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 pre-processed 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.
Maximum number of seats: 10
- To present the basic aspects and techniques in Radiomics
- To become familiar with practical aspects of a Radiomics Pipeline
- To discuss potential clinical applications of Radiomics in Oncologic Patients
Programme will include
- Each module will be covered by means of a short theoretical lecture and Q&A after a practical online demonstration.
Level II - General radiologist
- A computer with Google Chrome and Internet Access
- Attendees need to download the free software "Rapid Miner" in order to carry the hands on