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Author: C. A. Glasbey
Publisher:
Published: 1995-08-08
Total Pages: 248
ISBN-13:
DOWNLOAD EBOOKCovering the basics of quantitative image analysis - the extraction of information from data in the form of pictures - this study places special emphasis on methods relevant to environmental scientists. Practical examples from various fields are introduced to demonstrate applications.
Author: Kota Miura
Publisher: Springer Nature
Published: 2019-10-17
Total Pages: 178
ISBN-13: 3030223868
DOWNLOAD EBOOKThis Open Access textbook provides students and researchers in the life sciences with essential practical information on how to quantitatively analyze data images. It refrains from focusing on theory, and instead uses practical examples and step-by step protocols to familiarize readers with the most commonly used image processing and analysis platforms such as ImageJ, MatLab and Python. Besides gaining knowhow on algorithm usage, readers will learn how to create an analysis pipeline by scripting language; these skills are important in order to document reproducible image analysis workflows. The textbook is chiefly intended for advanced undergraduates in the life sciences and biomedicine without a theoretical background in data analysis, as well as for postdocs, staff scientists and faculty members who need to perform regular quantitative analyses of microscopy images.
Author:
Publisher: Academic Press
Published: 2014-06-25
Total Pages: 609
ISBN-13: 0124202012
DOWNLOAD EBOOKThis new volume, number 123, of Methods in Cell Biology looks at methods for quantitative imaging in cell biology. It covers both theoretical and practical aspects of using optical fluorescence microscopy and image analysis techniques for quantitative applications. The introductory chapters cover fundamental concepts and techniques important for obtaining accurate and precise quantitative data from imaging systems. These chapters address how choice of microscope, fluorophores, and digital detector impact the quality of quantitative data, and include step-by-step protocols for capturing and analyzing quantitative images. Common quantitative applications, including co-localization, ratiometric imaging, and counting molecules, are covered in detail. Practical chapters cover topics critical to getting the most out of your imaging system, from microscope maintenance to creating standardized samples for measuring resolution. Later chapters cover recent advances in quantitative imaging techniques, including super-resolution and light sheet microscopy. With cutting-edge material, this comprehensive collection is intended to guide researchers for years to come. Covers sections on model systems and functional studies, imaging-based approaches and emerging studies Chapters are written by experts in the field Cutting-edge material
Author: Spencer L. Shorte
Publisher: Springer Science & Business Media
Published: 2007-09-12
Total Pages: 457
ISBN-13: 354071331X
DOWNLOAD EBOOKThis book offers a comprehensive selection of essays by leading experts, which covers all aspects of modern imaging, from its application and up-scaling to its development. The chapter content ranges from the basics to the most complex overview of method and protocols. There is ample practical and detailed "how-to" content on important, but rarely addressed topics. This first edition features all-colour-plate chapters, licensed software and a unique, continuously updated website forum.
Author: Gobert Lee
Publisher: Springer Nature
Published: 2020-02-06
Total Pages: 184
ISBN-13: 3030331288
DOWNLOAD EBOOKThis book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.
Author: Sujata Dash
Publisher: John Wiley & Sons
Published: 2021-08-24
Total Pages: 450
ISBN-13: 111971124X
DOWNLOAD EBOOKBIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.
Author: S Dutta Gupta
Publisher: CRC Press
Published: 2014-09-17
Total Pages: 410
ISBN-13: 1466583029
DOWNLOAD EBOOKThe application of imaging techniques in plant and agricultural sciences had previously been confined to images obtained through remote sensing techniques. Technological advancements now allow image analysis for the nondestructive and objective evaluation of biological objects. This has opened a new window in the field of plant science. Plant Image
Author: Alejandro Frangi
Publisher: Academic Press
Published: 2023-09-20
Total Pages: 700
ISBN-13: 0128136588
DOWNLOAD EBOOKMedical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC. - An authoritative presentation of key concepts and methods from experts in the field - Sections clearly explaining key methodological principles within relevant medical applications - Self-contained chapters enable the text to be used on courses with differing structures - A representative selection of modern topics and techniques in medical image computing - Focus on medical image computing as an enabling technology to tackle unmet clinical needs - Presentation of traditional and machine learning approaches to medical image computing
Author: Ch.W. Sensen
Publisher: Springer Science & Business Media
Published: 2008-12-03
Total Pages: 447
ISBN-13: 3540689931
DOWNLOAD EBOOKA picture says more than a thousand words. This is something that we all know to be true. Imaging has been important since the early days of medicine and bi- ogy, as seen in the anatomical studies of Leonardo Da Vinci or Andreas Vesalius. More than 100 years ago, the ?rst noninvasive imaging technologies, such as K- rad Roentgen’s X-ray technology,were applied to the medical ?eld—and while still crude—revolutionized medical diagnosis. Today, every patient will be exposed to some kind of advanced imaging technology such as medical resonance imaging, computed tomography or four-dimensional ultrasound during their lifetime. Many diseases, such as brain tumors, are initially diagnosed solely by imaging, and most of the surgical planning relies on the patient imagery. 4D ultrasound is available to expecting parents who wish to create unique early memories of the new baby, and it may soon be used for the morphometric diagnosis of malformations that may one day be treatable—inutero! Light and electron microscopy are unequal brethren, which have contributed to most of our knowledge about the existence and organization of cells, tissues and microorganisms. Every student of biology or medicine is introduced to the fascinating images of the microcosm. New advances have converted these im- ing technologies, which were considered by many to be antiquated, into powerful tools for research in systems biology and related ?elds.
Author: Omer Demirkaya
Publisher: CRC Press
Published: 2008-12-22
Total Pages: 446
ISBN-13: 1420008935
DOWNLOAD EBOOKImage Processing with MATLAB: Applications in Medicine and Biology explains complex, theory-laden topics in image processing through examples and MATLAB algorithms. It describes classical as well emerging areas in image processing and analysis. Providing many unique MATLAB codes and functions throughout, the book covers the theory of probability an
