Application of Image Processing Functions for Brain Tumor Enhancement in Intraoperative Ultrasound Image Data

dc.contributor.authorChalopin, Claireen_US
dc.contributor.authorMbuyamba, Elisee Ilungaen_US
dc.contributor.authorAragon, Jesus Guillermo Cabalen_US
dc.contributor.authorRodriguez, Juan Carlos Camachoen_US
dc.contributor.authorArlt, Felixen_US
dc.contributor.authorCervantes, Juan Gabriel Avinaen_US
dc.contributor.authorMeixensberger, Juergenen_US
dc.contributor.authorLindner, Dirken_US
dc.contributor.editorStefan Bruckner and Anja Hennemuth and Bernhard Kainz and Ingrid Hotz and Dorit Merhof and Christian Riederen_US
dc.date.accessioned2017-09-06T07:12:40Z
dc.date.available2017-09-06T07:12:40Z
dc.date.issued2017
dc.description.abstractIntraoperative ultrasound (iUS) imaging supports neurosurgeons significantly during brain tumor operations. At the beginning of the intervention the integration of the iUS image data within the navigation system guides the surgeon by optimally planning the position and size of the skull opening. After tumor resection, the visualization of the iUS image data enables to identify possible tumor residuals. However, the iUS image data can be complex to interpret. Existing segmentation and registration functions were assembled into pipeline to enhance brain tumor contours in the 3D iUS image data. A brain tumor model, semi-automatically segmented in the preoperative MR data of patients, is rigidly registered with the 3D iUS image using image gradient information. The contour of the registered tumor model is visualized on the monitor of the navigation system. The rigid registration step was offline evaluated on 15 patients who overcame a brain tumor operation. The registered tumor models were compared with manual segmentations of the brain tumor in the 3D iUS data. Averaged DSI values of 82.3% and 68.4% and averaged contour mean distances of 1.7 mm and 3.3 mm were obtained for brain metastases and glioblastomas respectively. Future works will include the improvement of the functions in the pipeline, the integration of the pipeline into a centralized assistance system including further fonctionalities and connected with the navigation system, and the evaluation of the system during brain tumor operations.en_US
dc.description.sectionheadersApplications
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20171242
dc.identifier.isbn978-3-03868-036-9
dc.identifier.issn2070-5786
dc.identifier.pages103-111
dc.identifier.urihttps://doi.org/10.2312/vcbm.20171242
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20171242
dc.publisherThe Eurographics Associationen_US
dc.subjectCCS Concepts
dc.subjectComputing methodologies
dc.subject3D imaging
dc.subjectImage segmentation
dc.titleApplication of Image Processing Functions for Brain Tumor Enhancement in Intraoperative Ultrasound Image Dataen_US
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