Lossless Scalable Representations of Hyper-Volume Data Using Compensated Wavelet Lifting

Beschreibung

Hyper-volume data have three or more dimensions and play a very important role especially in the medical environment. Computed Tomography and Magnetic Resonance Imaging allow insights into the patient and became invaluable for medical diagnosis. The size of the hyper-volume data can quickly become very large and unhandy. To obtain scalable representations of hyper-volume data with a very high quality, various aspects of the concept of compensated wavelet lifting are analyzed and improvements are developed. The data acquisition and data characteristics are taken into account. Different compensation methods are analyzed to compensate the deforming displacements within dynamic medical hyper-volume data. In addition to the scalable representation, lossless reconstruction plays an essential role.

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Wolfgang Schnurrer

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