Educational project
Radiomics in medical diagnostic image analysis
SUPSI Image Focus
The project involved the analysis of digital medical images from Computed Tomography and the creation of appropriate predictive models. Using radiomics, information can be extrapolated from these images and, by analysing them, a decision support system can be created for the study of a specific clinical case.
The project was realised by the student groups of the "Hackaton 3" module in the Bachelor in Data Science and Artificial Intelligence curriculum.
The project was realised by the student groups of the "Hackaton 3" module in the Bachelor in Data Science and Artificial Intelligence curriculum.
Computed Tomography is a diagnostic examination used to create detailed images of internal organs, bones, soft tissues and blood vessels by means of ionising radiation (X-ray technology), through which neoplasms can be detected.
Radiomics allows a quantitative approach to the analysis of medical images, through which features can be extracted that describe them objectively.
The first phase of the project consisted of using a radiomics library to extract features from an image dataset.Subsequently, the features were analysed in order to identify the most significant ones, on which prediction models were created using machine learning techniques.
Radiomics allows a quantitative approach to the analysis of medical images, through which features can be extracted that describe them objectively.
The first phase of the project consisted of using a radiomics library to extract features from an image dataset.Subsequently, the features were analysed in order to identify the most significant ones, on which prediction models were created using machine learning techniques.