Ken Sauer


PUBLISHED: December 19, 2011

Ken SauerAssociate Professor
Department of Electrical Engineering

X-rays, CT scans, MRIs, and ultrasound scans are all imaging techniques physicians use to form their diagnoses. “Image reconstruction — developing an accurate picture from the indirect measurements created by these types of scans,” says Associate Professor Ken Sauer, “increasingly focuses on three-dimensional data. Using any of a variety of medical imaging modalities, we create the algorithms that transform non-invasive measurements into a three-dimensional map of a particular section of the body.”

Ken Sauer Research
The algorithms developed through the collaborative efforts of Notre Dame, GE Healthcare, and Purdue University are designed to run on the GE Lightspeed VCT scanner, shown here.

Sauer’s tomographic research, supported by the Indiana 21st Century Research and Technology Fund and the General Electric Corporation (GE) and in collaboration with researchers from Indiana University and Purdue University, focuses on two types of imaging: emission and transmission. In transmission imaging, such as an X-ray or CT scan, the image is constructed from the amount of radioactivity that transmits through the patient. In emission imaging, such as positron emission tomography (PET), the patient either inhales or is injected with a radioactive isotope whose subsequent emissions can be measured by medical personnel using the scanning equipment. For example, some tumors absorb certain types of glucose at higher rates than healthy tissue. When this glucose is tagged with radioactive tracers, the signals sent back during the scan can help identify the location and size of the tumor, as well as how active it is.

“What is different about the methods we use” says Sauer, “is that they’re based directly on the statistics of the data. We assume the data received from imaging techniques has problems. For instance, since only a limited amount of radioactive material can be injected into a patient, the signals from those isotopes can be relatively weak. So we explicitly include those limitations of quality in our inverse problem solutions to create more accurate images using less radiation (reducing a patient’s exposure to radiation).”