Recent advances in medical imaging technology have led to systems that can produce highly detailed anatomical and functional images of the human body. Continuing developments are leading to ever more detailed images, which presents increasing challenges for handling the volume of data acquired and making sense of the information represented. There is, therefore, a pressing need for computer software which is able to intelligently handle the large datasets generated by modern imaging techniques, to provide robust, quantitative measures of health or disease.
In the case of imaging biomarkers for respiratory disease, this requires the development of advanced algorithms, for example, to segment the parts of the image data of interest, such as the tracheo-bronchial tree. Combining information from different imaging modalities of the same patient has the potential to offer new insights, but requires the development of software tools to perform the combination intelligently, taking into account the different imaging parameters of the different modalities.