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Learning Expected Appearances for Intraoperative Registration during Neurosurgery.
Haouchine, Nazim; Dorent, Reuben; Juvekar, Parikshit; Torio, Erickson; Wells, William M; Kapur, Tina; Golby, Alexandra J; Frisken, Sarah.
Afiliación
  • Haouchine N; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
  • Dorent R; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
  • Juvekar P; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
  • Torio E; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
  • Wells WM; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
  • Kapur T; Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Golby AJ; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
  • Frisken S; Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Med Image Comput Comput Assist Interv ; 14228: 227-237, 2023 Oct.
Article en En | MEDLINE | ID: mdl-38371724
ABSTRACT
We present a novel method for intraoperative patient-to-image registration by learning Expected Appearances. Our method uses preoperative imaging to synthesize patient-specific expected views through a surgical microscope for a predicted range of transformations. Our method estimates the camera pose by minimizing the dissimilarity between the intraoperative 2D view through the optical microscope and the synthesized expected texture. In contrast to conventional methods, our approach transfers the processing tasks to the preoperative stage, reducing thereby the impact of low-resolution, distorted, and noisy intraoperative images, that often degrade the registration accuracy. We applied our method in the context of neuronavigation during brain surgery. We evaluated our approach on synthetic data and on retrospective data from 6 clinical cases. Our method outperformed state-of-the-art methods and achieved accuracies that met current clinical standards.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Med Image Comput Comput Assist Interv Asunto de la revista: DIAGNOSTICO POR IMAGEM / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Alemania
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Med Image Comput Comput Assist Interv Asunto de la revista: DIAGNOSTICO POR IMAGEM / INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Alemania