mutual information (mi) is a widely used similarity metric for multimodality image registration. however, it involves an extremely high computational time especially when it is applied to volume images. moreover, its robustness is affected by existence of local maxima. the multi-resolution pyramid approaches have been proposed to speed up the registration process and increase the accuracy of th...

to perform an accurate approach to the spine specially for fracture stabilization a 3d model of spine surgical region may improve this mechanism and it can help the surgeon to have a deeper glance to this scenario. the pre-op planning facility is another advantage of the patient spine specific model to take a chance of making guides to direct pedicle screws safely and increase the pathomechanic...

cancer registration is an important source for measuring the burden of cancer in a population. in practice, however, quite frequently incorrect patients are registered or data items can be inaccurately recorded or not recorded at all. also the process or quality of these registrations varies among countries. in this paper, we briefly discussed some statistical techniques including; mortality an...

medical image registration methods which use mutual information as similarity measure have been improved in recent decades. mutual information is a basic concept of information theory which indicates the dependency of two random variables (or two images). in order to evaluate the mutual information of two images their joint probability distribution is required. several interpolation methods, su...

purpose : to determine cyclotorsional eye movement between the upright position and the supine position, in iranian patients with high preoperative astigmatism methods : this prospective cross sectional study contains 102 eyes of 59 patients who were candidates for refractive surgery with technolas 217z100 excimer laser system for correction of high astigmatism. wavefront measurements using zyw...

Image registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources. In general, the majority of registration methods consist of the following four steps: feature extraction, feature matching, transform modeling, and finally image resampling. As the accuracy of a registration process is highly dependent to the fe...