Rolf A. Heckemann MD PhD
Professor
MedTech West
Röda stråket 10B
Sahlgrenska University Hospital
413 45 Göteborg
Sweden

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Rolf A. Heckemann MD PhD
Professor of Medical Imaging and Image Analysis


MedTech West
Röda stråket 10B
Sahlgrenska University Hospital
413 45 Göteborg
Sweden


Email: rolf.heckemann@medtechwest.se

Research Mission To discover novel ways of detecting disease and predicting outcomes using medical imaging.

Medical doctors today have at their disposal a marvellous range of technologies for taking pictures from inside the living body. The venerable projection radiograph using X-rays is still a mainstay of diagnostic imaging over a hundred years after its invention. More recently, other modalities have been developed that employ a variety of probes to show the structure as well as the function of the human body (CT, MRI, ultrasonography, PET, SPECT, and others). The amount of image data obtained each time a patient is scanned is vast, and it has to be boiled down to the salient information. This is image interpretation: understanding images so as to know whether and how to treat the patient. Image interpretation is a highly developed skill: diagnostic radiology training takes years in addition to basic medical training. It also takes time: a single patient's CT of the abdomen, for example, can have many hundreds of slices that need to be reviewed. Human expertise is thus the bottleneck in the system. In fact, more generally, our capability to generate images exceeds our capability to understand them.

In my research, I look for ways to automatically extract information from images. For this, I employ cutting-edge computer algorithms, for example for image registration. One approach is to identify anatomical structures (image segmentation) and to measure their volume, extent, and shape. Such properties, termed morphometric descriptors, can be used for statistical comparisons between subjects. If a morphometric descriptor is systematically different in patients with a disease, or if it is systematically associated with a certain outcome, it has potential as a marker for diagnosing that disease or for predicting the outcome. Such markers can help radiologists make better diagnostic decisions.

Part of my calling is to build bridges between engineering and clinical medicine. Theoretical advances in mathematics and informatics need to be translated into practical tools for doctors and ultimately benefit people who are ill.

Achievements



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