Background-suppressed MR venography of the brain using magnitude data: a high-pass filtering approach.
Zhaoyang JinE Ling XiaMinming ZhangYiping P DuPublished in: Computational and mathematical methods in medicine (2014)
Conventional susceptibility-weighted imaging (SWI) uses both phase and magnitude data for the enhancement of venous vasculature and, thus, is subject to signal loss in regions with severe field inhomogeneity and in the peripheral regions of the brain in the minimum-intensity projection. The purpose of this study is to enhance the visibility of the venous vasculature and reduce the artifacts in the venography by suppressing the background signal in postprocessing. A high-pass filter with an inverted Hamming window or an inverted Fermi window was applied to the Fourier domain of the magnitude images to enhance the visibility of the venous vasculature in the brain after data acquisition. The high-pass filtering approach has the advantages of enhancing the visibility of small veins, diminishing the off-resonance artifact, reducing signal loss in the peripheral regions of the brain in projection, and nearly completely suppressing the background signal. The proposed postprocessing technique is effective for the visualization of small venous vasculature using the magnitude data alone.
Keyphrases
- resting state
- electronic health record
- white matter
- big data
- functional connectivity
- image quality
- cerebral ischemia
- high resolution
- computed tomography
- signaling pathway
- early onset
- photodynamic therapy
- convolutional neural network
- multiple sclerosis
- blood brain barrier
- quantum dots
- drug induced
- fluorescence imaging
- energy transfer