We are seeking grant applications in the following areas:
- Multi-modality imaging labels. The use of contrast agents or labeled compounds to provide specific information is common in imaging, however there are often limits on what information can be achieved with any one label. We seek applications that propose ways in which novel imaging agents can report information across more than one “readout” modality.
- Flexible image analysis. Image analysis is often developed for a specific type of imaging technique, yet the underlying image analysis principles are often common across image modalities and image scales. We seek grant applications that describe image analysis methods that can be applied widely across imaging science, or that allow new insights to be made by combining information across techniques.
- Extracting information from multi-scale images. Different imaging modalities provide information at different spatial scales. Often, information is required across a range of spatial scales to address a biological or medical problem. We seek grants that combine information across spatial scales to address a specific area of biology or human disease.
- Novel combined imaging modalities. There is an increasing trend to combine different imaging modalities to take advantage of the complementary information that they can yield. We seek grant applications that combine two or more existing imaging technologies in novel ways to address a specific biomedical application.
- Improving imaging sensitivity and image contrast. Biomedical imaging is invariably limited by a given method’s signal-to-noise ratio. We invite grants that propose novel methods to improve the achievable image sensitivity or contrast, either by improving the image acquisition, or analysis, or both.
- Using medical imaging to develop or validate biophysical models. Different imaging modalities can provide complementary information about different aspects of tissue or organ function. Such information can be used to develop, refine, or validate biophysical models, which may be important in characterizing disease processes (e.g. a biomechanical model of the ankle, or physiological models of blood flow). We seek grants that incorporate information available from medical imaging into biophysical models related to human biology or human disease.