Full Description
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.
Contents
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
