Clinical imaging increasingly utilises functional and molecular methods that are often more sensitive and specific than conventional anatomical approaches at detecting disease and its response to therapy. Functional and molecular imaging is often dimensionally complex and therefore offers opportunities to probe tissue biology in new ways. However, the multidimensionality of the data can present challenges as well as opportunities, as it is often noisy and acquired at low spatial resolution. This presentation will discuss new clinical methods including hyperpolarised carbon-13 MRI for probing tissue metabolism and how this has been applied to the study of the human brain and for cancer imaging. Model and non-model based approaches to quantify the data will be discussed. Methods for automated segmentation have also been used which exploit the multidimensionality of the data. Ultimately these quantitative approaches could be used as robust methods to study imaging data in routine clinical practice.