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Radiomics and Radiogenomics in Neuro-Oncology. An Artificial Intelligence Paradigm - Volume 1: Radiogenomics Flow Using Artificial Intelligence

  • Book

  • April 2024
  • Elsevier Science and Technology
  • ID: 5894775

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.

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Table of 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

Authors

Sanjay Saxena Assistant Professor, Department of Computer Science and Engineering, International Institute of Information Technology, Bhubaneswar, India.

Dr. Sanjay Saxena is an Assistant Professor in the Department of Computer Science and Engineering at IIIT Bhubaneswar, India. He obtained his Ph.D. from the Indian Institute of Technology (BHU), Varanasi, and completed his postdoctoral research at the Artificial Intelligence in Biomedical Imaging Lab, University of Pennsylvania, USA. Dr. Saxena's primary research area involves developing AI-based methods for brain cancer analysis, with a broader focus on Data Science, Machine Learning, Deep Learning, and the emerging fields of Radiomics and Radiogenomics. His tenure under Prof. Davatzikos at the University of Pennsylvania was instrumental in his significant learning about Radiomics/Radiogenomics. Dr. Saxena is a member of prestigious organisations such as IEEE, the Society of Neuro-Oncology, ACM, and the New York Academy of Science. He has presented his work at globally recognised universities such as like Imperial College London, Stony Brook University, and Vienna University of Technology. and has made substantial scholarly contributions, with several peer-reviewed Journals, conference publications, book chapters, and two books to his name, advancing the intersection of AI and human cancer research.

Jasjit Suri Chairman, AtheroPoint LLC.

Dr. Jasjit Suri, PhD, MBA, is an innovator, visionary, scientist, and internationally known world leader. Dr Suri received the Director General's Gold medal in 1980 and Fellow of (i) American Institute of Medical and Biological Engineering, awarded by the National Academy of Sciences, Washington DC, (ii) Institute of Electrical and Electronics Engineers, (iii) American Institute of Ultrasound in Medicine, (iv) Society of Vascular Medicine, (v) Asia Pacific Vascular Society, and (vi) Asia Association of Artificial Intelligence. Dr. Suri was honored with life time achievement awards by Marcus, NJ, USA and Graphics Era University, Dehradun, India. He has published nearly 300 peer-reviewed Artificial Intelligence articles, nearly 2000 Google Scholar Publications, 100 books, and 100 innovations/trademarks leading to an H-index of nearly 100 with about 43,000 citations. He has held positions as chairman of AtheroPoint, CA, USA, IEEE Denver section, Colorado, USA, and advisory board member to healthcare industries and several universities in the United States of America and abroad.