Radiomics is a novel technology that unlocks new diagnostic capabilities by means of medical images and machine learning techniques. Today, medical imaging interpretation is solely based on subjective radiological opinions that suffers from increased variability and low reproducibility. Including Radiomics in the diagnostic process it is expected to result in improvement of diagnostic accuracy, as well as prediction of treatment response and access to early prognosis valuable information.
In this course, a non-technical review of the basic concepts of machine learning will be provided, while the focus of the second part of the course will be in specific areas of potential clinical applications in oncologic imaging.
Several modules of the Radiomics pipeline will be presented and discussed starting from the first phase where a clinician needs to formulate the clinical question. Consequently, a Radiologist needs to identify the relevant data sources (types of imaging modalities), and after that an imaging scientist should make sure that the data are preprocessed in a way to become exploitable by the next phases in the pipeline. Following the lesion segmentation should take place be more than one Radiologists, then radiomics features should be computed by and Imaging scientist, in order to proceed to model training and validation phases made by a Data Scientist.
Testimonials:
"Very competent presenter with deep knowledge in the field.”
Dr. Mischa Woisetschläger, University Hospital Linköping, Sweden (Fellow, June 2021)
"Useful course which will help me a lot in preparing radiomics papers. Great interaction with the speaker”
Dr. Achilles Chatziioannou, Greece (Fellow, June 2021)
Level II - General radiologist
Intermediate level
Nickolas Papanikolaou, PhD (Male), is a Principal Investigator in Oncologic Imaging at CHAMPALIMAUD FOUNDATION and research group leader of the Computational Clinical Imaging Group. He is an Affiliated Researcher at Karolinska Institute and a Senior Affiliated Researcher at the Institute of Computer Science – FORTH. Dr. Nikolaos Papanikolaou studied biomedical engineering while he obtained his Ph.D. from the Medical School of the University of Crete. He has been a research associate of the Department of Radiology, University Hospital of Heraklion, from 1999 to 2009. He has published 85 scientific papers in peer-reviewed international journals and 17 chapters in international books. At the same time, he edited a series of 3 books on Diffusion-Weighted Imaging Applications in GI, GU, and Hepatobiliary systems. He has delivered more than 100 invited lectures in international congresses and educational courses. He served as a member of the editorial board of European Radiology in the section of experimental radiology while he was a member of the abdominal subcommittee of ECR. He has been awarded two research scholarships from ECR. Finally, he is an honorary member of the Spanish Society of Gastrointestinal Radiology (SEDIA). The main focus of his research is the development and validation of imaging biomarkers on cancer applications. He recently initiated the development of a Radiomics Network comprising luminary clinical sites in the US and Europe to advance research in that area of Radiomics. He is the section editor on AI, Radiomics, and Machine Learning in Cancer Imaging, and he is chairing the e-learning subcommittee of ICIS.
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