Radiomics And Radiogenomics In Neuro Oncology

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Radiomics And Radiogenomics In Neuro Oncology

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Author : Sanjay Saxena
language : en
Publisher: Elsevier
Release Date : 2024-10-15

Radiomics And Radiogenomics In Neuro Oncology written by Sanjay Saxena and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-15 with Medical categories.

Radiomics and Radiogenomics in Neuro-Oncology: An Artificial Intelligence Paradigm—Volume 2: Genetics and Clinical Applications provides readers with a broad and detailed framework for radiomics and radiogenomics (R-n-R) approaches with AI in neuro-oncology. It delves into the study of cancer biology and genomics, presenting methods and techniques for analyzing these elements. The book also highlights current solutions that R-n-R can offer for personalized patient treatments, as well as discusses the limitations and future prospects of AI technologies.Volume 1: Radiogenomics Flow Using Artificial Intelligence covers the genomics and molecular study of brain cancer, medical imaging modalities and their analysis in neuro-oncology, and the development of prognostic and predictive models using radiomics.Volume 2: Genetics and Clinical Applications extends the discussion to imaging signatures that correlate with molecular characteristics of brain cancer, clinical applications of R-n-R in neuro-oncology, and the use of Machine Learning and Deep Learning approaches for R-n-R in neuro-oncology. - Includes coverage of foundational concepts of the emerging fields of Radiomics and Radiogenomics - Covers imaging signatures for brain cancer molecular characteristics, including Isocitrate Dehydrogenase Mutations (IDH), TP53 Mutations, ATRX loss, MGMT gene, Epidermal Growth Factor Receptor (EGFR), and other mutations - Presents clinical applications of R-n-R in neuro-oncology such as risk stratification, survival prediction, heterogeneity analysis, as well as early and accurate prognosis - Provides in-depth technical coverage of radiogenomics studies for difference brain cancer types, including glioblastoma, astrocytoma, CNS lymphoma, meningioma, acoustic neuroma, and hemangioblastoma

Radiomics And Radiogenomics In Neuro Oncology

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Author : Hassan Mohy-ud-Din
language : en
Publisher: Springer Nature
Release Date : 2020-02-24

Radiomics And Radiogenomics In Neuro Oncology written by Hassan Mohy-ud-Din and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-24 with Computers categories.

This book constitutes the proceedings of the First International Workshop on Radiomics and Radiogenomics in Neuro-oncology, RNO-AI 2019, which was held in conjunction with MICCAI in Shenzhen, China, in October 2019. The 10 full papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with the development of tools that can automate the analysis and synthesis of neuro-oncologic imaging.

Radiomics And Radiogenomics In Neuro Oncology

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Author : Sanjay Saxena
language : en
Publisher: Elsevier
Release Date : 2024-03-29

Radiomics And Radiogenomics In Neuro Oncology written by Sanjay Saxena and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-29 with Medical categories.

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

Machine Learning In Clinical Neuroimaging And Radiogenomics In Neuro Oncology

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Author : Seyed Mostafa Kia
language : en
Publisher: Springer Nature
Release Date : 2020-12-30

Machine Learning In Clinical Neuroimaging And Radiogenomics In Neuro Oncology written by Seyed Mostafa Kia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-30 with Computers categories.

This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and the Second International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.* For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging. For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience. *The workshops were held virtually due to the COVID-19 pandemic.

Machine Learning In Clinical Neuroscience

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Author : Victor E. Staartjes
language : en
Publisher: Springer Nature
Release Date : 2021-12-03

Machine Learning In Clinical Neuroscience written by Victor E. Staartjes and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-03 with Medical categories.

This book bridges the gap between data scientists and clinicians by introducing all relevant aspects of machine learning in an accessible way, and will certainly foster new and serendipitous applications of machine learning in the clinical neurosciences. Building from the ground up by communicating the foundational knowledge and intuitions first before progressing to more advanced and specific topics, the book is well-suited even for clinicians without prior machine learning experience. Authored by a wide array of experienced global machine learning groups, the book is aimed at clinicians who are interested in mastering the basics of machine learning and who wish to get started with their own machine learning research. The volume is structured in two major parts: The first uniquely introduces all major concepts in clinical machine learning from the ground up, and includes step-by-step instructions on how to correctly develop and validate clinical prediction models. It also includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, and time series analysis. The second part provides an overview of some state-of-the-art applications of these methodologies. The Machine Intelligence in Clinical Neuroscience (MICN) Laboratory at the Department of Neurosurgery of the University Hospital Zurich studies clinical applications of machine intelligence to improve patient care in clinical neuroscience. The group focuses on diagnostic, prognostic and predictive analytics that aid in decision-making by increasing objectivity and transparency to patients. Other major interests of our group members are in medical imaging, and intraoperative applications of machine vision.

Radiomics And Radiogenomics

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Author : Ruijiang Li
language : en
Publisher: CRC Press
Release Date : 2019-07-09

Radiomics And Radiogenomics written by Ruijiang Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-09 with Science categories.

Radiomics and Radiogenomics: Technical Basis and Clinical Applications provides a first summary of the overlapping fields of radiomics and radiogenomics, showcasing how they are being used to evaluate disease characteristics and correlate with treatment response and patient prognosis. It explains the fundamental principles, technical bases, and clinical applications with a focus on oncology. The book’s expert authors present computational approaches for extracting imaging features that help to detect and characterize disease tissues for improving diagnosis, prognosis, and evaluation of therapy response. This book is intended for audiences including imaging scientists, medical physicists, as well as medical professionals and specialists such as diagnostic radiologists, radiation oncologists, and medical oncologists. Features Provides a first complete overview of the technical underpinnings and clinical applications of radiomics and radiogenomics Shows how they are improving diagnostic and prognostic decisions with greater efficacy Discusses the image informatics, quantitative imaging, feature extraction, predictive modeling, software tools, and other key areas Covers applications in oncology and beyond, covering all major disease sites in separate chapters Includes an introduction to basic principles and discussion of emerging research directions with a roadmap to clinical translation

Hybrid Pet Mr Neuroimaging

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Author : Ana M. Franceschi
language : en
Publisher: Springer Nature
Release Date : 2021-11-30

Hybrid Pet Mr Neuroimaging written by Ana M. Franceschi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-30 with Medical categories.

This book serves as a reference and comprehensive guide for PET/MR neuroimaging. The field of PET/MR is rapidly evolving, however, there is no standard resource summarizing the vast information and its potential applications. This book will guide neurological molecular imaging applications in both clinical practice and the research setting. Experts from multiple disciplines, including radiologists, researchers, and physicists, have collaborated to bring their knowledge and expertise together. Sections begin by covering general considerations, including public health and economic implications, the physics of PET/MR systems, an overview of hot lab and cyclotron, and radiotracers used in neurologic PET/MRI. There is then coverage of each major disease/systemic category, including dementia and neurodegenerative disease, epilepsy localization, brain tumors, inflammatory and infectious CNS disorders, head and neck imaging, as well as vascular hybrid imaging. Together, we have created a thorough, concise and up-to-date textbook in a unique, user-friendly format. This is an ideal guide for neuroradiologists, nuclear medicine specialists, medical physicists, clinical trainees and researchers.

Cancer Exposomics And Environmental Influences On Carcinogenesis

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Author : Raghavan, Ramya
language : en
Publisher: IGI Global
Release Date : 2025-07-02

Cancer Exposomics And Environmental Influences On Carcinogenesis written by Raghavan, Ramya and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-02 with Medical categories.

Cancer exposomics is an emerging field seeking to understand how environmental exposures across a person's lifetime contribute to cancer development. Exposomics emphasize the role of external and internal environmental influences, including pollutants, diet, lifestyle, infections, and the microbiome, in carcinogenesis. This approach leverages advanced technologies like spectrometry, bioinformatics, and data analysis to map complex exposure-disease relationships. By uncovering the environmental causes of cancer, exposomics can inform prevention strategies, early detection, and targeted interventions, shifting treatment to proactive health protection. Cancer Exposomics and Environmental Influences on Carcinogenesis explores multi-omics and its application in the exposomics of cancer. It serves as a vital resource for researchers, bridging the gap between scientific research and practical applications in cancer prevention and treatment. This book covers topics such as biology, environmental science, and medical technology, and is a useful resource for medical and healthcare workers, oncologists, engineers, academicians, researchers, and environmental scientists.

Roles Of Mitophagy In Cancer Regulation

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Author : Pandurangan, Ashok Kumar
language : en
Publisher: IGI Global
Release Date : 2025-06-05

Roles Of Mitophagy In Cancer Regulation written by Pandurangan, Ashok Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-05 with Medical categories.

Mitogaphy is a selective autophagic degradation of mitochondria, playing a crucial role in maintaining cellular homeostasis by eliminating damaged or dysfunctional mitochondria. Relating to cancer, mitophagy influences tumorigenesis, progression, and therapeutic response in complex and contradictory ways. By regulating mitochondrial quality control, energy metabolism, and apoptotic signaling, mitophagy contributes to the delicate balance between cell survival and death. This process can support cancer cell survival under stress conditions such as hypoxia and nutrient deprivation, yet it can suppress tumor development by limiting oxidative stress and genome instability. Understanding the multifaceted roles of mitophagy in cancer regulation is essential for developing targeted therapeutic strategies and improving clinical outcomes. Roles of Mitophagy in Cancer Regulation explores how mitophagy influences cell differentiation and its central role in cellular activities. It examines how mitophagy is regulated in cancer, the removal of damaged mitochondria through autophagy, and the maintenance of proper cellular functions. Covering topics such as cellular biology, DNA, and mitochondrial science, this book is an excellent resource for engineers, medical professionals, academicians, scientists, and researchers.

Computational Neurosurgery

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Author : Antonio Di Ieva
language : en
Publisher: Springer Nature
Release Date : 2024-11-10

Computational Neurosurgery written by Antonio Di Ieva and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-10 with Science categories.

This comprehensive and authoritative reference presents the state-of-the-art computational methods applied to the field of neurosurgery. The book brings together leading neuroscientists, neurosurgeons, mathematicians, computer scientists, engineers, ethicists and lawyers, to open the new frontier of computational neurosurgery to a broad audience interested in the translational field of the application of computational models, such as deep learning, to the study of the brain and the practical applications of neurosurgery. The focus is primarily clinical, and there is a solid foundation of research aspects. With forewords by Michael L.J. Apuzzo and Enrico Coiera, the book is organized into 2 sections: (1) tenets of computational modeling, artificial intelligence, computational analysis, and analysis software; (2) computational neurosurgery applications, including neurodiagnostics, neuro-oncology, vascular neurosurgery, all the neurosurgical disciplines, surgical approaches, intraoperative applications, and ethics and legal aspects.