James Pipe, University of Michigan Medical School
Left port: Cropped/Sliced data set.
Right port: Mask data set.
SHOW MASK: (toggle)
This is OFF, no mask data is created for the right port. This is useful for faster throughput of this module as well as reducing memory requirements.crop n/slice n: (radio buttons)
Indicates whether to crop or to slice dimension ndim n begin: (islider)
Indicates the first index to crop from in dimension ndim n end: (islider)
Indicates the last index to crop to in dimension ndim n center: (islider)
Indicates the center of the cropped region in dimension n OR the slice index along dimension ndim n width: (islider)
Indicates the width of the cropped region in dimension n
This module combines the functionality of series of the supported 'orthogonal slicer' and 'crop' modules and with some additional capabilities. For each dimension in the input data set (up to 4 dimensions), one may crop (preserve that dimension but limit its range), or slice (eliminate that dimension by choosing data from one index into that dimension) the data along that dimension. If the data is cropped along some dimension, one can specify the range either with 'begin' and 'end' indices, or by using 'center' and 'width'. Changing the value in one pair (begin/end or center/width) causes the module to the values of the other pair. If the data is sliced along any dimension, only the 'dimension center' widget remains visible; this is similar to the 'slice plane' parameter in the supported 'orthogonal slicer' module. For every dimension that is sliced, the dimensionality of the output data is reduced by 1. For instance, a 4D input data set that is sliced along dimensions 2 and 4 results in a two-dimensional output data set. The cropped/sliced data set is present at the LEFT output port. The RIGHT output port contains a 'mask' data set which is identical to the input data set EXCEPT for the data which was cropped/sliced into the left output port data set; this part of the mask (right port) data is set to zero, so that one can visualize the location in the original data set from which the cropped/sliced data came. For example, if the input is a 2D image, and dimension 2 is sliced, then the left output port will be a 1D 4-vector byte, and the right output port will be the same as the original image except for a vertical black line running through it where dimension 2 was sliced (plus perhaps some cropping along dimension 1).