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.

Pericardium segmentation

Feature-based registration

Multi-atlas segmentation

Brain segmentation

Författare

Jennifer Alvén

Signaler och system, Signalbehandling och medicinsk teknik, Digitala bildsystem och bildanalys

Alexander Norlén

Chalmers University of Technology

Olof Enqvist

Signaler och system, Signalbehandling och medicinsk teknik, Digitala bildsystem och bildanalys

Fredrik Kahl

Signaler och system, Signalbehandling och medicinsk teknik, Digitala bildsystem och bildanalys

Pattern Recognition Letters

0167-8655 (ISSN)

Vol. 80 249-255

Styrkeområden

Informations- och kommunikationsteknik

Livsvetenskaper och teknik

Ämneskategorier

Data- och informationsvetenskap

Datorseende och robotik (autonoma system)

Medicinsk bildbehandling

DOI

10.1016/j.patrec.2016.05.001