4D Visualization

4D-THE MODERN DIMENSION

"4D" is shorthand for "four-dimensional"- the fourth dimension being time. 4D visualization takes three-dimensional images and adds the element of time to the process.

In contrast to 3D imaging diagnostic processes, 4D allows doctor to visualize internal anatomy moving in real-time. For example: Movement patterns of fetuses allows conclusions to be drawn about their development; increase of accuracy in ultrasound guided biopsies thanks to the visualization of needle movements in real time in all 3 planes. So physicians and sonographers can detect or rule out any number of issues, from vascular anomalies and genetic syndromes

Concept Of 4D Visualization

In the field of scientific visualization, the term "four dimensional visualization" usually refers to the process of rendering a three dimensional field of scalar values. While this paradigm applies to many different data sets, there are also uses for visualizing data that correspond to actual four-dimensional structures. Four dimensional structures have typically been visualized via wire frame methods, but this process alone is usually insufficient for an intuitive understanding. The visualization of four dimensional objects is possible through wire frame methods with extended visualization cues, and through ray tracing methods. Both the methods employ true four-space viewing parameters and geometry.

4D Viewing Vectors and Viewing Frustum

METHOD:

4D-HAMMER, involves the following two steps:

(1) Rigid alignment of 3D images of a given subject acquired at different time points, in order to produce a 4D image. 3D-HAMMER is employed to establish the correspondences between neighboring 3D images, and then align one image (time t) to its previous-time image (t-1) by a rigid transformation calculated from the established

correspondences.

(2) Hierarchical deformation of the 4D atlas to the 4D subject images, via a hierarchical attribute-based matching method. Initially, the deformation of the atlas is influenced primarily by voxels with distinctive attribute vectors, thereby minimizing the chances of poor matches and also reducing computational burden. As the deformation proceeds, voxels with less distinctive attribute vectors gradually gain influence over the deformation

ALGORITHM:

it uses the ray tracing algorithm