Radiomics and Radiogenomics in Neuro-Oncology: An Artificial Intelligence Paradigm, Volume One: Radiogenomics Flow Using Artificial Intelligence broadly encompasses the study of life-threatening brain and spinal cord malignancies, including primary lesions and those metastasizing to the central nervous system. 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…mehr
Radiomics and Radiogenomics in Neuro-Oncology: An Artificial Intelligence Paradigm, Volume One: Radiogenomics Flow Using Artificial Intelligence broadly encompasses the study of life-threatening brain and spinal cord malignancies, including primary lesions and those metastasizing to the central nervous system. 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. Sections in this book discuss several AI approaches that have been applied to conventional and advanced medical imaging data. 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.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr. Sanjay Saxena is Assistant Professor in the Department of Computer Science and Engineering at International Institute of Information Technology, Bhubaneswar, India. Dr. Saxena completed is Post-Doctoral research in Radiomics and Radiogenomics studies in Neuro-Oncology at the Artificial Intelligence in Biomedical Imaging Lab, Perelman School of Medicine, University of Pennsylvania, USA. Dr. Saxena is author of several books, including Deep Learning Applications in Medical Imaging, IGI Global; and High-Performance Medical Image Processing, Apple Academic Press. His research specialties include work on brain tumor (glioblastoma) segmentation and analysis.
Inhaltsangabe
Section 1: Introduction 1. Fundamental pipelines of Radiomics and Radiogenomics(R-n-R) Contributors - Ishan Ayus, Biswajit Jena, Sanjay Saxena 2. Artificial Intelligence, its Components and crucial technologies for implementation Contributors - Rupsa Bhattacharjee, Snekha Thakran 3. Radiomics and Radiogenomics(R-n-R) with?Artificial Intelligence:?approaches,??applications,?advances,?current challenges,?future?perspectives Contributor - Pinar Kirci Section 2: Genomics and Molecular Study of Brain Cancer 4. Brain Cancer and World Health Organization Contributors - Moirangthem Gelson Singh , Sanjay Saxena , Suvendu Rup , Sarthak Padhi 5. Genomic and Genetic levels alteration in Brain Cancer Contributors - Shantilata Palei, Sakshi Arora, Sanjay Saxena, Niranjan Kaushik 6. Role of Molecular Markers in Diagnosis and Prognosis of Gliomas(Brain Tumor) Contributor - Anand Kumar Pandey 7. Multi-omics studies in Neuro-Oncology Contributors - Mullapudi Venkata Sai Samartha, Sakshi Arora, Shantilata Palei, Vitthal Gupta, Sanjay Saxena Section 3: Medical Imaging Modalities and Analysis in Neuro-Oncology 8. Medical image analysis steps: Medical image acquisition to classification(or regression) in Neuro-Oncology Contributors - Suchismita Das, Meghna, Sanjay Saxena 9. MRI: An important Biomarker for radiomics study of brain cancer and Its uses in Machine Learning Contributors - Sudip Paul and Vinayak Majhi 10. Deep learning algorithms for imaging gliomas for diagnosis, prognosis, and treatment strategies predictions Contributor- Anand Kumar Pandey Section 4: Radiomics and Radiogenomics in Neuro-Oncology 11. Radiomics and Radiogenomics of Central Nervous System Metastatic Lesions Contributor - Teresa Perillo 12. Clinical Applications implementation in Neuro-Oncology using Machine Learning Approaches Contributors - Biswajit Jena, Ishan Ayus, Sanjay Saxena 13. Applications and Constraints of Artificial Intelligence in Radiomics and Radiogenomics(R-n-R) Studies in Neuro-Oncology Contributors - Shovna Panda, Sarthak Padhi, Vitthal Gupta, Jasjit S. Suri, Sanjay Saxena
Section 1: Introduction 1. Fundamental pipelines of Radiomics and Radiogenomics(R-n-R) Contributors - Ishan Ayus, Biswajit Jena, Sanjay Saxena 2. Artificial Intelligence, its Components and crucial technologies for implementation Contributors - Rupsa Bhattacharjee, Snekha Thakran 3. Radiomics and Radiogenomics(R-n-R) with?Artificial Intelligence:?approaches,??applications,?advances,?current challenges,?future?perspectives Contributor - Pinar Kirci Section 2: Genomics and Molecular Study of Brain Cancer 4. Brain Cancer and World Health Organization Contributors - Moirangthem Gelson Singh , Sanjay Saxena , Suvendu Rup , Sarthak Padhi 5. Genomic and Genetic levels alteration in Brain Cancer Contributors - Shantilata Palei, Sakshi Arora, Sanjay Saxena, Niranjan Kaushik 6. Role of Molecular Markers in Diagnosis and Prognosis of Gliomas(Brain Tumor) Contributor - Anand Kumar Pandey 7. Multi-omics studies in Neuro-Oncology Contributors - Mullapudi Venkata Sai Samartha, Sakshi Arora, Shantilata Palei, Vitthal Gupta, Sanjay Saxena Section 3: Medical Imaging Modalities and Analysis in Neuro-Oncology 8. Medical image analysis steps: Medical image acquisition to classification(or regression) in Neuro-Oncology Contributors - Suchismita Das, Meghna, Sanjay Saxena 9. MRI: An important Biomarker for radiomics study of brain cancer and Its uses in Machine Learning Contributors - Sudip Paul and Vinayak Majhi 10. Deep learning algorithms for imaging gliomas for diagnosis, prognosis, and treatment strategies predictions Contributor- Anand Kumar Pandey Section 4: Radiomics and Radiogenomics in Neuro-Oncology 11. Radiomics and Radiogenomics of Central Nervous System Metastatic Lesions Contributor - Teresa Perillo 12. Clinical Applications implementation in Neuro-Oncology using Machine Learning Approaches Contributors - Biswajit Jena, Ishan Ayus, Sanjay Saxena 13. Applications and Constraints of Artificial Intelligence in Radiomics and Radiogenomics(R-n-R) Studies in Neuro-Oncology Contributors - Shovna Panda, Sarthak Padhi, Vitthal Gupta, Jasjit S. Suri, Sanjay Saxena
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