Artificial Intelligence in Label-free Microscopy PDF Download
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Author: Ata Mahjoubfar
Publisher: Springer
ISBN: 3319514482
Category : Technology & Engineering
Languages : en
Pages : 151
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Book Description
This book introduces time-stretch quantitative phase imaging (TS-QPI), a high-throughput label-free imaging flow cytometer developed for big data acquisition and analysis in phenotypic screening. TS-QPI is able to capture quantitative optical phase and intensity images simultaneously, enabling high-content cell analysis, cancer diagnostics, personalized genomics, and drug development. The authors also demonstrate a complete machine learning pipeline that performs optical phase measurement, image processing, feature extraction, and classification, enabling high-throughput quantitative imaging that achieves record high accuracy in label -free cellular phenotypic screening and opens up a new path to data-driven diagnosis.
Author: Ata Mahjoubfar
Publisher: Springer
ISBN: 3319514482
Category : Technology & Engineering
Languages : en
Pages : 151
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Book Description
This book introduces time-stretch quantitative phase imaging (TS-QPI), a high-throughput label-free imaging flow cytometer developed for big data acquisition and analysis in phenotypic screening. TS-QPI is able to capture quantitative optical phase and intensity images simultaneously, enabling high-content cell analysis, cancer diagnostics, personalized genomics, and drug development. The authors also demonstrate a complete machine learning pipeline that performs optical phase measurement, image processing, feature extraction, and classification, enabling high-throughput quantitative imaging that achieves record high accuracy in label -free cellular phenotypic screening and opens up a new path to data-driven diagnosis.
Author: Ankur Gogoi
Publisher: Springer Nature
ISBN: 9819753457
Category :
Languages : en
Pages : 359
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Book Description
Author: Vasily Astratov
Publisher: Springer Nature
ISBN: 3030217221
Category : Science
Languages : en
Pages : 498
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Book Description
This book presents the advances in super-resolution microscopy in physics and biomedical optics for nanoscale imaging. In the last decade, super-resolved fluorescence imaging has opened new horizons in improving the resolution of optical microscopes far beyond the classical diffraction limit, leading to the Nobel Prize in Chemistry in 2014. This book represents the first comprehensive review of a different type of super-resolved microscopy, which does not rely on using fluorescent markers. Such label-free super-resolution microscopy enables potentially even broader applications in life sciences and nanoscale imaging, but is much more challenging and it is based on different physical concepts and approaches. A unique feature of this book is that it combines insights into mechanisms of label-free super-resolution with a vast range of applications from fast imaging of living cells to inorganic nanostructures. This book can be used by researchers in biological and medical physics. Due to its logically organizational structure, it can be also used as a teaching tool in graduate and upper-division undergraduate-level courses devoted to super-resolved microscopy, nanoscale imaging, microscopy instrumentation, and biomedical imaging.
Author: Xunbin Wei
Publisher: Springer Nature
ISBN: 9811576270
Category : Medical
Languages : en
Pages : 309
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Book Description
The book introduces readers to the basic principle of optical imaging technologies. Focusing on human disease diagnostics using optical imaging methods, it provides essential information for researchers in various fields and discusses the latest trends in optical imaging. In recent decades, there has been a huge increase in imaging technologies and their applications in human diseases diagnostics, including magnetic resonance imaging, x-ray computed tomography, and nuclear tomographic imaging. This book promotes further developments to extend optical imaging to a wider range of disease diagnostics. It is a valuable resource for researchers and students in the field of biomedical optics, as well as for clinicians.
Author: Inkyu Moon
Publisher: John Wiley & Sons
ISBN: 0470647507
Category : Technology & Engineering
Languages : en
Pages : 341
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Book Description
Artificial Intelligence in Digital Holographic Imaging Technical Basis and Biomedical Applications An eye-opening discussion of 3D optical sensing, imaging, analysis, and pattern recognition Artificial intelligence (AI) has made great progress in recent years. Digital holographic imaging has recently emerged as a powerful new technique well suited to explore cell structure and dynamics with a nanometric axial sensitivity and the ability to identify new cellular biomarkers. By combining digital holography with AI technology, including recent deep learning approaches, this system can achieve a record-high accuracy in non-invasive, label-free cellular phenotypic screening. It opens up a new path to data-driven diagnosis. Artificial Intelligence in Digital Holographic Imaging introduces key concepts and algorithms of AI to show how to build intelligent holographic imaging systems drawing on techniques from artificial neural networks, convolutional neural networks, and generative adversarial network. Readers will be able to gain an understanding of the basics for implementing AI in holographic imaging system designs and connecting practical biomedical questions that arise from the use of digital holography with various AI algorithms in intelligence models. What’s Inside Introductory background on digital holography Key concepts of digital holographic imaging Deep-learning techniques for holographic imaging AI techniques in holographic image analysis Holographic image-classification models Automated phenotypic analysis of live cells For readers with various backgrounds, this book provides a detailed discussion of the use of intelligent holographic imaging system in biomedical fields with great potential for biomedical application.
Author: Chhavi Chauhan
Publisher: Elsevier
ISBN: 032395832X
Category : Science
Languages : en
Pages : 661
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Book Description
Artificial Intelligence in Pathology: Principles and Applications provides a strong foundation of core artificial intelligence principles and their applications in the field of digital pathology. This is a reference of current and emerging use of AI in digital pathology as well as the emerging utility of quantum artificial intelligence and neuromorphic computing in digital pathology. It is a must-have educational resource for lay public, researchers, academicians, practitioners, policymakers, key administrators, and vendors to stay current with the shifting landscapes within the emerging field of digital pathology. It is also of use to workers in other diagnostic imaging areas such as radiology. This resource covers various aspects of the use of AI in pathology, including but not limited to the basic principles, advanced applications, challenges in the development, deployment, adoption, and scalability of AI-based models in pathology, the innumerous benefits of applying and integrating AI in the practice of pathology, ethical considerations for the safe adoption and deployment of AI in pathology. - Discusses the evolution of machine learning in the field to provide a foundational background - Addresses challenges in the development, deployment and regulation of AI in anatomic pathology - Includes information on generative deep learning in digital pathology workflows - Provides current tools and future perspectives
Author: Erik R. Ranschaert
Publisher: Springer
ISBN: 3319948784
Category : Medical
Languages : en
Pages : 369
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Book Description
This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
Author: Deepak Gupta
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110668386
Category : Computers
Languages : en
Pages : 385
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Book Description
This book collects research works of data-driven medical diagnosis done via Artificial Intelligence based solutions, such as Machine Learning, Deep Learning and Intelligent Optimization. Physical devices powered with Artificial Intelligence are gaining importance in diagnosis and healthcare. Medical data from different sources can also be analyzed via Artificial Intelligence techniques for more effective results.
Author: Stanley Cohen
Publisher: Elsevier Health Sciences
ISBN: 0323675379
Category : Medical
Languages : en
Pages : 290
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Book Description
Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. - Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. - Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. - Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.
Author: Long Cheng
Publisher: Springer
ISBN: 303004212X
Category : Computers
Languages : en
Pages : 716
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Book Description
The seven-volume set of LNCS 11301-11307, constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The 4th volume, LNCS 11304, is organized in topical sections on feature selection, clustering, classification, and detection.
