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MR Image Reconstruction from Raw Data
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Spatial Frequency Domain  |
Fourier Transform (FT) |
Spatial Domain  |
| In MRI, the raw data is acquired in spatial frequency space, as shown above on the left. Notice that most of the raw data is centered about the origin of frequency space. Low spatial frequencies contain most of the information about the image, including gross structural features and contrast. On the other hand, high spatial frequencies at the periphery of frequency space contain information about fine details and edges -- places in the image where the signal intensity varies abruptly from one pixel to the next. A 2-D Fourier Transform (FT) is applied to the raw data to reconstruct the image from the spatial frequency data. The reconstructed image is a phantom object used for testing purposes in MRI, with components of varying size, shape, and material. | ||
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Fourier Transform (FT) |
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Low pass filtering attenuates high frequency data and passes low frequency data, as shown by the crude low-pass filter above left. Since the raw data is comprised mostly of low spatial frequencies, most of the original data will be preserved, and the reconstructed image will look fairly similar to the original image -- just a little blurrier. The blurring is caused by the fact that the high spatial frequencies, which contain information about edges in the image, are lost. |
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Fourier Transform (FT) |
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High pass filtering attenuates low frequencies and passes high frequencies, as shown by the crude high pass filter above left. Therefore most of the major features and constrast of the original image are lost in the reconstructed image; however, the edges are clearly visible because high frequency data has been preserved. |
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Anja Brau Department of Biomedical Engineering Center for In Vivo Microscopy |
