Manoj Diwakar (83 results)

Paperback. Condition: Brand New. 76 pages. 8.66x5.91x0.18 inches. In Stock.

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Taschenbuch. Condition: Neu. Computed Tomography Image Denoising | Techniques and Applications | Manoj Diwakar | Taschenbuch | 108 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139584819 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

Hardcover. Condition: new. Hardcover. This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction. The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: New.

Hardcover. Condition: new. Hardcover. This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction. The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Hardcover. Condition: new. Hardcover. This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction. The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

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Condition: New. Dr. Kapil Joshi is an Associate Professor in the Department of Computer Science &amp Engineering at the Uttaranchal Institute of Technology (UIT), Uttaranchal University, Dehradun, India. He holds a Ph.D. in Computer Science &amp Engin.

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Hardback. Condition: New. This volume documents the contributions presented at The ICRTMPCS II International Conference on Advances in Mathematical and Computational Sciences. Entries focus on modern trends and techniques in branches of pure and applied mathematics, statistics, and computer science. Highlighting applications in coding theory, cryptography, graph theory, fuzzy theory, variance analysis, data analysis, and sampling theory. …

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Taschenbuch. Condition: Neu. Healthcare Industry Assessment: Analyzing Risks, Security, and Reliability | Pardeep Kumar (u. a.) | Taschenbuch | Engineering Cyber-Physical Systems and Critical Infrastructures | xii | Englisch | 2025 | Springer | EAN 9783031654367 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Hardcover. Condition: Brand New. 308 pages. 6.38x0.91x9.45 inches. In Stock.

Hardcover. Condition: new. Hardcover. This book caters to a wide range of readers, including professionals in the healthcare and IT sectors, as well as security practitioners. This resource provides valuable perspectives on the risks and difficulties currently faced by the healthcare industry and presents practical recommendations for effectively managing these risks and enhancing security and reliability. This book is beneficial for anyone seeking to enhance their understanding of the risks, security, and reliability challenges encountered by the healthcare industry. The provided information offers a comprehensive overview of the issues at hand and provides recommendations for mitigating risks and enhancing security and stability. This resource provides valuable perspectives on the risks and difficulties currently faced by the healthcare industry and presents practical recommendations for effectively managing these risks and enhancing security and reliability. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction.The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset. …

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Hardcover. Condition: New. The series is aimed specifically at publishing peer-reviewed reviews and contributions presented at conferences, workshops, and international seminars as well as edited volumes commemorating and honoring significant achievements by mathematicians. This c.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Hardcover. Condition: new. Hardcover. This book offers a comprehensive study of medical image processing, with an emphasis on methods to enhance the accuracy and readability of medical images for diagnosis and therapy. Its main goals are to improve the visual clarity of images by sharpening details, lowering noise, and altering contrast to better visualize subtle elements. Also, it guarantees that anatomical features are accurately represented by correcting distortions, artefacts, and defects resulting from capture or transmission. Reconstruction is the main topic, including how to mix data from different modalities (such as CT and MRI) to build a more complete perspective or recreate missing or incomplete data from fragmented images. This book covers a wide range of topics, including deep learning methodologies, image processing methods, clinical applications, evaluation, and validation. The goal of the book is to provide readers a thorough understanding of medical image processing methods for enhancing, restoring, and reconstructing medical images. It describes the different algorithms theoretical foundations and real-world applications. It highlights the practical uses and promise of these methods for enhancing medical diagnosis and care. This book offers a comprehensive study of medical image processing, with an emphasis on methods to enhance the accuracy and readability of medical images for diagnosis and therapy. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

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