Skip to main content

Save up to 20% on Elsevier print and eBooks with free shipping. No promo code needed.

Save up to 20% on print and eBooks.

Radiomics and Radiogenomics in Neuro-Oncology

An Artificial Intelligence Paradigm - Volume 1: Radiogenomics Flow Using Artificial Intelligence

1st Edition - April 1, 2024

Editors: Sanjay Saxena, Jasjit Suri

Language: English
Paperback ISBN:
9 7 8 - 0 - 4 4 3 - 1 8 5 0 8 - 3
eBook ISBN:
9 7 8 - 0 - 4 4 3 - 1 8 5 0 7 - 6

Radiomics and Radiogenomics in Neuro-Oncology: An Artificial Intelligence Paradigm, Volume One: Radiogenomics Flow Using Artificial Intelligence broadly encompasses the study… Read more

Radiomics and Radiogenomics in Neuro-Oncology

Purchase options

LIMITED OFFER

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code is needed.

Institutional subscription on ScienceDirect

Request a sales quote
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.