A Survey Of Ultrasonography Breast Cancer Image Segmentation Techniques PDF Download
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Author: Jwan Najeeb Saeed
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 14
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Book Description
The most common cause of death among women globally is breast cancer. One of the key strategies to reduce mortality associated with breast cancer is to develop effective early detection techniques. The segmentation of breast ultrasound (BUS) image in Computer-Aided Diagnosis (CAD) systems is critical and challenging. Image segmentation aims to represent the image in a simplified and more meaningful way while retaining crucial features for easier analysis.
Author: Jwan Najeeb Saeed
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 14
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Book Description
The most common cause of death among women globally is breast cancer. One of the key strategies to reduce mortality associated with breast cancer is to develop effective early detection techniques. The segmentation of breast ultrasound (BUS) image in Computer-Aided Diagnosis (CAD) systems is critical and challenging. Image segmentation aims to represent the image in a simplified and more meaningful way while retaining crucial features for easier analysis.
Author: Min Xian
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 71
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Book Description
Breast cancer is one of the leading causes of cancer death among women worldwide. In clinical routine, automatic breast ultrasound (BUS) image segmentation is very challenging and essential for cancer diagnosis and treatment planning.
Author: H.D.Cheng
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 19
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Book Description
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.
Author: Min Xian
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 9
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Book Description
Breast ultrasound (BUS) image segmentation is challenging and critical for BUS Computer-Aided Diagnosis (CAD) systems. Many BUS segmentation approaches have been proposed in the last two decades, but the performances of most approaches have been assessed using relatively small private datasets with different quantitative metrics, which result in discrepancy in performance comparison.
Author: YaozhongLuo
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 18
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Book Description
Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US) image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309075505
Category : Medical
Languages : en
Pages : 34
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Book Description
X-ray mammography screening is the current mainstay for early breast cancer detection. It has been proven to detect breast cancer at an earlier stage and to reduce the number of women dying from the disease. However, it has a number of limitations. These current limitations in early breast cancer detection technology are driving a surge of new technological developments, from modifications of x-ray mammography such as computer programs that can indicate suspicious areas, to newer methods of detection such as magnetic resonance imaging (MRI) or biochemical tests on breast fluids. To explore the merits and drawbacks of these new breast cancer detection techniques, the Institute of Medicine of the National Academy of Sciences convened a committee of experts. During its year of operation, the committee examined the peer-reviewed literature, consulted with other experts in the field, and held two public workshops. In addition to identifying promising new technologies for early detection, the committee explored potential barriers that might prevent the development of new detection methods and their common usage. Such barriers could include lack of funding from agencies that support research and lack of investment in the commercial sector; complicated, inconsistent, or unpredictable federal regulations; inadequate insurance reimbursement; and limited access to or unacceptability of breast cancer detection technology for women and their doctors. Based on the findings of their study, the committee prepared a report entitled Mammography and Beyond: Developing Technology for Early Detection of Breast Cancer, which was published in the spring of 2001. This is a non-technical summary of that report.
Author: Abhishek Swaroop
Publisher: Springer Nature
ISBN: 9819937167
Category : Technology & Engineering
Languages : en
Pages : 937
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Book Description
This book features high-quality research papers presented at Fourth Doctoral Symposium on Computational Intelligence (DoSCI 2023), organized by Institute of Engineering and Technology (IET), AKTU, Lucknow, India, on March 3, 2023. This book discusses the topics such as computational intelligence, artificial intelligence, deep learning, evolutionary algorithms, swarm intelligence, fuzzy sets and vague sets, rough set theoretic approaches, quantum-inspired computational intelligence, hybrid computational intelligence, machine learning, computer vision, soft computing, distributed computing, parallel and grid computing, cloud computing, high-performance computing, biomedical computing, and decision support and decision making
Author: Raj, Alex Noel Joseph
Publisher: IGI Global
ISBN: 1799866920
Category : Computers
Languages : en
Pages : 381
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Book Description
Recent advancements in imaging techniques and image analysis has broadened the horizons for their applications in various domains. Image analysis has become an influential technique in medical image analysis, optical character recognition, geology, remote sensing, and more. However, analysis of images under constrained and unconstrained environments require efficient representation of the data and complex models for accurate interpretation and classification of data. Deep learning methods, with their hierarchical/multilayered architecture, allow the systems to learn complex mathematical models to provide improved performance in the required task. The Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments provides a critical examination of the latest advancements, developments, methods, systems, futuristic approaches, and algorithms for image analysis and addresses its challenges. Highlighting concepts, methods, and tools including convolutional neural networks, edge enhancement, image segmentation, machine learning, and image processing, the book is an essential and comprehensive reference work for engineers, academicians, researchers, and students.
Author: Steve H. Parker
Publisher: Raven Press (ID)
ISBN:
Category : Medical
Languages : en
Pages : 200
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Book Description
A comprehensive treatment of large-core needle biopsy, a new technique for the early diagnosis of breast cancer. Considers the history of the technique, equipment, the principles of stereotactic mammography, and several procedures using ultrasound. The roles and perspectives of the pathologist, the nurse, and the technologist are delineated, with the emphasis on teamwork. Also evaluates fine-needle aspiration biopsy. Addressed to radiologists. Highly illustrated. Annotation copyright by Book News, Inc., Portland, OR
Author: Jasjit S. Suri
Publisher: Artech House
ISBN: 1596931450
Category : Medical
Languages : en
Pages : 449
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Book Description
This groundbreaking resource offers you exclusive coverage of the latest techniques in diagnostic and therapeutic 3-D ultrasound imaging instrumentation and techniques. Providing a solid overview of potential applications in clinical practice, you find need-to-know details on major diseases, including vascular diseases, breast cancer, cardiac abnormalities and prostate cancer.
