| Literature DB >> 28110313 |
Nico Hoffmann1, Florian Weidner1, Peter Urban1, Tobias Meyer1, Christian Schnabel1, Yordan Radev1, Gabriele Schackert1, Uwe Petersohn1, Edmund Koch1, Stefan Gumhold1, Gerald Steiner1, Matthias Kirsch1.
Abstract
Multimodal medical image fusion combines information of one or more images in order to improve the diagnostic value. 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. Image-guided neurosurgeries are based on neuronavigation systems, which further allow us track the position and orientation of arbitrary cameras. Hereby, we are able to relate the 2D coordinate system of the infrared camera with the 3D MRI coordinate system. 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. In extensive accuracy measurements, we found that the proposed framework achieves a mean accuracy of 2.46 mm.Keywords: image fusion; image-guided neurosurgery; infrared thermography; magnetic resonance imaging; neurosurgery
Mesh:
Year: 2017 PMID: 28110313 DOI: 10.1515/bmt-2016-0075
Source DB: PubMed Journal: Biomed Tech (Berl) ISSN: 0013-5585 Impact factor: 1.411