Computed tomography (CT) introduced medicine to digital imaging. This occurred in the early 1970s and it was the start of the digital medical imaging revolution. The resulting changes and improvements in health care associated with digital imaging have been marked, are occurring now, and are likely to continue into the future. Before CT, medical images were acquired, stored, and displayed in analog form (i.e., on film). Now essentially all medical images are acquired and stored digitally. When they are not viewed by computer, they are converted to an analog image to be seen. The application of computer algorithms and the processing of digital medical images improves the visualization of diagnostically important details and aids diagnosis by extracting significant quantitative information. Examples of this can be seen with CAD and radiomics applications in the diagnosis of lung and colorectal cancer, respectively. The objectives of this article are to point out the key aspects of the digital medical imaging revolution, to review its current status, to discuss its clinical translation in two major areas: lung and colorectal cancer, and to provide future directions and challenges of these techniques.

Acute ischemic stroke (AIS) is the loss of neurological function due to a sudden reduction in cerebral blood flow and is a leading cause of disability and death worldwide. In recent years, the field of radiological imaging has experienced an explosion that may reach unprecedented heights with the advent of artificial intelligence. One of the latest innovations in artificial intelligence is radiomics, which is based on the fact that a large amount of quantitative data can be extracted from radiological images, from which patterns can be identified and associated with specific pathologies. Since its inception, radiomics has been particularly associated with the field of oncology, with promising results in a wide range of clinical situations. The performance of radiomics in non-tumour pathologies has been increasingly explored in recent years and the results continue to be promising. The aim of this review is to explore the potential applications of radiomics in AIS patients and to theorise how radiomics may change the paradigm for these patients in the coming years.