Forskning ved Københavns Universitet - Københavns Universitet


Local appearance features for robust MRI brain structure segmentation across scanning protocols

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  • H.C. Achterberg
  • Dirk H. J. Poot
  • Fedde van der Lijn
  • Meike W. Vernooij
  • M. Arfan Ikram
  • Wiro J. Niessen
  • de Bruijne, Marleen
Segmentation of brain structures in magnetic resonance images is an important task in neuro image analysis. Several papers on this topic have shown the benefit of supervised classification based on local appearance features, often combined with atlas-based approaches. These methods require a representative annotated training set and therefore often do not perform well if the target image is acquired on a different scanner or with a different acquisition protocol than the training images. Assuming that the appearance of the brain is determined by the underlying brain tissue distribution and that brain tissue classification can be performed robustly for images obtained with different protocols, we propose to derive appearance features from brain-tissue density maps instead of directly from the MR images. We evaluated this approach on hippocampus segmentation in two sets of images acquired with substantially different imaging protocols and on different scanners. While a combination of conventional appearance features trained on data from a different scanner with multiatlas segmentation performed poorly with an average Dice overlap of 0.698, the local appearance model based on the new acquisition-independent features significantly improved (0.783) over atlas-based segmentation alone (0.728).
TitelMedical Imaging 2013 : image processing
RedaktørerSebastien Ourselin, David R. Haynor
Antal sider7
ForlagSPIE - International Society for Optical Engineering
ISBN (Trykt) 9780819494436
StatusUdgivet - 2013
BegivenhedMedical Imaging 2013: Image Processing - Lake Buena Vista, USA
Varighed: 10 feb. 201312 feb. 2013


KonferenceMedical Imaging 2013
ByLake Buena Vista
NavnProgress in Biomedical Optics and Imaging

ID: 169381109