Department of Mathematics, Applied Mathematics and Statistics

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ImagingWe live in the society of images. Communication relies increasingly on the power of images as means of quick information transfer, and the human brain is amazingly effective in extracting salient information from images. The scientific communication is no exception: the use of images has become a central protocol for instance in medicine, where ever more sophisticated imaging modalities are introduced and further developed to retrieve information of the anatomy, structure and functioning of the living human body. Computerized imaging relies heavily on sophisticated mathematics, and mathematical imaging is a growing and active research field. The field of imaging can be divided in different subclasses:

Image formation: the goal is to form an image of an object based on indirect information. Computerized X-ray tomography is an outstanding and classical example of image formation: three-dimensional image of the human body is formed based on several transmission projections of it.

Image processing: given an image containing undesired qualities such as blurredness, noise, scratches or occlusions, the goal is to restore a higher quality image by removing the flaws using complementary information and introducing minimum amount of artifacts or ambiguities.

Image analysis: a raw image may contain a feature of interest, but the feature is masked by inessential details in the image. The challenge is to develop methods that are able to automatically extract pertinent information of an image without relying on an expert eye.

The imaging research at the department at Case addresses several aspects and challenges in the imaging field, and there is a strong connection to the biomedical research that routinely uses imaging techniques.



Daniela Calvetti

Julia Dobrosotskaya

Weihong Guo

Steven Izen

Erkki Somersalo

Page last modified: January 20, 2017