Zero filling artifact
Zero-filling artifact in MRI refers to an artifact that can occur when the acquired data is insufficiently sampled or when interpolation techniques are used to fill in missing data points during image reconstruction. In MRI, data acquisition is often undersampled to reduce scan time or improve temporal resolution. Reconstruction using zero-filling involves filling the missing k-space data with zeros, which can lead to noticeable artifacts in the resulting images. Zero-filling artifact in MRI can cause blurring, smoothing, grid-like patterns, ghosting or replica artifacts, and loss of high-frequency information in the image.
Here are some strategies to minimize or avoid Zero-filling artifact :
Avoid excessive undersampling: Reduce the amount of undersampling in the data acquisition to avoid significant loss of information that can lead to zero-filling artifact.
Use more advanced reconstruction methods: Consider using more advanced reconstruction methods such as compressed sensing or parallel imaging, which can reduce the amount of missing data and improve image quality.
Avoid excessive undersampling: Reduce the amount of undersampling in the data acquisition to avoid significant loss of information that can lead to zero-filling artifact.
Increase the field of view (FOV): Increasing the FOV can provide additional data that can be used to improve the reconstruction and reduce zero-filling artifact.
Use higher spatial resolution: Higher spatial resolution can reduce the amount of missing data in the image and minimize the need for zero-filling.
Increase the signal-to-noise ratio (SNR): Higher SNR can provide more reliable data and reduce the impact of missing data in the reconstruction.
Use a higher number of averages: Acquire more data points by increasing the number of averages to reduce the amount of missing data and minimize the need for zero-filling.