In neurosurgery, navigation is being used to improve surgical orientation by using preoperative
images as a roadmap. Skin or bone fiducials couple the image coordinate system to
that of the patient's head fixed by the Mayfield clamp. Then the tip of a pointer of another
instrument (localization device) can be seen in relation to the image to give the surgeon
insight where he/she is in the brain and where the tumor or lesion can be expected in the
depth.
Drawbacks from current navigation systems are that 1) they only show the actual
position of the localization device and thus do not hint whether the surgeon has removed the
tumor completely, 2) don't warn when the device is about to hit a critical brain structure, and
3) do not compensate for shifts of the brain during surgery invalidating the pre-operative
image data.
During the last 5 years we investigated in our hospital whether sound and workflow
feedback could improve the surgical resection accuracy and looked how the pre-operative
image data could be deformed in real-time using GPU hardware to match the tracked cortical
surface to compensate for brain shifts.
Processing large images files or real-time video streams requires intense computational power. Driven by the gaming
industry, the processing power of graphic process units (GPUs) has increased significantly. With the pixel shader model
4.0 the GPU can be used for image processing 10x faster than the CPU. Dedicated software was developed to deform
3D MR and CT image sets for real-time brain shift correction during navigated neurosurgery using landmarks or cortical
surface traces defined by the navigation pointer. Feedback was given using orthogonal slices and an interactively raytraced
3D brain image. GPU based programming enables real-time processing of high definition image datasets and
various applications can be developed in medicine, optics and image sciences.
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