Marginal Space Learning
Learning a classifier in a
marginal space in which some of the object parameters are integrated
out (ignored) allows to elliminate thousands of uninteresting
locations of the object parameter space in one step. This way speedups
by 3-6 orders of magnitude have been observed.
This principle was sucessfully applied to many medical imaging projects
including Guidewire Localization and Heart Segmentation.
Zheng, Adrian Barbu, B. Georgescu, M. Scheuering and D. Comaniciu.
Four-Chamber Heart Modeling and
Automatic Segmentation for 3D Cardiac CT
Volumes Using Marginal Space Learning and Steerable Features.
IEEE Trans Medical Imaging,
November 2008. (pdf)
- L. Lu, Adrian Barbu, J. Liang, L. Bogoni, M. Salganicoff and D. Comaniciu. Simultaneous Detection and Registration
Ileo-Cecal Valve Detection in 3D CT Colonography. ECCV 2008
- L. Lu, Adrian Barbu, M. Wolf, J. Liang, M. Salganicoff, D. Comaniciu. Accurate
Polyp Segmentation for 3D
CT Colonography Using Multi-Staged Probabilistic
Binary Learning and Compositional Model. CVPR 2008.(pdf)
- R. Socher, Adrian Barbu, D. Comaniciu. A Learning Based Hierarchical Model for Vessel Segmentation.
IEEE International Symposium on Biomedical Imaging, 2008. (pdf)
- Y. Zheng, Adrian Barbu, B. Georgescu, M. Scheuering, D.
Comaniciu. Fast Automatic Heart Chamber Segmentation
from 3D CT Data Using
Marginal Space Learning and Steerable Features. ICCV 2007 (pdf)
- S Lakare, M Wolf, L Bogoni, Adrian Barbu, M Dundar, L Lu,
M Salganicoff, Evaluation of a Learning-based
Component for Suppression of
False Positives Located on the
Ileo Cecal Valve or Rectal Tube, RSNA 2007
- A. Barbu, V. Athitsos, B. Georgescu, S. Boehm, P. Durlak, D. Comaniciu. Hierarchical Learning of Curves:
Application to Guidewire Localization in Fluoroscopy. CVPR 2007 (pdf)