Wavelet based noise reduction in CT-images using correlation analysis

Beitrag in einer Fachzeitschrift

Details zur Publikation

Autorinnen und Autoren: Borsdorf A, Raupach R, Flohr T, Hornegger J
Zeitschrift: IEEE Transactions on Medical Imaging
Verlag: Institute of Electrical and Electronics Engineers (IEEE)
Jahr der Veröffentlichung: 2008
Band: 27
Heftnummer: 12
Seitenbereich: 1685-1703
ISSN: 0278-0062


The projection data measured in computed tomography (CT) and, consequently, the slices reconstructed from these data are noisy. We present a new wavelet based structure-preserving method for noise reduction in CT-images that can be used in combination with different reconstruction methods. The approach is based on the assumption that data can be decomposed into information and temporally uncorrected noise. In CT two spatially identical images can be generated by reconstructions from disjoint subsets of projections: using the latest generation dual source CT-scanners one image can be reconstructed from the projections acquired at the first, the other image from the projections acquired at the second detector. For standard CT-scanners the two images can be generated by splitting up the set of projections into even and odd numbered projections. The resulting images show the same information but differ with respect to image noise. The analysis of correlations between the wavelet representations of the input images allows separating information from noise down to a certain signal-to-noise level. Wavelet coefficients with small correlation are suppressed, while those with high correlations are assumed to represent structures and are preserved. The final noise-suppressed image is reconstructed from the averaged and weighted wavelet coefficients of the input images. The proposed method is robust, of low complexity and adapts itself to the noise in the images. The quantitative and qualitative evaluation based on phantom as well as real clinical data showed, that high noise reduction rates of around 40% can be achieved without noticable loss of image resolution. © 2008 IEEE.

FAU-Autorinnen und Autoren / FAU-Herausgeberinnen und Herausgeber

Hornegger, Joachim Prof. Dr.-Ing.
Lehrstuhl für Informatik 5 (Mustererkennung)

Einrichtungen weiterer Autorinnen und Autoren

Siemens AG, Healthcare Sector


Borsdorf, A., Raupach, R., Flohr, T., & Hornegger, J. (2008). Wavelet based noise reduction in CT-images using correlation analysis. IEEE Transactions on Medical Imaging, 27(12), 1685-1703. https://dx.doi.org/10.1109/TMI.2008.923983

Borsdorf, Anja, et al. "Wavelet based noise reduction in CT-images using correlation analysis." IEEE Transactions on Medical Imaging 27.12 (2008): 1685-1703.


Zuletzt aktualisiert 2019-16-04 um 14:50