instrument calibration matrix brainlab manual

An exhaustive taxonomy of image registration methods can be found in. The latter relies on external tracking systems, pre-calibrated instruments or manual measurements. This transformation is called image registration and requires establishing a coordinate transform by feature matching, optimizing a similarity measure or by calibration-based approaches. Image fusion requires the images to be aligned such that structures being visible in each appear at the same spatial position. The images show the same scene, yet they may have been recorded by different modalities or contain overlapping parts or both. Image fusion denotes the process of joining multiple image sources to one image. One approach to this challenge is to fusion the novel infrared thermography with prevailing imaging modalities. As intraoperative infrared thermography is used as a medical decision support system, it is important for non-technical personnel to interpret thermographic images as well as results originating from data analysis workflows. This introduces additional challenges when transferring information from infrared thermography to surgical staff. However, thermographic images are difficult to analyze as the infrared camera operates on a different spectrum than human visual perception. who unveiled the cortical perfusion by intraoperative infrared thermography. One such application was demonstrated by Steiner et al. In neurosurgery, the temperature distribution of the brain’s surface may help to differentiate between healthy and tumor tissue. According to the Stefan-Boltzmann law, this radiation correlates with the temperature of the object. Infrared thermography measures the emitted infrared radiation of the exposed cerebral cortex during neurosurgical interventions. In extensive accuracy measurements, we found that the proposed framework achieves a mean accuracy of 2.46 mm. The registered image data are now combined by calibration-based image fusion in order to map our intraoperative 2D thermographic images onto the respective brain surface recovered from preoperative MRI. Hereby, we are able to relate the 2D coordinate system of the infrared camera with the 3D MRI coordinate system. Image-guided neurosurgeries are based on neuronavigation systems, which further allow us track the position and orientation of arbitrary cameras. While previous applications mainly focus on merging images from computed tomography, magnetic resonance imaging (MRI), ultrasonic and single-photon emission computed tomography, we propose a novel approach for the registration and fusion of preoperative 3D MRI with intraoperative 2D infrared thermography. Multimodal medical image fusion combines information of one or more images in order to improve the diagnostic value.

Instrument calibration matrix brainlab manual