A High Resolution Dynamic Heart Model Based on Averaged MRI Data

We are in the process of constructing a high resolution, high signal to noise ratio (SNR) dynamic MRI dataset for the human heart using methodology similar to that employed to construct a low-noise standard brain at the Montreal Neurological Institute. Several high resolution, low SNR magnetic resonance images of 20 phases over the cardiac cycle were acquired from a single subject. Images from identical phases and temporally adjacent phases were registered, and the image intensities were averaged together to generate a high resolution, high SNR dynamic magnetic resonance image volume of the human heart. Although this work is still preliminary, and the results still demonstrate residual artifacts due to motion an sub-optimal alignment of interleaved image slices, our model has a SNR that is improved by a factor of 2.7 over a single

• Type: Conference
• Year: 2003
• Where: MICCAI
• Authors: John Moore, Maria Drangova, Marcin Wierzbicki, Terry M. Peters
• Keywords: Interleaved Image Slices, Magnetic Resonance Image, Medical Imaging, MICCAI 2003, SNR Magnetic Resonance