Deformation Aware Augmented Reality for Craniotomy using 3D/2D Non-rigid Registration of Cortical Vessels.

Autor: Haouchine N; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA., Juvekar P; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA., Wells WM 3rd; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.; Massachusetts Institute of Technology, Cambdridge, MA, USA., Cotin S; Inria, Strasbourg, France., Golby A; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA., Frisken S; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Jazyk: angličtina
Zdroj: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention [Med Image Comput Comput Assist Interv] 2020 Oct; Vol. 12264, pp. 735-744. Date of Electronic Publication: 2020 Sep 29.
DOI: 10.1007/978-3-030-59719-1_71
Abstrakt: Intra-operative brain shift is a well-known phenomenon that describes non-rigid deformation of brain tissues due to gravity and loss of cerebrospinal fluid among other phenomena. This has a negative influence on surgical outcome that is often based on pre-operative planning where the brain shift is not considered. We present a novel brain-shift aware Augmented Reality method to align pre-operative 3D data onto the deformed brain surface viewed through a surgical microscope. We formulate our non-rigid registration as a Shape-from-Template problem. A pre-operative 3D wire-like deformable model is registered onto a single 2D image of the cortical vessels, which is automatically segmented. This 3D/2D registration drives the underlying brain structures, such as tumors, and compensates for the brain shift in sub-cortical regions. We evaluated our approach on simulated and real data composed of 6 patients. It achieved good quantitative and qualitative results making it suitable for neurosurgical guidance.
Databáze: MEDLINE
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