Download or read book Detection Systems in Lung Cancer and Imaging Volume 1 written by Ayman El-Baz and published by IOP Publishing Limited. This book was released on 2022-01-20 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on major trends and challenges in the detection of lung cancer, presenting work aimed at identifying new techniques and their use in biomedical analysis. This volume covers recent advancements in lung cancer and imaging detection and classification, examining the main applications of Computer aided diagnosis (CAD) relating to lung cancer: lung nodule segmentation, lung nodule classification, and Big Data in lung cancer. Ideal for academics working in lung cancer, data-mining, machine learning, deep learning and reinforcement learning, as well as industry professionals working in the areas of healthcare, lung cancer imaging, machine learning, deep learning and reinforcement learning, this edited collection comprises an essential reference for researchers at the forefront of the field, and provides a high-level entry point for more advanced students. Key Features:  -Unique focus on advance work in detection system and classification systems. -An updated reference for lung cancer detection via imaging. -Focus on progressive deep learning and machine learning applications for more effective detection.

Download or read book Detection Systems in Lung Cancer and Imaging written by Ayman El-Baz and published by IOP ebooks. This book was released on 2022-05-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Lung Imaging and CADx written by Ayman El-Baz and published by CRC Press. This book was released on 2019-04-24 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great clinical importance and can significantly increase the patient's chance for survival. For this reason, CAD systems for lung cancer have been investigated in a large number of research studies. A typical CAD system for lung cancer diagnosis is composed of four main processing steps: segmentation of the lung fields, detection of nodules inside the lung fields, segmentation of the detected nodules, and diagnosis of the nodules as benign or malignant. This book overviews the current state-of-the-art techniques that have been developed to implement each of these CAD processing steps. Overviews the latest state-of-the-art diagnostic CAD systems for lung cancer imaging and diagnosis Offers detailed coverage of 3D and 4D image segmentation Illustrates unique fully automated detection systems coupled with 4D Computed Tomography (CT) Written by authors who are world-class researchers in the biomedical imaging sciences Includes extensive references at the end of each chapter to enhance further study Ayman El-Baz is a professor, university scholar, and chair of the Bioengineering Department at the University of Louisville, Louisville, Kentucky. He earned his bachelor’s and master’s degrees in electrical engineering in 1997 and 2001, respectively. He earned his doctoral degree in electrical engineering from the University of Louisville in 2006. In 2009, he was named a Coulter Fellow for his contributions to the field of biomedical translational research. He has 17 years of hands-on experience in the fields of bio-imaging modeling and noninvasive computer-assisted diagnosis systems. He has authored or coauthored more than 500 technical articles (132 journals, 23 books, 57 book chapters, 211 refereed-conference papers, 137 abstracts, and 27 U.S. patents and disclosures). Jasjit S. Suri is an innovator, scientist, a visionary, an industrialist, and an internationally known world leader in biomedical engineering. He has spent over 25 years in the field of biomedical engineering/devices and its management. He received his doctorate from the University of Washington, Seattle, and his business management sciences degree from Weatherhead School of Management, Case Western Reserve University, Cleveland, Ohio. He was awarded the President’s Gold Medal in 1980 and named a Fellow of the American Institute of Medical and Biological Engineering for his outstanding contributions in 2004. In 2018, he was awarded the Marquis Life Time Achievement Award for his outstanding contributions and dedication to medical imaging and its management.

Download or read book Lung Cancer and Imaging written by Ayman El-Baz and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lung cancer is one of the most common cancers in both men and women worldwide. Early diagnosis of lung cancer can significantly increase the chances of a patient's survival, yet early detection has historically been difficult. As a result, there has been a great deal of progress in the development of accurate and fast diagnostic tools in recent years. Lung Cancer and Imaging provides an introduction to both the methods currently used in lung cancer diagnosis and the promising new techniques that are emerging. Areas covered include the major trends and challenges in lung cancer detection and diagnosis, classification of cancer types, lung feature extraction in joint PET/CT images, and algorithms in the area of low dosage CT lung cancer images. Part of Series in Physics and Engineering in Medicine and Biology.

Download or read book Lung Cancer written by Barbara Driscoll and published by Springer Science & Business Media. This book was released on 2003 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leading physician scientists and noted researchers review novel methods for determining the etiology of a variety of lung cancers and present readily reproducible techniques for examining the associated multitude of genetic abnormalities. The methods make it possible to detect these alterations at the cellular, DNA, and protein levels, to study the development of lung cancer in vitro and in vivo-either in situ or in the form of metastases, and to test targeted therapies with detailed model systems. An animal models section gives explicit instructions for setting up and testing these systems, which are rarely described in the literature.

Download or read book Lung Imaging and Computer Aided Diagnosis written by Ayman El-Baz and published by CRC Press. This book was released on 2011-08-23 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lung cancer remains the leading cause of cancer-related deaths worldwide. Early diagnosis can improve the effectiveness of treatment and increase a patient’s chances of survival. Thus, there is an urgent need for new technology to diagnose small, malignant lung nodules early as well as large nodules located away from large diameter airways because the current technology—namely, needle biopsy and bronchoscopy—fail to diagnose those cases. However, the analysis of small, indeterminate lung masses is fraught with many technical difficulties. Often patients must be followed for years with serial CT scans in order to establish a diagnosis, but inter-scan variability, slice selection artifacts, differences in degree of inspiration, and scan angles can make comparing serial scans unreliable. Lung Imaging and Computer Aided Diagnosis brings together researchers in pulmonary image analysis to present state-of-the-art image processing techniques for detecting and diagnosing lung cancer at an early stage. The book addresses variables and discrepancies in scans and proposes ways of evaluating small lung masses more consistently to allow for more accurate measurement of growth rates and analysis of shape and appearance of the detected lung nodules. Dealing with all aspects of image analysis of the data, this book examines: Lung segmentation Nodule segmentation Vessels segmentation Airways segmentation Lung registration Detection of lung nodules Diagnosis of detected lung nodules Shape and appearance analysis of lung nodules Contributors also explore the effective use of these methodologies for diagnosis and therapy in clinical applications. Arguably the first book of its kind to address and evaluate image-based diagnostic approaches for the early diagnosis of lung cancer, Lung Imaging and Computer Aided Diagnosis constitutes a valuable resource for biomedical engineers, researchers, and clinicians in lung disease imaging.

Download or read book Imaging of Lung Cancer An Issue of Radiologic Clinics of North America E Book written by Ella A. Kazerooni and published by Elsevier Health Sciences. This book was released on 2012-09-30 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This issue gives the general radiologist a solid overview of lung cancer imaging techniques. CT screening for lung cancer is discussed, and the evaluation and management of indeterminate pulmonary nodules is reviewed. Revised TNM lung cancer staging, as well as the optimal imaging protocols for lung cancer staging (CT, MR and PET) are thoroughly examined. A multidisciplinary approach to tissue sampling and updated histopathologic classification of lung cancer are discussed. Image-guided ablative therapies for lung cancer are reviewed. Finally, future trends in lung cancer diagnosis and staging and genetics are reviewed, as well as novel biomarkers for lung cancer detection.

Download or read book Lung Cancer Imaging written by James G. Ravenel and published by Springer Science & Business Media. This book was released on 2013-06-22 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: While specialists often guide the care to lung cancer patients, it is often a general radiologist who is left to interpret studies that impact patient care and management. Lung Cancer Imaging provides a comprehensive guide to the diagnosis, staging and overview of the management of lung cancer relevant to practicing radiologists so that they can better understand the decision making issues and provide more directed and useful communication to the treating physicians. It Primary Care physicians will also find this book valuable to understand the relevant issues that they face when one of their patients is being treated for lung cancer.

Download or read book Machine Learning for Tomographic Imaging written by Ge Wang and published by Programme: Iop Expanding Physi. This book was released on 2019-12-30 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning represents a paradigm shift in tomographic imaging, and image reconstruction is a new frontier of machine learning. This book will meet the needs of those who want to catch the wave of smart imaging. The book targets graduate students and researchers in the imaging community. Open network software, working datasets, and multimedia will be included. The first of its kind in the emerging field of deep reconstruction and deep imaging, Machine Learning for Tomographic Imaging presents the most essential elements, latest progresses and an in-depth perspective on this important topic.

Download or read book Cloud Computing in Medical Imaging written by Ayman El-Baz and published by CRC Press. This book was released on 2023-03-14 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today’s healthcare organizations must focus on a lot more than just the health of their clients. The infrastructure it takes to support clinical-care delivery continues to expand, with information technology being one of the most significant contributors to that growth. As companies have become more dependent on technology for their clinical, administrative, and financial functions, their IT departments and expenditures have had to scale quickly to keep up. However, as technology demands have increased, so have the options for reliable infrastructure for IT applications and data storage. The one that has taken center stage over the past few years is cloud computing. Healthcare researchers are moving their efforts to the cloud because they need adequate resources to process, store, exchange, and use large quantities of medical data. Cloud Computing in Medical Imaging covers the state-of-the-art techniques for cloud computing in medical imaging, healthcare technologies, and services. The book focuses on Machine-learning algorithms for health data security Fog computing in IoT-based health care Medical imaging and healthcare applications using fog IoT networks Diagnostic imaging and associated services Image steganography for medical informatics This book aims to help advance scientific research within the broad field of cloud computing in medical imaging, healthcare technologies, and services. It focuses on major trends and challenges in this area and presents work aimed to identify new techniques and their use in biomedical analysis.

Download or read book Big Data in Multimodal Medical Imaging written by Ayman El-Baz and published by CRC Press. This book was released on 2019-11-05 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems.

Download or read book Lung Cancer and Imaging written by Aymen El-Baz and published by . This book was released on 2019-12-30 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lung cancer is one of the most common cancers in both men and women worldwide. Early diagnosis of lung cancer can significantly increase the chances of a patient's survival, yet early detection has historically been difficult. As a result, there has been a great deal of progress in the development of accurate and fast diagnostic tools in recent years. Lung Cancer and Imaging provides an introduction to both the methods currently used in lung cancer diagnosis and the promising new techniques that are emerging. Areas covered include the major trends and challenges in lung cancer detection and diagnosis, classification of cancer types, lung feature extraction in joint PET/CT images, and algorithms in the area of low dosage CT lung cancer images.

Download or read book Artificial Intelligence and Machine Learning in 2D 3D Medical Image Processing written by Rohit Raja and published by CRC Press. This book was released on 2020-12-23 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field

Download or read book Handbook of Texture Analysis written by Ayman El-Baz and published by CRC Press. This book was released on 2024-06-21 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book: Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methods Covers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformation Describes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentation Is aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering This is an essential reference for those looking to advance their understanding in this applied and emergent field.

Download or read book Lung Cancer written by Pedro G. Santiago-Cardona and published by Humana. This book was released on 2021-04-09 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This detailed book serves as a laboratory manual containing vital protocols and in-depth discussion involving commonly used experimental approaches for the characterization of several aspects of lung tumor biology. Beginning with an extensive section on biomarker detection, the volume continues with chapters on the genetic and molecular characterization of lung cancer biological samples as well as protocols for the generation of research tools and pre-clinical lung cancer models. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Lung Cancer: Methods and Protocols provides a global perspective of research efforts related to lung cancer, while allowing researchers to experimentally probe the different aspects of lung cancer research, including the experimentally relevant tests used in the establishment of lung cancer diagnosis and prognosis, in their laboratories.

Download or read book Progress in Advanced Computing and Intelligent Engineering written by Bibudhendu Pati and published by Springer. This book was released on 2018-12-17 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book gathers high-quality research papers presented at the International Conference on Advanced Computing and Intelligent Engineering (ICACIE 2017). It includes technical sections describing progress in the fields of advanced computing and intelligent engineering, and is primarily intended for postgraduate students and researchers working in Computer Science and Engineering. However, researchers working in Electronics will also find the book useful, as it addresses hardware technologies and next-gen communication technologies.

Download or read book Neural Engineering Techniques for Autism Spectrum Disorder written by Ayman S. El-Baz and published by Academic Press. This book was released on 2021-07-16 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Engineering for Autism Spectrum Disorder, Volume One: Imaging and Signal Analysis Techniques presents the latest advances in neural engineering and biomedical engineering as applied to the clinical diagnosis and treatment of Autism Spectrum Disorder (ASD). Advances in the role of neuroimaging, infrared spectroscopy, sMRI, fMRI, DTI, social behaviors and suitable data analytics useful for clinical diagnosis and research applications for Autism Spectrum Disorder are covered, including relevant case studies. The application of brain signal evaluation, EEG analytics, feature selection, and analysis of blood oxygen level-dependent (BOLD) signals are presented for detection and estimation of the degree of ASD. Presents applications of Neural Engineering and other Machine Learning techniques for the diagnosis of Autism Spectrum Disorder (ASD) Includes in-depth technical coverage of imaging and signal analysis techniques, including coverage of functional MRI, neuroimaging, infrared spectroscopy, sMRI, fMRI, DTI, and neuroanatomy of autism Covers Signal Analysis for the detection and estimation of Autism Spectrum Disorder (ASD), including brain signal analysis, EEG analytics, feature selection, and analysis of blood oxygen level-dependent (BOLD) signals for ASD Written to help engineers, computer scientists, researchers and clinicians understand the technology and applications of Neural Engineering for the detection and diagnosis of Autism Spectrum Disorder (ASD)