Integrative Imaging research theme
Bringing together ideas, modalities, and people
Developing the next generation of ultrasound, magnetic resonance, optical, and chemical imaging technologies.
![Lalel-free in vivo image of extracellular vesicles, which show up bright blue against a black background](https://beckman.illinois.edu/images/default-source/research/evit2.png?sfvrsn=4890cdee_0)
![A stimulated Raman scattering microscopy image shows a co-culture of colon cancer cells and fibroblasts embedded in hydrogel matrix.](https://beckman.illinois.edu/images/default-source/research/bi_image_sm_high-resolution_wout_scalebar.png?sfvrsn=e3f6f176_6)
Fighting cancer with imaging tools
Advances in different scales and modes of biomedical imaging tools, as well as the algorithms that create imaging data, can attack cancer better than ever. Researchers are working to understand how cancer cells form and respond to treatment. They're partnering with the Cancer Center at Illinois to use their imaging expertise for new discoveries, with the goals of understanding and predicting how cancer will respond to treatment.
![mri_nancy](https://beckman.illinois.edu/images/default-source/research/mri_nancy.jpg?sfvrsn=4e00c47_4)
Understanding the brain with neuroimaging
Neuroimaging methods are helping cognitive neuroscience flourish. At Beckman, researchers are working to understand changes in cognition and brain structure and function in adults, and how interventions like fitness or cognition training affect aging.
They're developing the next generation of tools in magnetic resonance imaging and diffuse optical imaging to examine neural activity, blood flow, metabolites, and chemistry of the brain.
![A four-channel multiphoton image of cancer cells](https://beckman.illinois.edu/images/default-source/research/deep-neural-network_compim1a.png?sfvrsn=763522cd_4)
Breaking barriers in computational imaging
Researchers are transforming the advanced computational methods and algorithms to acquire and process images. They’re revamping the entire imaging process:
- building physics-based forward models and biology-based interpretation models
- solving large-scale inverse problems
- developing machine learning-based methods
They’re changing the way images are acquired, processed, and interpreted, while overcoming barriers in speed, resolution, and signal-to-noise ratio.
Theme co-chairs
![Mariana Kersh's directory photo.](https://beckman.illinois.edu/content/uploads/images/directory/mkersh.jpg)
Mariana Kersh Associate Professor mkersh@illinois.edu
![Michael L. Oelze's directory photo.](https://beckman.illinois.edu/content/uploads/images/directory/oelze.png)
Michael L. Oelze Professor oelze@illinois.edu