Interactive Segmentation of MR Images from Brain Tumor Patients

Bauer, Stefan; Porz, Nicole; Meier, Raphael; Pica, Alessia; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio (2014). Interactive Segmentation of MR Images from Brain Tumor Patients. In: ISBI 2014: Proceedings of the 2014 IEEE international conference on Biomedical imaging (pp. 862-865). Beijing: IEEE 10.1109/ISBI.2014.6868007

	Text BauerISBI2014.pdf - Accepted Version Restricted to registered users only Available under License Publisher holds Copyright. Download (481kB)
	Text 06868007.pdf - Published Version Restricted to registered users only Available under License Publisher holds Copyright. Download (941kB)

Medical doctors often do not trust the result of fully automatic segmentations because they have no possibility to make corrections if necessary. On the other hand, manual corrections can introduce a user bias. In this work, we propose to integrate the possibility for quick manual corrections into a fully automatic segmentation method for brain tumor images. This allows for necessary corrections while maintaining a high objectiveness. The underlying idea is similar to the well-known Grab-Cut algorithm, but here we combine decision forest classification with conditional random field regularization for interactive segmentation of 3D medical images. The approach has been evaluated by two different users on the BraTS2012 dataset. Accuracy and robustness improved compared to a fully automatic method and our interactive approach was ranked among the top performing methods. Time for computation including manual interaction was less than 10 minutes per patient, which makes it attractive for clinical use.

Interest & Impact

Downloads

23 since deposited on 05 Jan 2015
1 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item