Quantitative Image Computing
The role of imaging in healthcare is continuously increasing. Today, medical imaging plays a role in early patient diagnosis, individualized therapy planning, population screening, therapy outcome prediction and assessment, and translational pre-clinical and clinical research. Recent innovations in medical imaging technology have created a tsunami of imaging data, which is revolutionizing diagnosis, therapy planning and follow-up, as well as clinical, preclinical and biomedical research. Moreover, the rapid adoption of digital image archiving and communication makes that large image databases are readily available for multi-modal, multi-temporal, and multi-subject assessment. A consequence is that accurate quantitative image computing has become indispensable. A prerequisite for quantitative image computing is the availability of suitable models that incorporate prior knowledge about the image content and other patient data, including clinical and genetic information. A powerful strategy is to construct such models from the data itself by learning from a representative training set of image instances. In this seminar several clinical applications of this approach will illustrate the opportunities for population and disease modeling, therapy outcome prediction, evidence-based medicine, and predicting missing or unobserved data.
Over deze serie
Beelden worden steeds belangrijker bij medische diagnose en behandeling. Wat betekent dit voor de geneeskundige praktijk? Hoe moeten we scans en foto’s interpreteren? Symposium over de toekomst van de medische techniek.