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Based on the analytical methods and the computer programs presented in this book, all that may be needed to perform MRI tissue diagnosis is the availability of relaxometric data and simple computer program proficiency. These programs are easy to use, highly interactive and the data processing is fast and unambiguous. Laboratories (with or without sophisticated facilities) can perform computational magnetic resonance diagnosis with only T1 and T2 relaxation data. The results have motivated the use of data to produce data-driven predictions required for machine learning, artificial intelligence (AI) and deep learning for multidisciplinary and interdisciplinary research. Consequently, this book is intended to be very useful for students, scientists, engineers, the medial personnel and researchers who are interested in developing new concepts for deeper appreciation of computational magnetic Resonance Imaging for medical diagnosis, prognosis, therapy and management of tissue diseases.
Book Synopsis Computational Molecular Magnetic Resonance Imaging for Neuro-oncology by : Michael O. Dada
Download or read book Computational Molecular Magnetic Resonance Imaging for Neuro-oncology written by Michael O. Dada and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the analytical methods and the computer programs presented in this book, all that may be needed to perform MRI tissue diagnosis is the availability of relaxometric data and simple computer program proficiency. These programs are easy to use, highly interactive and the data processing is fast and unambiguous. Laboratories (with or without sophisticated facilities) can perform computational magnetic resonance diagnosis with only T1 and T2 relaxation data. The results have motivated the use of data to produce data-driven predictions required for machine learning, artificial intelligence (AI) and deep learning for multidisciplinary and interdisciplinary research. Consequently, this book is intended to be very useful for students, scientists, engineers, the medial personnel and researchers who are interested in developing new concepts for deeper appreciation of computational magnetic Resonance Imaging for medical diagnosis, prognosis, therapy and management of tissue diseases.
Based on the analytical methods and the computer programs presented in this book, all that may be needed to perform MRI tissue diagnosis is the availability of relaxometric data and simple computer program proficiency. These programs are easy to use, highly interactive and the data processing is fast and unambiguous. Laboratories (with or without sophisticated facilities) can perform computational magnetic resonance diagnosis with only T1 and T2 relaxation data. The results have motivated the use of data to produce data-driven predictions required for machine learning, artificial intelligence (AI) and deep learning for multidisciplinary and interdisciplinary research. Consequently, this book is intended to be very useful for students, scientists, engineers, the medical personnel and researchers who are interested in developing new concepts for deeper appreciation of computational magnetic resonance imaging for medical diagnosis, prognosis, therapy and management of tissue diseases.
Book Synopsis Computational Molecular Magnetic Resonance Imaging for Neuro-oncology by : Michael O. Dada
Download or read book Computational Molecular Magnetic Resonance Imaging for Neuro-oncology written by Michael O. Dada and published by Springer Nature. This book was released on 2021-07-31 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the analytical methods and the computer programs presented in this book, all that may be needed to perform MRI tissue diagnosis is the availability of relaxometric data and simple computer program proficiency. These programs are easy to use, highly interactive and the data processing is fast and unambiguous. Laboratories (with or without sophisticated facilities) can perform computational magnetic resonance diagnosis with only T1 and T2 relaxation data. The results have motivated the use of data to produce data-driven predictions required for machine learning, artificial intelligence (AI) and deep learning for multidisciplinary and interdisciplinary research. Consequently, this book is intended to be very useful for students, scientists, engineers, the medical personnel and researchers who are interested in developing new concepts for deeper appreciation of computational magnetic resonance imaging for medical diagnosis, prognosis, therapy and management of tissue diseases.
With treatment approaches and the field of neuro-oncology neuroimaging changing rapidly, this third edition of the Handbook of Neuro-Oncology Neuroimaging is very relevant to those in the field, providing a single-source, comprehensive, reference handbook of the most up-to-date clinical and technical information regarding the application of neuroimaging techniques to brain tumor and neuro-oncology patients. This new volume will have updates on all of the material from the second edition, and in addition features several new important chapters covering diverse topics such as imaging for the use of Laser Interstitial Thermal Therapy, advanced imaging techniques in radiation therapy, therapeutic treatment fields, response assessment in clinical trials, surgical planning of neoplastic disease of the spine, and more. Sections first overview neuro-oncological disorders before delving into the physics and basic science of neuroimaging and great focus on CT and MRI. The book then focuses on advances in the neuroimaging of brain tumors and neuroimaging of specific tumor types. There is also discussion of neuroimaging of other neuro-oncological syndromes. This book will serve as a resource of background information to neuroimaging researchers and basic scientists with an interest in brain tumors and neuro-oncology. Summarizes translational research on brain imaging for brain tumors Discusses limitations of neuroimaging for diagnosis and treatment Presents advanced imaging technologies, including CT, MRI, and PET Contains new coverage on Laser Interstitial Thermal Therapy, radiation therapy, clinical trials, and more
Book Synopsis Handbook of Neuro-Oncology Neuroimaging by : Herbert B. Newton
Download or read book Handbook of Neuro-Oncology Neuroimaging written by Herbert B. Newton and published by Academic Press. This book was released on 2022-08-21 with total page 1022 pages. Available in PDF, EPUB and Kindle. Book excerpt: With treatment approaches and the field of neuro-oncology neuroimaging changing rapidly, this third edition of the Handbook of Neuro-Oncology Neuroimaging is very relevant to those in the field, providing a single-source, comprehensive, reference handbook of the most up-to-date clinical and technical information regarding the application of neuroimaging techniques to brain tumor and neuro-oncology patients. This new volume will have updates on all of the material from the second edition, and in addition features several new important chapters covering diverse topics such as imaging for the use of Laser Interstitial Thermal Therapy, advanced imaging techniques in radiation therapy, therapeutic treatment fields, response assessment in clinical trials, surgical planning of neoplastic disease of the spine, and more. Sections first overview neuro-oncological disorders before delving into the physics and basic science of neuroimaging and great focus on CT and MRI. The book then focuses on advances in the neuroimaging of brain tumors and neuroimaging of specific tumor types. There is also discussion of neuroimaging of other neuro-oncological syndromes. This book will serve as a resource of background information to neuroimaging researchers and basic scientists with an interest in brain tumors and neuro-oncology. Summarizes translational research on brain imaging for brain tumors Discusses limitations of neuroimaging for diagnosis and treatment Presents advanced imaging technologies, including CT, MRI, and PET Contains new coverage on Laser Interstitial Thermal Therapy, radiation therapy, clinical trials, and more
Book Synopsis Molecular Imaging Through Magnetic Resonance for Clinical Oncology by : Karen Belkic
Download or read book Molecular Imaging Through Magnetic Resonance for Clinical Oncology written by Karen Belkic and published by Cambridge Int Science Publishing. This book was released on 2005-10 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt:
This issue of MRI Clinics of North America focuses on Functional MRI in Oncology. Articles will include: Functional MRI techniques in oncology in the era of personalized medicine, MRI biomarkers and surrogate endpoints in oncology clinical trials, Therapy monitoring with functional MRI, Multiparametric MRI in the assessment of brain tumors, Multiparametric MRI of breast cancer, Functional MRI in chest malignancies, Multiparametric MRI in abdominal malignancies, Assessment of musculoskeletal malignancies with functional MRI, Evaluation of head and neck tumors with functional MRI, Role of multiparametric MRI in malignancies of the urogenital tract, Diffusion-weighted imaging in oncology, Functional MRI in gynecologic cancer, Assessment of angiogenesis with MRI: DCE-MRI and beyond, Imaging of tumor metabolism: MR spectroscopy, and more!
Book Synopsis Functional and Molecular Imaging in Oncology, An Issue of Magnetic Resonance Imaging Clinics of North America, by : Antonio Luna
Download or read book Functional and Molecular Imaging in Oncology, An Issue of Magnetic Resonance Imaging Clinics of North America, written by Antonio Luna and published by Elsevier Health Sciences. This book was released on 2016-01-19 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This issue of MRI Clinics of North America focuses on Functional MRI in Oncology. Articles will include: Functional MRI techniques in oncology in the era of personalized medicine, MRI biomarkers and surrogate endpoints in oncology clinical trials, Therapy monitoring with functional MRI, Multiparametric MRI in the assessment of brain tumors, Multiparametric MRI of breast cancer, Functional MRI in chest malignancies, Multiparametric MRI in abdominal malignancies, Assessment of musculoskeletal malignancies with functional MRI, Evaluation of head and neck tumors with functional MRI, Role of multiparametric MRI in malignancies of the urogenital tract, Diffusion-weighted imaging in oncology, Functional MRI in gynecologic cancer, Assessment of angiogenesis with MRI: DCE-MRI and beyond, Imaging of tumor metabolism: MR spectroscopy, and more!
Propelling quantitative MRI techniques from bench to bedside, Quantitative MRI in Cancer presents a range of quantitative MRI methods for assessing tumor biology. It includes biophysical and theoretical explanations of the most relevant MRI techniques as well as examples of these techniques in cancer applications.The introductory part of the book c
Book Synopsis Quantitative MRI in Cancer by : Thomas E. Yankeelov
Download or read book Quantitative MRI in Cancer written by Thomas E. Yankeelov and published by Taylor & Francis. This book was released on 2011-09-13 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Propelling quantitative MRI techniques from bench to bedside, Quantitative MRI in Cancer presents a range of quantitative MRI methods for assessing tumor biology. It includes biophysical and theoretical explanations of the most relevant MRI techniques as well as examples of these techniques in cancer applications.The introductory part of the book c
This issue of MRI Clinics of North America focuses on Imaging of Brain Tumors, and is edited by Dr. Rivka Colen. Articles will include: Multiparametric Imaging Analysis: MR Spectroscopy; Genomics and MicroRNAs in Glioma; Metabolomics and Hyperpolarization MRI in Brain Tumors; Imaging Genomics in Glioma; Radiomics and Big Data in Imaging; RANO Criteria and Clinical Endpoints; Gliomas: The New WHO Brain Tumor Pathological/Molecular Classification and Clinical and Radiographic Classifications; Liposomal Contrast Agents and Nanoparticles in Brain Tumor Imaging; Multiparametric Imaging Analysis: Perfusion, and more!
Book Synopsis Imaging of Brain Tumors, An Issue of Magnetic Resonance Imaging Clinics of North America, by : Rivka R. Colen
Download or read book Imaging of Brain Tumors, An Issue of Magnetic Resonance Imaging Clinics of North America, written by Rivka R. Colen and published by Elsevier Health Sciences. This book was released on 2016-10-15 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This issue of MRI Clinics of North America focuses on Imaging of Brain Tumors, and is edited by Dr. Rivka Colen. Articles will include: Multiparametric Imaging Analysis: MR Spectroscopy; Genomics and MicroRNAs in Glioma; Metabolomics and Hyperpolarization MRI in Brain Tumors; Imaging Genomics in Glioma; Radiomics and Big Data in Imaging; RANO Criteria and Clinical Endpoints; Gliomas: The New WHO Brain Tumor Pathological/Molecular Classification and Clinical and Radiographic Classifications; Liposomal Contrast Agents and Nanoparticles in Brain Tumor Imaging; Multiparametric Imaging Analysis: Perfusion, and more!
This is a report on updated techniques, instrumentation and clinical application of PET, MRI and MRS in cancer management.
Book Synopsis Molecular Imaging in Oncology by : E. Edmund Kim
Download or read book Molecular Imaging in Oncology written by E. Edmund Kim and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a report on updated techniques, instrumentation and clinical application of PET, MRI and MRS in cancer management.
A concise yet in-depth analysis of imaging modalities for brain tumors FOUR STARS from Doody's Star Ratings™ Brain Tumor Imaging is a practical, comprehensive reference that covers all the methods of imaging used in the diagnosis and assessment of brain tumors. It includes key information on the use of advanced imaging technologies in the clinical setting for the successful treatment of patients with brain tumors. Key Features: Includes more than 500 high-quality images (color as well as black and white) that help illustrate the latest imaging modalities used in neuro-oncology Covers advanced, functional imaging techniques, giving readers the latest information on clinically advanced imaging tools for brain tumor assessment Provides details on how to accurately evaluate treatment effects and differentiate from tumor progression This book is an essential guide to advanced imaging modalities for all radiologists, neuro-radiologists, neuro-oncologists, and neurosurgeons involved in the treatment and evaluation of patients with brain tumors.
Book Synopsis Brain Tumor Imaging by : Rajan Jain
Download or read book Brain Tumor Imaging written by Rajan Jain and published by Thieme. This book was released on 2015-08-19 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise yet in-depth analysis of imaging modalities for brain tumors FOUR STARS from Doody's Star Ratings™ Brain Tumor Imaging is a practical, comprehensive reference that covers all the methods of imaging used in the diagnosis and assessment of brain tumors. It includes key information on the use of advanced imaging technologies in the clinical setting for the successful treatment of patients with brain tumors. Key Features: Includes more than 500 high-quality images (color as well as black and white) that help illustrate the latest imaging modalities used in neuro-oncology Covers advanced, functional imaging techniques, giving readers the latest information on clinically advanced imaging tools for brain tumor assessment Provides details on how to accurately evaluate treatment effects and differentiate from tumor progression This book is an essential guide to advanced imaging modalities for all radiologists, neuro-radiologists, neuro-oncologists, and neurosurgeons involved in the treatment and evaluation of patients with brain tumors.
Neuro-oncology broadly encompasses life-threatening brain and spinal cord malignancies, including primary lesions and lesions metastasizing to the central nervous system. It is well suited for diagnosis, classification, and prognosis as well as assessing treatment response. Radiomics and Radiogenomics (R-n-R) have become two central pillars in precision medicine for neuro-oncology.Radiomics is an approach to medical imaging used to extract many quantitative imaging features using different data characterization algorithms, while Radiogenomics, which has recently emerged as a novel mechanism in neuro-oncology research, focuses on the relationship of imaging phenotype and genetics of cancer. Due to the exponential progress of different computational algorithms, AI methods are composed to advance the precision of diagnostic and therapeutic approaches in neuro-oncology.The field of radiomics has been and definitely will remain at the lead of this emerging discipline due to its efficiency in the field of neuro-oncology. Several AI approaches applied to conventional and advanced medical imaging data from the perspective of radiomics are very efficient for tasks such as survival prediction, heterogeneity analysis of cancer, pseudo progression analysis, and infiltrating tumors. Radiogenomics advances our understanding and knowledge of cancer biology, letting noninvasive sampling of the molecular atmosphere with high spatial resolution along with a systems-level understanding of causal heterogeneous molecular and cellular processes. These AI-based R-n-R tools have the potential to stratify patients into more precise initial diagnostic and therapeutic pathways and permit better dynamic treatment monitoring in this period of personalized medicine. While extremely promising, the clinical acceptance of R-n-R methods and approaches will primarily hinge on their resilience to non-standardization across imaging protocols and their capability to show reproducibility across large multi-institutional cohorts.Radiomics and Radiogenomics in Neuro-Oncology: An Artificial Intelligence Paradigm provides readers with a broad and detailed framework for R-n-R approaches with AI in neuro-oncology, the description of cancer biology and genomics study of cancer, and the methods usually implemented for analyzing. Readers will also learn about the current solutions R-n-R can offer for personalized treatments of patients, limitations, and prospects. There is comprehensive coverage of information based on radiomics, radiogenomics, cancer biology, and medical image analysis viewpoints on neuro-oncology, so this in-depth coverage is divided into two Volumes.Volume 1: Radiogenomics Flow Using Artificial Intelligence provides coverage of genomics and molecular study of brain cancer, medical imaging modalities and analysis in neuro-oncology, and prognostic and predictive models using radiomics.Volume 2: Genetics and Clinical Applications provides coverage of imaging signatures for brain cancer molecular characteristics, clinical applications of R-n-R in neuro-oncology, and Machine Learning and Deep Learning AI approaches for R-n-R in neuro-oncology. Includes coverage on the foundational concepts of the emerging fields of radiomics and radiogenomics Covers neural engineering modeling and AI algorithms for the imaging, diagnosis, and predictive modeling of neuro-oncology Presents crucial technologies and software platforms, along with advanced brain imaging techniques such as quantitative imaging using CT, PET, and MRI Provides in-depth technical coverage of computational modeling techniques and applied mathematics for brain tumor segmentation and radiomics features such as extraction and selection
Book Synopsis Radiomics and Radiogenomics in Neuro-Oncology by : Sanjay Saxena
Download or read book Radiomics and Radiogenomics in Neuro-Oncology written by Sanjay Saxena and published by Elsevier. This book was released on 2024-04-08 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuro-oncology broadly encompasses life-threatening brain and spinal cord malignancies, including primary lesions and lesions metastasizing to the central nervous system. It is well suited for diagnosis, classification, and prognosis as well as assessing treatment response. Radiomics and Radiogenomics (R-n-R) have become two central pillars in precision medicine for neuro-oncology.Radiomics is an approach to medical imaging used to extract many quantitative imaging features using different data characterization algorithms, while Radiogenomics, which has recently emerged as a novel mechanism in neuro-oncology research, focuses on the relationship of imaging phenotype and genetics of cancer. Due to the exponential progress of different computational algorithms, AI methods are composed to advance the precision of diagnostic and therapeutic approaches in neuro-oncology.The field of radiomics has been and definitely will remain at the lead of this emerging discipline due to its efficiency in the field of neuro-oncology. Several AI approaches applied to conventional and advanced medical imaging data from the perspective of radiomics are very efficient for tasks such as survival prediction, heterogeneity analysis of cancer, pseudo progression analysis, and infiltrating tumors. Radiogenomics advances our understanding and knowledge of cancer biology, letting noninvasive sampling of the molecular atmosphere with high spatial resolution along with a systems-level understanding of causal heterogeneous molecular and cellular processes. These AI-based R-n-R tools have the potential to stratify patients into more precise initial diagnostic and therapeutic pathways and permit better dynamic treatment monitoring in this period of personalized medicine. While extremely promising, the clinical acceptance of R-n-R methods and approaches will primarily hinge on their resilience to non-standardization across imaging protocols and their capability to show reproducibility across large multi-institutional cohorts.Radiomics and Radiogenomics in Neuro-Oncology: An Artificial Intelligence Paradigm provides readers with a broad and detailed framework for R-n-R approaches with AI in neuro-oncology, the description of cancer biology and genomics study of cancer, and the methods usually implemented for analyzing. Readers will also learn about the current solutions R-n-R can offer for personalized treatments of patients, limitations, and prospects. There is comprehensive coverage of information based on radiomics, radiogenomics, cancer biology, and medical image analysis viewpoints on neuro-oncology, so this in-depth coverage is divided into two Volumes.Volume 1: Radiogenomics Flow Using Artificial Intelligence provides coverage of genomics and molecular study of brain cancer, medical imaging modalities and analysis in neuro-oncology, and prognostic and predictive models using radiomics.Volume 2: Genetics and Clinical Applications provides coverage of imaging signatures for brain cancer molecular characteristics, clinical applications of R-n-R in neuro-oncology, and Machine Learning and Deep Learning AI approaches for R-n-R in neuro-oncology. Includes coverage on the foundational concepts of the emerging fields of radiomics and radiogenomics Covers neural engineering modeling and AI algorithms for the imaging, diagnosis, and predictive modeling of neuro-oncology Presents crucial technologies and software platforms, along with advanced brain imaging techniques such as quantitative imaging using CT, PET, and MRI Provides in-depth technical coverage of computational modeling techniques and applied mathematics for brain tumor segmentation and radiomics features such as extraction and selection
