Interpolating and Removing Image Slices
If unrepresentative slices are present within a dataset, the use of some available analysis tools may be restricted. For example, an image with major stains might significantly affect the histogram of the intensity distribution and prevent the correct evaluation of automatic thresholding for segmentation. Removing the slice or replacing it with representative information taken from the closest slices could avoid this problem. Unrepresentative slices might also cause problems for segmentation algorithms that assume continuity in the direction of slices.
Interpolating Image Slices
Image slices that are marked for interpolation are first removed from the dataset and then replaced by a linear weighted interpolation from adjacent slices. For example, if slices 4 and 5 are marked, slices 3 and 6 will serve as references. The data of slice 4 will be replaced by the data of slice 3 weighted by 2/3, summed to the data of slice 6 weighted by 1/3. The data of slice 5 will be replaced by the data of slice 3 weighted by 1/3, summed to the data of slice 6 weighted by 2/3.
You should note that if a marked slice is located at the beginning or end of the stack, its data will be replaced by the closest unmarked slice. This is done to preserve the shape of the dataset, including the number of slices, volume, spacing between slices, and so on.
How to Interpolate Image Slices
- Mark the image slices that you need to interpolate (see Marking Image Slices).
- Right-click a 2D view and then choose Simple Marked Slice Replacement in the pop-up menu.
Interpolation is applied automatically to the marked slices in the dataset.
Removing Image Slices
In cases in which unrepresentative slices are present within a dataset, and interpolating image slices is insufficient or not required, you can simply remove them. You should note that applying this operation will alter the shape of the dataset, in particular, the number of slices and its volume. You should also note that if this operation is applied to a time-enabled dataset, marked slices will be removed at each time step. For example, if you mark slice 20 in a time-enabled dataset with 3 time steps, then slice 20 will be removed at T1, T2, and T3.
How to Remove Image Slices
- Mark the image slices that you need to remove (see Marking Image Slices).
- Right-click a 2D view of the marked dataset and then choose Remove All Marked Slices in the pop-up menu.
The marked slices are automatically removed from the dataset.
