Time-efficient and easy-to-use segmentation algorithms (contour generation) are a precondition for various applications in radiation oncology, especially for planning purposes in hyperthermia. We have developed the three following algorithms for contour generation and implemented them in an editor of the HyperPlan hyperthermia planning system. Firstly, a manual contour input with numerous correction and editing options. Secondly, a volume growing algorithm with adjustable threshold range and minimal region size. Thirdly, a watershed transformation in two and three dimensions. In addition, the region input function of the Helax commercial radiation therapy planning system was available for comparison. All four approaches were applied under routine conditions to two-dimensional computed tomographic slices of the superior thoracic aperture, mid-chest, upper abdomen, mid-abdomen, pelvis and thigh; they were also applied to a 3D CT sequence of 72 slices using the three-dimensional extension of the algorithms. Time to generate the contours and their quality with respect to a reference model were determined. Manual input for a complete patient model required approximately 5 to 6 h for 72 CT slices (4.5 min/slice). If slight irregularities at object boundaries are accepted, this time can be reduced to 3.5 min/slice using the volume growing algorithm. However, generating a tetrahedron mesh from such a contour sequence for hyperthermia planning (the basis for finite-element algorithms) requires a significant amount of postediting. With the watershed algorithm extended to three dimensions, processing time can be further reduced to 3 min/slice while achieving satisfactory contour quality. Therefore, this method is currently regarded as offering some potential for efficient automated model generation in hyperthermia. In summary, the 3D volume growing algorithm and watershed transformation are both suitable for segmentation of even low-contrast objects. However, they are not always superior to user-friendly manual programs for contour generation. When the volume growing algorithm is used, the contours have to be postprocessed with suitable filters. The watershed transformation has a large potential if appropriately developed to 3D sequences and 3D interaction features. After all, the practicality and feasibility of every segmentation method critically depend on various details of the user software as pointed out in this article.
For a hyperthermia planning environment the main requirements for the following numerical computation and visualization of the temperature field are the separation of several anatomical objects. Since different contrast objects cannot be seen at the same resolution, a segmentation technique using multiresolution segmentation planes is described here. The computation of these planes is based on the technique of region growing using watersheds in digital images. First, the watershed transformation is applied on the gradient image. The resulting image is then transformed into a graph on which a region growing process is performed. The iteration of these two actions results in hierarchical segmentation planes which differ in region amount and region size. Consequently low contrast objects can be separated in the lower planes whereas high contrast objects can be extracted in the higher planes.
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