Neurosurgical Craniotomy Localization Using Interactive 3D Lesion Mapping for Image-Guided Neurosurgery
Precise craniotomy localization is essential in neurosurgical procedures, especially during the preoperative planning. The mainstream craniotomy localization method utilizing image-guided neurosurgery system (IGNS) or augmented reality (AR) navigation system require experienced neurosurgeons to poin...
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Veröffentlicht in: | IEEE access 2019, Vol.7, p.10606-10616 |
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Sprache: | eng |
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Zusammenfassung: | Precise craniotomy localization is essential in neurosurgical procedures, especially during the preoperative planning. The mainstream craniotomy localization method utilizing image-guided neurosurgery system (IGNS) or augmented reality (AR) navigation system require experienced neurosurgeons to point out the lesion margin by probe and draw the craniotomy manually on the patient's head according to cranial anatomy. However, improper manual operation and dither from the AR model will bring in errors about craniotomy localization. In addition, there is no specific standard to evaluate the accuracy of craniotomy. This paper attempts to propose a standardized interactive 3D method using orthogonal transformation to map the lesion onto the scalp model and generate a conformal virtual incision in real time. Considering clinical requirements, the incision can be amended by 3D interaction and margin modification. According to the IGNS and the virtual incision, an actual craniotomy will be located on the patient's head and the movement path of the probe will be recorded and evaluated by an indicator, which is presented as an evaluated standard to measure the error between virtual and actual craniotomies. After the experiment, an incision is drawn on a 3D printing phantom based on the generated virtual one. The results show that the proposed method can generate a lesion-consistent craniotomy according to the size of the lesion and the mapping angle and delineate the incision on the patient's head precisely under the IGNS. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2019.2890977 |