PURPOSE: To develop an automatic registration method for electrocardiogram-gated myocardial perfusion single-photon emission computed tomography (SPECT) and cardiac cine-magnetic resonance imaging (MRI). MATERIALS AND METHODS: Paired myocardial perfusion SPECT (MPS) and MRI from 20 patients were considered. MR images were presegmented by heart localization based on detection of cardiac motion and optimal thresholding. A registration algorithm based on mutual information was subsequently applied to all time frames or a selected subset from both modalities. RESULTS: A preprocessing step significantly improved the accuracy of the registration when compared to automatic registration performed without preprocessing. Errors in translation parameters (T(x), T(y), T(z)) averaged (1.0 +/- 1.5, 1.1 +/- 1.3, 0.9 +/- 0.9) pixels with MRI segmentation and (4.6 +/- 3.2, 3.4 +/- 2.6, 3.0 +/- 3.4) pixels without MRI segmentation. Errors in rotation parameters (R(x), R(y), R(z)) averaged (5.4 +/- 2.9, 3.4 +/- 2.7, 4.5 +/- 3.6) degrees with MRI segmentation and (9.3 +/- 6.1, 4.8 +/- 4.3, 14.6 +/- 12.6) degrees without MRI segmentation. Error was calculated as the absolute difference between the expert manual and the automatic registration transformation. CONCLUSION: Automatic registration of gated MPS and cine MRI is possible with the use of a mutual information-based technique when MR images are presegmented. Cardiac motion can be used to isolate the left ventricle (LV) on the MR images automatically, and subsequently the segmented MR images can be coregistered with gated MPS. Copyright 2004 Wiley-Liss, Inc.
PURPOSE: To develop an automatic registration method for electrocardiogram-gated myocardial perfusion single-photon emission computed tomography (SPECT) and cardiac cine-magnetic resonance imaging (MRI). MATERIALS AND METHODS: Paired myocardial perfusion SPECT (MPS) and MRI from 20 patients were considered. MR images were presegmented by heart localization based on detection of cardiac motion and optimal thresholding. A registration algorithm based on mutual information was subsequently applied to all time frames or a selected subset from both modalities. RESULTS: A preprocessing step significantly improved the accuracy of the registration when compared to automatic registration performed without preprocessing. Errors in translation parameters (T(x), T(y), T(z)) averaged (1.0 +/- 1.5, 1.1 +/- 1.3, 0.9 +/- 0.9) pixels with MRI segmentation and (4.6 +/- 3.2, 3.4 +/- 2.6, 3.0 +/- 3.4) pixels without MRI segmentation. Errors in rotation parameters (R(x), R(y), R(z)) averaged (5.4 +/- 2.9, 3.4 +/- 2.7, 4.5 +/- 3.6) degrees with MRI segmentation and (9.3 +/- 6.1, 4.8 +/- 4.3, 14.6 +/- 12.6) degrees without MRI segmentation. Error was calculated as the absolute difference between the expert manual and the automatic registration transformation. CONCLUSION: Automatic registration of gated MPS and cine MRI is possible with the use of a mutual information-based technique when MR images are presegmented. Cardiac motion can be used to isolate the left ventricle (LV) on the MR images automatically, and subsequently the segmented MR images can be coregistered with gated MPS. Copyright 2004 Wiley-Liss, Inc.
Authors: Anu Juslin; Jyrki Lötjönen; Sergey V Nesterov; Kari Kalliokoski; Juhani Knuuti; Ulla Ruotsalainen Journal: J Nucl Cardiol Date: 2007-01 Impact factor: 5.952
Authors: Jonghye Woo; Piotr J Slomka; Damini Dey; Victor Y Cheng; Byung-Woo Hong; Amit Ramesh; Daniel S Berman; Ronald P Karlsberg; C-C Jay Kuo; Guido Germano Journal: Med Phys Date: 2009-12 Impact factor: 4.071
Authors: Jonghye Woo; Piotr J Slomka; Damini Dey; Victor Cheng; Amit Ramesh; Byung-Woo Hong; C-C Jay Kuo; Daniel S Berman; Guido Germano Journal: Proc IEEE Int Symp Biomed Imaging Date: 2009
Authors: Piotr J Slomka; Victor Y Cheng; Damini Dey; Jonghye Woo; Amit Ramesh; Serge Van Kriekinge; Yasuzuki Suzuki; Yaron Elad; Ronald Karlsberg; Daniel S Berman; Guido Germano Journal: J Nucl Med Date: 2009-09-16 Impact factor: 10.057