TwinTree Insert

15-07 Three-Dimensional Visualization

s with most imaging modalities, MR imaging data are normally presented as two-dimensional gray-scale images. However, MR imaging is essentially a 3D method and can produce three-dimensional data sets of virtually any body organ [⇒ Aichner 1994].

The simplest way of visualizing such data sets is by letting ra­dio­lo­gist flip through the set displayed as slices of 2D images, leaving it up to them to visualize the struc­tu­res.

Whereas this approach is suitable for some purposes, like diagnosis, it is less suit­able for other purposes, like surgical plan­ning or radiotherapy planning.

Thus, there is a need for 3D visualization tech­ni­ques.

By performing segmentation, surface- or volume-rendering techniques can be ap­plied [⇒ Maintz 1998]. The advantage of surface-rendering techniques is that they are easy and fast to visualize and manipulate (by rotation, zooming, etc.).

Since a segmentation has been done, it is possible to manipulate the 3D data set by re­mov­ing tissues, request volumes and sizes.

The dis­ad­van­tage is that segmentation of the data is required before visualization can be performed, and that some information is lost in the segmentation step. An al­ter­na­tive technique is volume-rendering. Volume-rendering does not require seg­men­ta­tion.

However, the method requires more powerful computers to be fully interactive, and nor­mal­ly some interaction to visualize structures of interest (Figure 15-12) [⇒ Tiede 1994].

Figure 15-12:
Dissection of an MR imaging-based head model. A wire mesh is used to define cut planes. Similar re­con­struc­tions can be used in surgery and ra­dia­tion the­ra­py plan­ning. One of the main problems in 3D image-processing is that objects within the 3D domain may obscure each other. Therefore any vi­su­a­li­za­tion must be pre­ced­ed by a segmentation step in which 3D regions belonging to an organ must be iden­­ti­­fied.