Restoration of nuclear medicine images using a Kalman filtering approach

Thomas Schmitt; Heinz-Dieter Gebauer; Richard Freyer; Liane Oehme; Wolf-Gunter Franke

doi:10.1117/12.205494

23 March 1995 Restoration of nuclear medicine images using a Kalman filtering approach

Thomas Schmitt, Heinz-Dieter Gebauer, Richard Freyer, Liane Oehme, Wolf-Gunter Franke

Proceedings Volume 2421, Image and Video Processing III; (1995) https://doi.org/10.1117/12.205494
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

Abstract

The discrepancy between diagnostic importance of nuclear medicine images and their quality and the predominating visual interpretation of the images demand quality improvements. Digital image restoration procedures are known for being capable to solve this problem considering both noise and blurring. In this paper we propose the application of a modified 2D Kalman filter for nuclear medicine images (SPECT). In addition to the special capability of processing instationary signals the Kalman filter offers a possibility for controlling the filtering effect in a convenient way. The Kalman filter is based on a state space approach subdividing the imaging process into image generation and image degradation processes. The tested filter operates adaptively by permanent identification of the image generation model. For adaptation to the human visual system the filtering effect is modified depending on image quality represented by the mean information density and the local image contents represented by a structure information. The appropriate filtering effect is determined by modifying filter parameters with a predefined piecewise linear characteristic curve. The both smoothing and structure enhancing effect of our Kalman filtering approach is demonstrated in numerous tests performed with SPECT phantom images and brain SPECT studies.

Citation Download Citation

Thomas Schmitt, Heinz-Dieter Gebauer, Richard Freyer, Liane Oehme, and Wolf-Gunter Franke "Restoration of nuclear medicine images using a Kalman filtering approach", Proc. SPIE 2421, Image and Video Processing III, (23 March 1995); https://doi.org/10.1117/12.205494

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