Anzeige
Erschienen in:
2018 | OriginalPaper | Buchkapitel
Initialize Globally Before Acting Locally: Enabling Landmark-Free 3D US to MRI Registration
verfasst von : Julia Rackerseder, Maximilian Baust, Rüdiger Göbl, Nassir Navab, Christoph Hennersperger
Erschienen in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Registration of partial-view 3D US volumes with MRI data is influenced by initialization. The standard of practice is using extrinsic or intrinsic landmarks, which can be very tedious to obtain. To overcome the limitations of registration initialization, we present a novel approach that is based on Euclidean distance maps derived from easily obtainable coarse segmentations. We evaluate our approach on a publicly available brain tumor dataset (RESECT) and show that it is robust regarding minimal to no overlap of target area and varying initial position. We demonstrate that our method provides initializations that greatly increase the capture range of state-of-the-art nonlinear registration algorithms.