Medical imaging is a very promising clinical application of AI. Classical machine learning techniques are often used together with the computation of predefined radiomics features.

However, deep learning using deep neural networks is increasingly being used in automated image analysis. This usually requires larger datasets, but here it automatically extracts features from complex medical images instead of predefined radiomics features, and often yields gains in diagnostic accuracy.

Although DL methods are computationally intensive, they can be accelerated by high-performance computing and parallel computing techniques.