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Deformation Aware Augmented Reality for Craniotomy using 3D/2D Non-rigid Registration of Cortical Vessels.
Haouchine, Nazim; Juvekar, Parikshit; Wells, William M; Cotin, Stephane; Golby, Alexandra; Frisken, Sarah.
Afiliación
  • 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; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
  • Cotin S; Massachusetts Institute of Technology, Cambdridge, MA, USA.
  • Golby A; Inria, Strasbourg, France.
  • Frisken S; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Med Image Comput Comput Assist Interv ; 12264: 735-744, 2020 Oct.
Article en En | MEDLINE | ID: mdl-33778818
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Qualitative_research Idioma: En Revista: Med Image Comput Comput Assist Interv Asunto de la revista: DIAGNOSTICO POR IMAGEM / INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: ALEMANHA / ALEMANIA / DE / DEUSTCHLAND / GERMANY

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Qualitative_research Idioma: En Revista: Med Image Comput Comput Assist Interv Asunto de la revista: DIAGNOSTICO POR IMAGEM / INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: ALEMANHA / ALEMANIA / DE / DEUSTCHLAND / GERMANY