In the era of big data and multi-connectivity via IoTs, protecting and securing multimedia data has become a real necessity and priority for organizations and businesses, but this can be a rather difficult task due to the heterogeneous nature of platforms and data sets. It is therefore essential to improve the security level of multimedia information by developing core technologies to prevent the loss and damage of information during processing and transmission.

Medical images, in various formats, are used by clinicians to identify abnormalities or markers associated with certain conditions, such as cancers, diseases, abnormalities or other adverse health conditions. Deep learning algorithms use vast volumes of data to train the computer to recognise certain features in the images that are associated with the disease or condition that you wish to identify.

Medical images can highlight differences between healthy tissue and unhealthy tissue and these images can then be assessed by a healthcare professional to identify the stage and spread of a disease so a treatment path can be established. With machine learning techniques becoming more prevalent in healthcare, algorithms can be trained to identify healthy or unhealthy tissues and quickly differentiate between the two. Statistical models can be used to process numerous images of the same type in a fraction of the time it would take a human to assess the same quantity, saving time and money in aiding practitioners in their assessment.