Correction is done by translating the image by a value equal to the difference between the measured centre and the fitted sine for each angle. Image segmentation Extracting seeds from fluoroscopic images is not an easy task. Grey level does not provide much information since the surrounding bones can have the same grey level value as the seeds. Presence of noise, scattering and low-contrast make the task even more difficult. One solution for this problem is mathematical morphology.
Mathematical morphology is a powerful, shaped-based method often used in image processing.
Results obtained using morphological top-hat opening, as well as an example of image enhancement, are shown in Figure 2. Reconstruction Three-films based methods allow reconstruction of seed centre only. It would be particularly useful to be able to reconstruct the shape of the seeds in 3D space. Using reconstructed shapes, one can also find the orientation of the seeds, which is valuable information for treatment planning. There is also a lot of other applications, for example locating the catheter during the operation.