Abstract
An accurate method for localising and segmenting intervertebral discs in magnetic resonance (MR) spine imaging is presented. Atlas-based labelling of discs in MRI is challenging due to the small field of view and repetitive structures, which may cause the image registration to converge to a local minimum. To tackle this initialisation problem, our approach uses Vantage Point Hough Forests to automatically and robustly regress landmark positions, which are used to initialise a discrete deformable registration of all training images. An image-adaptive fusion of propagated segmentation labels is obtained by non-negative least-squares regression. Despite its simplicity and without using specific domain knowledge, our approach achieves sub-voxel localisation accuracy of 0.61 mm, Dice segmentation overlaps of nearly 90% (for the training data) and takes less than ten minutes to process a new scan.
| Original language | English |
|---|---|
| Title of host publication | Computational Methods and Clinical Applications for Spine Imaging |
| Editors | Jianhua Yao, Tomaž Vrtovec, Guoyan Zheng, Alejandro Frangi, Ben Glocker, Shuo Li |
| Number of pages | 8 |
| Volume | 10182 |
| Publisher | Springer International Publishing |
| Publication date | 01.03.2016 |
| Pages | 77 - 84 |
| ISBN (Print) | 978-3-319-55049-7 |
| ISBN (Electronic) | 978-3-319-55050-3 |
| DOIs | |
| Publication status | Published - 01.03.2016 |
| Event | International Workshop on Computational Methods and Clinical Applications for Spine Imaging - Athens, Greece Duration: 17.10.2016 → … https://csi2016.wordpress.com/ |