Überatlas: Fast and robust registration for multi-atlas segmentation
Artikel i vetenskaplig tidskrift, 2016

Multi-atlas segmentation has become a frequently used tool for medical image segmentation due to its outstanding performance. A computational bottleneck is that all atlas images need to be registered to a new target image. In this paper, we propose an intermediate representation of the whole atlas set – an überatlas – that can be used to speed up the registration process. The representation consists of feature points that are similar and detected consistently throughout the atlas set. A novel feature-based registration method is presented which uses the überatlas to simultaneously and robustly find correspondences and affine transformations to all atlas images. The method is evaluated on 20 CT images of the heart and 30 MR images of the brain with corresponding ground truth. Our approach succeeds in producing better and more robust segmentation results compared to three baseline methods, two intensity-based and one feature-based, and significantly reduces the running times.

Feature-based registration

Brain segmentation

Multi-atlas segmentation

Pericardium segmentation

Författare

Jennifer Alvén

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik

Alexander Norlén

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik

Olof Enqvist

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik

Fredrik Kahl

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik

Pattern Recognition Letters

0167-8655 (ISSN)

Vol. 80 249-255

Styrkeområden

Informations- och kommunikationsteknik

Livsvetenskaper och teknik (2010-2018)

Ämneskategorier

Data- och informationsvetenskap

Datorseende och robotik (autonoma system)

Medicinsk bildbehandling

DOI

10.1016/j.patrec.2016.05.001

Mer information

Senast uppdaterat

2018-07-23