Novel Methods For Oncologic Imaging Analysis Radiomics Machine Learning And Artificial Intelligence
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Novel Methods For Oncologic Imaging Analysis Radiomics Machine Learning And Artificial Intelligence
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Author : Xuelei Ma
language : en
Publisher: Frontiers Media SA
Release Date : 2021-09-23
Novel Methods For Oncologic Imaging Analysis Radiomics Machine Learning And Artificial Intelligence written by Xuelei Ma and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-23 with Medical categories.
Radiomics And Its Clinical Application
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Author : Jie Tian
language : en
Publisher: Academic Press
Release Date : 2021-06-03
Radiomics And Its Clinical Application written by Jie Tian and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-03 with Computers categories.
The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting. This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice. - An introduction to the concepts of radiomics - In-depth presentation of the core technologies and methods - Summary of current radiomics research, perspective on the future of radiomics and the challenges ahead - An introduction to several platforms that are planned to be built: cooperation, data sharing, software, and application platforms
Artificial Intelligence In Medical Imaging
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Author : Erik R. Ranschaert
language : en
Publisher: Springer
Release Date : 2019-01-29
Artificial Intelligence In Medical Imaging written by Erik R. Ranschaert and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with Medical categories.
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 implicationsfor 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.
Artificial Intelligence In Decision Support Systems For Diagnosis In Medical Imaging
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Author : Kenji Suzuki
language : en
Publisher: Springer
Release Date : 2018-01-09
Artificial Intelligence In Decision Support Systems For Diagnosis In Medical Imaging written by Kenji Suzuki and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-09 with Technology & Engineering categories.
This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world. Medical imaging offers essential information on patients’ medical condition, and clues to causes of their symptoms and diseases. Modern imaging modalities, however, also produce a large number of images that physicians have to accurately interpret. This can lead to an “information overload” for physicians, and can complicate their decision-making. As such, intelligent decision support systems have become a vital element in medical-image-based diagnosis and treatment. Presenting extensive information on this growing field of AI, the book offers a valuable reference guide for professors, students, researchers and professionals who want to learn about the most recent developments and advances in the field.
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
Novel Biomarkers And Big Data Based Biomedical Studies In Cancer Diagnosis And Management
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Author : Lin Zhang
language : en
Publisher: Frontiers Media SA
Release Date : 2025-06-05
Novel Biomarkers And Big Data Based Biomedical Studies In Cancer Diagnosis And Management written by Lin Zhang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-05 with Science categories.
Cancer is a multifaceted disease that can elude the natural defense mechanisms of the immune system. Due to the heterogeneity and complexity of cancer, the technical methods used for pre-treatment evaluation, prediction of treatment efficacy, and prognosis analysis still require further research. Immunotherapy has shown immense potential in the treatment of numerous types of cancer. Cancer immunotherapy aims to eliminate malignant cells based on their antigen composition and tumor-associated antigens. PD-1 and PD-L1 are crucial targets for cancer immunotherapy. Although various inflammatory factors and immune markers have been identified to aid in selecting appropriate treatment (chemotherapy or immunotherapy), monitoring treatment efficacy, and predicting prognosis, the combination of different markers in predictive models performs better than a single marker in enhancing the accuracy of treatment efficacy and clinical judgments. In the context of precise cancer treatment, novel diagnoses, predictive factors, and predictive models are essential for better comprehension of cancer treatment and prognosis. The amalgamation of big data and artificial intelligence has been widely utilized in various cancer fields, including basic cancer research, particularly in molecular biological mechanisms, metabolic reprogramming, tumor biology, and clinical transformation research (such as cancer prediction, early diagnosis methods, and development of new treatment methods). The systematic and objective data provided by big data and artificial intelligence can guide diagnosis, optimize clinical treatment decisions, and have a far-reaching impact on clinical transformation. This research topic aims to explore novel biomarkers and predictive models that predict prognosis, treatment efficacy, and toxic side effects in cancer patients. We welcome submissions including, but not limited to: (1) Clinical research investigating novel biomarkers and their comprehensive predictive models for cancer treatment (including chemotherapy, radiation therapy, targeted therapy, and immunotherapy) and prognosis. (2) Original research investigating inflammatory and immune factors associated with various types of cancer, particularly breast and gastrointestinal cancer. (3) Reviews and meta-analyses of effective biomarkers and predictive models in cancer treatment and prognosis. (4) Cancer-related basic research and clinical transformation research based on big data and artificial intelligence. (5) Accurate detection and diagnosis of early cancer, intelligent prediction models of neoadjuvant treatment, and targeted treatment response of cancer.
Reviews In Breast Cancer
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Author : Claudia Mello-Thoms
language : en
Publisher: Frontiers Media SA
Release Date : 2023-06-07
Reviews In Breast Cancer written by Claudia Mello-Thoms and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-07 with Medical categories.
Mr Imaging Of Head And Neck Cancer An Issue Of Magnetic Resonance Imaging Clinics Of North America E Book
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Author : Ahmed Abdel Khalek Abdel Razek
language : en
Publisher: Elsevier Health Sciences
Release Date : 2021-11-26
Mr Imaging Of Head And Neck Cancer An Issue Of Magnetic Resonance Imaging Clinics Of North America E Book written by Ahmed Abdel Khalek Abdel Razek and has been published by Elsevier Health Sciences this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-26 with Medical categories.
In this issue of MRI Clinics, guest editor Dr. Ahmed Abdel Khalek Abdel Razek brings his considerable expertise to the topic of MR Imaging of Head and Neck Cancer. Top experts in the field cover key topics such as artificial intelligence and deep learning of head and neck cancer, MR imaging of salivary gland tumors, MR imaging of vascular malformations and tumors of the head and neck, and more. - Contains 14 relevant, practice-oriented topics including the role of MR imaging in head and neck squamous cell carcinoma; MR imaging of nasopharyngeal carcinoma; MR imaging of oropharyngeal cancer and oral cavity tumors; MR imaging of laryngeal and hypopharyngeal cancer; MR imaging of nasal and paranasal sinuses tumors; and more. - Provides in-depth clinical reviews on MR imaging of head and neck cancer, offering actionable insights for clinical practice. - Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.
Automation And Artificial Intelligence In Radiation Oncology
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Author : Savino Cilla
language : en
Publisher: Frontiers Media SA
Release Date : 2022-11-16
Automation And Artificial Intelligence In Radiation Oncology written by Savino Cilla and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-16 with Medical categories.
Machine Learning In Radiation Oncology
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Author : Issam El Naqa
language : en
Publisher: Springer
Release Date : 2015-06-19
Machine Learning In Radiation Oncology written by Issam El Naqa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-19 with Medical categories.
This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.