Figure 4.

(a) A time series of dynamic cardiac images is shown, where the x-y plane shows the images, and the t axis depicts the time dimension (left). Three different images of the heart show the motion that occurs through time (right). (b) When one frame from the dynamic dataset is subtracted from another, the result is a sparser image because many tissues are stationary from frame to frame. Only pixels near the heart change, and these are reflected in the temporal difference image. (c) The 3D space-time data can be examined along one slice of the x-t plane (left), designated by the white dotted line. The areas with significant motion can be clearly seen in the “x-t space” image (middle). If a Fourier transform is applied to the x-t space in the time direction, the result is the image representation in the spatiotemporal domain (x-f space, right). Static areas of the image will only have a single bright pixel in the x-f space (orange arrow), and only pixels with significant motion will contribute many non-zero pixels (purple arrow), making x-f space sparse in many dynamic applications.