Publications

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Search for Publication


Year(s) from:  to 
Author:
Keywords (separated by spaces):

Oblique Random Forests for 3-D Vessel Detection Using Steerable Filters and Orthogonal Subspace Filtering

Matthias Schneider, Sven Hirsch, Gábor Székely, Bruno Weber, and Bjoern H. Menze
Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging - Second International MICCAI Workshop, MCV 2012
2013

Abstract

We propose a machine learning-based framework using oblique random forests for 3-D vessel segmentation. Two different kinds of features are compared. One is based on orthogonal subspace filtering where we learn 3-D eigenspace filters from local image patches that return task optimal feature responses. The other uses a specific set of steerable filters that show, qualitatively, similarities to the learned eigenspace filters, but also allow for explicit parametrization of scale and orientation that we formally generalize to the 3-D spatial context. In this way, steerable filters allow to efficiently compute oriented features along arbitrary directions in 3-D. The segmentation performance is evaluated on four 3-D imaging datasets of the murine visual cortex at 700nm resolution. Our experiments show that the learning-based approach is able to significantly improve the segmentation compared to conventional Hessian-based methods. Features computed based on steerable filters prove to be superior to eigenfilter based features for the considered datasets. We further demonstrate that random forests using oblique split directions outperform decision tree ensembles with univariate orthogonal splits.


Link to publisher's page
@InProceedings{eth_biwi_00920,
  author = {Matthias Schneider and Sven Hirsch and Gábor Székely and Bruno Weber and and Bjoern H. Menze},
  title = {Oblique Random Forests for 3-D Vessel Detection Using Steerable Filters and Orthogonal Subspace Filtering},
  booktitle = {Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging - Second International MICCAI Workshop, MCV 2012},
  year = {2013},
  pages = {142--154},
  volume = {7766},
  editor = {Menze and Bjoern H. and Langs and Georg and Montillo and Albert and Tu and Zhuowen and Criminisi and Antonio},
  series = {LNCS},
  publisher = {Springer Heidelberg / Berlin},
  keywords = {}
}