informatics
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Author : Faisal Saeed
language : en
Publisher: Springer Nature
Release Date : 2019-11-01
Emerging Trends In Intelligent Computing And Informatics written by Faisal Saeed and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-01 with Technology & Engineering categories.
This book presents the proceedings of the 4th International Conference of Reliable Information and Communication Technology 2019 (IRICT 2019), which was held in Pulai Springs Resort, Johor, Malaysia, on September 22–23, 2019. Featuring 109 papers, the book covers hot topics such as artificial intelligence and soft computing, data science and big data analytics, internet of things (IoT), intelligent communication systems, advances in information security, advances in information systems and software engineering.
Automated Breast Cancer Detection And Classification Using Ultrasound Images A Survey
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Author : H.D.Cheng
language : en
Publisher: Infinite Study
Release Date :
Automated Breast Cancer Detection And Classification Using Ultrasound Images A Survey written by H.D.Cheng and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Breast cancer is the second leading cause of death for women all over the world. Since the cause of the disease remains unknown, early detection and diagnosis is the key for breast cancer control, and it can increase the success of treatment, save lives and reduce cost. Ultrasound imaging is one of the most frequently used diagnosis tools to detect and classify abnormalities of the breast.
Breast Cancer Diagnostic Imaging And Therapeutic Guidance
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Author : Uwe Fischer
language : en
Publisher: Thieme
Release Date : 2017-12-13
Breast Cancer Diagnostic Imaging And Therapeutic Guidance written by Uwe Fischer and has been published by Thieme this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-13 with Medical categories.
Breast Cancer: Diagnostic Imaging and Therapeutic Guidance provides a concise, practical, and practice-based source of up-to-date diagnostic and therapeutic information for the general radiologist. In the diagnostic phase of evaluating breast disorders, the overriding consideration in the examination and assessment is to reduce false diagnoses to the absolute minimum-a principle wholly in the interests of the patient. The particular diagnostic pathway chosen will depend on the highly variable individual presentations and the associated findings. A major focus of the book is the comparative value of the various diagnostic imaging modalities. As well as discussing conventional mammography and adjunct modalities such as breast ultrasound and galactography, the text also showcases the superior utility of contrast-enhanced magnetic resonance imaging in providing the highest rate of detection of cancers at any stage. As well as radiological diagnosis, sections written by top specialists cover the interventional procedures for obtaining biopsies and also the surgical and medical therapy of breast carcinoma. Key Features: Combined authors' experience of more than 100 years provides this work with great depth and expertise. Richly illustrated with almost 600 images, including full color histology, patient photographs, and hundreds of radiological studies. BI-RADS classification for mammography, breast ultrasound, and breast MRI. Adjunct topics covered include screening and staging; lymph nodes; breast reconstruction; chemotherapy, also with respect to endocrine-active tumors; radiation therapy; tumors of the male breast; logistics in the breast care center; and psychosocial care. Breast Cancer: Diagnostic Imaging and Therapeutic Guidance is certain to prove an invaluable tool for all general radiologists involved in the evaluation and treatment of patients with breast cancer.
Applied Nature Inspired Computing Algorithms And Case Studies
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Author : Nilanjan Dey
language : en
Publisher: Springer
Release Date : 2019-08-10
Applied Nature Inspired Computing Algorithms And Case Studies written by Nilanjan Dey and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-10 with Technology & Engineering categories.
This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.
Fractal Analysis Of Breast Masses In Mammograms
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Author : Thanh Cabral
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Fractal Analysis Of Breast Masses In Mammograms written by Thanh Cabral and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Technology & Engineering categories.
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
Breast Cancer Early Detection With Mammography
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Author : Laszlo Tabar
language : en
Publisher: Thieme
Release Date : 2011-01-01
Breast Cancer Early Detection With Mammography written by Laszlo Tabar and has been published by Thieme this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-01 with Medical categories.
Praise for this book:This book should be required reading for the multidisciplinary team of physicians and health care professionals who use mammography for breast cancer detection and treatment...a landmark volume in the field of mammography.--RadiologyInternationally renowned breast cancer imagers, Laszlo Tabar and Peter B. Dean, and the eminent breast pathologist, Tibor Tot, distill decades of clinical expertise in this new volume covering the most frequently occurring malignant type of calcifications: the pleomorphic, crushed stone-like calcifications. The book presents a systematic approach to using mammographic features to distinguish different subtypes of breast diseases originating within the terminal ductal lobular unit (TDLU). More than 800 images demonstrate abnormal findings with superb clarity, providing a state-of-the-art visual reference for interpreting mammograms in the clinical setting. Features: Concise descriptions of mammographic and MRI findings correlated with high-quality histopathologic images to provide a reliable guide for accurate diagnosis and differential diagnosis, as well as prognostic classification Extensive coverage of all aspects of the benign differential diagnostic counterparts of pleomorphic calcifications, including fibrocystic change, fibroadenoma, and papilloma Straightforward discussion of terminology based on a thorough analysis of subgross anatomy, 3D histologic features, and long-term disease outcomes 3D viewing glasses enclosed in the book for perceiving specially marked images in their true three-dimensional form This book is ideal for all breast imagers and breast pathologists, as well as for surgeons and oncologists specializing in breast diseases. For the radiologist, this book is an indispensable reference for harnessing the power of mammography to detect breast cancer at the earliest stages possible.
Fractal Analysis Of Breast Masses In Mammograms
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Author : Thanh M. Cabral
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2012-10-01
Fractal Analysis Of Breast Masses In Mammograms written by Thanh M. Cabral and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-01 with Technology & Engineering categories.
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
Second International Conference On Image Processing And Capsule Networks
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Author : Joy Iong-Zong Chen
language : en
Publisher: Springer Nature
Release Date : 2021-09-09
Second International Conference On Image Processing And Capsule Networks written by Joy Iong-Zong Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-09 with Technology & Engineering categories.
This book includes the papers presented in 2nd International Conference on Image Processing and Capsule Networks [ICIPCN 2021]. In this digital era, image processing plays a significant role in wide range of real-time applications like sensing, automation, health care, industries etc. Today, with many technological advances, many state-of-the-art techniques are integrated with image processing domain to enhance its adaptiveness, reliability, accuracy and efficiency. With the advent of intelligent technologies like machine learning especially deep learning, the imaging system can make decisions more and more accurately. Moreover, the application of deep learning will also help to identify the hidden information in volumetric images. Nevertheless, capsule network, a type of deep neural network, is revolutionizing the image processing domain; it is still in a research and development phase. In this perspective, this book includes the state-of-the-art research works that integrate intelligent techniques with image processing models, and also, it reports the recent advancements in image processing techniques. Also, this book includes the novel tools and techniques for deploying real-time image processing applications. The chapters will briefly discuss about the intelligent image processing technologies, which leverage an authoritative and detailed representation by delivering an enhanced image and video recognition and adaptive processing mechanisms, which may clearly define the image and the family of image processing techniques and applications that are closely related to the humanistic way of thinking.