Regensburg 2010 – wissenschaftliches Programm
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ST: Fachverband Strahlen- und Medizinphysik
ST 3: Radiation Detectors and Imaging (Poster Session)
ST 3.4: Poster
Montag, 22. März 2010, 14:30–15:30, H41
MAR in CBCT using reconstructed data and mutual information realigment — •Manuel Meilinger1,2, Christian Schmidgunst2, OIiver Schütz2, and Elmar Lang1 — 1Computational Intelligence and Machine Learning Group, Institut für Biophysik, Universität Regensburg, Regensburg, Deutschland — 2Siemens Healthcare, Erlangen, Deutschland
High-density objects, especially metal implants or particles, generate various artifacts in cone-beam computed tomography (CBCT) images much like in computed tomography images. We present a novel method for metal artifact reduction in CBCT images via virtual replacement of the corrupted information in the 3D volume with objects of identical geometry but convenient attenuation coefficients. An additional correction based on mutual information needs to be applied to the distorted reconstruction and projection in case of CBCT images to compensate for artifacts due to mechanical instabilities of mobile C-arm systems. A reconstruction of the adapted 2D projection images generates a second 3D volume, where the original metal objects are replaced by tissue and the streak-like artifacts are clearly reduced. After that the segmented metal parts of the first 3D volume must be transfered into the metal and artifact free 3D volume of the second reconstruction. The proposed method is applied to clinical images and shows superior performance. The resulting reconstructed images show much reduced streak-like artifacts and related shadows.