The world's first use of Tc-99m for medical imaging was demonstrated at the UC. Theoretical and application developments for physical image quality assessment of spatial resolution, noise, and contrast were investigated for both analog and digital imaging systems. Research & developments in medical decision making & ROC analysis have benefited researchers around the world through the free availability of state-of-the-art ROC analysis software. Image co-registration and integration research done at UC in the 1980s germinated the field of multi-modality imaging. University of Chicago pioneered the field of computer-aided diagnosis, developing the first prototype for mammographic CAD in the early 1990's. Ground-breaking developments in tomographic image reconstruction have been made yielding analytic solutions to the complex 3D and 4D problems. More recently, developments in small-animal MRI have led to the first image of mammary DCIS in a mouse model. In addition, research at the UC includes solving important problems in muscle and cardiovascular physiology such as NMR detection of gene expression.
The Radiology Research Imaging Center, which occupies three floors and was partially financed by an NIH construction grant, provides the department with a state of the art multidisciplinary radiology imaging research center designed to facilitate greater integrated research and to encourage collaboration across department lines.
In coordination with the Human Imaging Research Office, "de-identified" medical images are provided to researchers spanning multiple disciplines to further scientific endeavors. Additionally, the Brain Research Imaging Center, a joint enterprise between Radiology and Neurology has a 3T and 1.5T MRI equipment to support this endeavor. The Department is also proud to run the Molecular Imaging and Cyclotron Facility with multiple interdisciplinary projects. Most recently, the faculty received an NIH Shared Instrument Grant to support high performance computing, NIH S10 OD025081 (Giger), namely the Protected Radiomics Analysis Commons for Deep Learning in Biomedical Discovery, which is currently installed in a machine learning facility within the Department of Radiology, with a reach of 1.9 PFLOPS.