Fig. 2 |. Artificial intelligence methods in medical imaging.

This schematic outlines two artificial intelligence (AI) methods for a representative classification task, such as the diagnosis of a suspicious object as either benign or malignant. a | The first method relies on engineered features extracted from regions of interest on the basis of expert knowledge. Examples of these features in cancer characterization include tumour volume, shape, texture, intensity and location. The most robust features are selected and fed into machine learning classifiers. b | The second method uses deep learning and does not require region annotation — rather, localization is usually sufficient. It comprises several layers where feature extraction, selection and ultimate classification are performed simultaneously during training. As layers learn increasingly higher-level features (Box 1), earlier layers might learn abstract shapes such as lines and shadows, while other deeper layers might learn entire organs or objects. Both methods fall under radiomics, the data-centric, radiology-based research field.