These programs provide various means to evaluate statistics and comparisons for series of images that stem from myocardial perfusion imaging.
This program is used to run a ICA on a series of myocardial perfusion images to create sythetic references that can be used for motion correction by image registration. If the aim is to run a full motion compensation then it is better to create a segmentation set and use mia-2dmyoica-nonrigid. If the input data is given by means of a segmentation set, then on can also use mia-2dmyocard-icaseries. This program is essentially used to test different options on how to run the ICA forreference image creation.
This program is used to run a ICA on a series of myocardial perfusion images given in a segmentation set in order to create sythetic references that can be used for motion correction by image registration. If the aim is to run a full motion compensation then it is better run mia-2dmyoica-nonrigid, since this program is essentially the same without the registration bits.
This program is used to evaluate the per-frame dice index of segmented regions of two image series
This program is used to evaluate the per-frame dice index of segmented regions of an image with respect to the segmentation of a reference frame from the same series.
This program is used to evaluate the Hausdorff distance between each frame of a perfusion time series of the input set to the corresponding frame of the reference set and prints the result to stdout.
Get the per-slice Hausdorff distance of a segmentation with respect to a given reference frame and print it to stdout.
This program is used on a segmentation set and evaluates a bounding box that encloses the segmentation in all slices. This bounding box is then used to crop the original images, correct the segmentation and store a new segmentation set with the cropped images. The cropped images will be of the same type as the original images. If no segmentation is given in the set, the result is undefined.
This program is used evaluate various time-intensity curves over a series of images given by a segmentation set. Specifically, the program is taylored to evaluate average intensities and variations of sections the left ventricle myocardium. The segmentation set must contain the segmentations for all slices that will be accessed during evaluation.
This program move the segmentation(s) of an image series by using a shift that is equal for all slices. The program also may remove images from the begin of the series. The program can be used to correct the segmentation of the images if the images where cropped.
This program move the segmentation(s) of an image series by using a shift that is given on a per-slice base. The program can be used to correct the segmentation of the images if a linear registration was executed that only applies a translation and does not correct the segmentation automatically.
Given a set of images of temporal sucession, this program evaluates the minimal correlation of the time-intensity curve between neighboring pixels.
Evaluate the masks for the sections of a segmented frame.
Get the mean distance of a segmentation boundary to the reference boundary.
This program evaluates the pixel-wise median of the absolute values of the gauss filtered 2nd order temporal derivative of a series of images. In addition, it can be used to output the time-intensity curve of a given pixel.The program supports slice-wise spacial pre-filtering by giving additional filters as free parameters (filter/2dimage).
This program takes all image files that are given as free parameters on the command line and creates segmentation sets based on information found in the images. Used information is the z-location of the slice and the acquisition number. The code is taylored to used the according descriptors defined in the DICOM standard. All images with the same slice location will be grouped together in one segmentation set and ordered according to their aquisition number. Slice locations are rounded to three digits accuracy to make proper comparison of floating point values feasable.
Given a set of images of temporal sucession, evaluates images that represent the time-intensity correlation in horizontal and vertical direction as well as average correlation of each pixel with its neighbors. All input images must be of the same pixel type and size.
Given a set of images of temporal sucession, evaluates the pixel-wise temporal gradient and then its median average distance (MAD) and stores the result in an image. Spacial pre-filtering may be applied as given additional plugin(s) (filter/2dimage).
Given a set of images of temporal sucession, this program evaluates the gradient variation of the pixel-wise time-intensity curves of this series. If the input image set provides a segmentation, then this segmentation can be used to create a bounding box and restrict evaluation to this box.
Get the per-slice Hausdorff distance of a segmentation with respect to a given reference segmentation set.
Given a set of images of temporal sucession, evaluate the temporal pixel-wise gaussian and evaluate pixel-wise its MAD.A spacial pre-filtering may be applied by specifying additional plugins (filter/2dimage)
Obtaines a 3D volume image by combining the images of the segmentation set.