Relaxed image foresting transforms for interactive volume image segmentation

Malmberg, Filip, Nyström, Ingela, Mehnert, Andrew, Engstrom, Craig and Bengtsson, Ewert (2011). Relaxed image foresting transforms for interactive volume image segmentation. In: Benoit M. Dawant and David R. Haynor, Proceedings of SPIE. Medical Imaging 2010: Image Processing, San Diego, California, USA, (1-11). 14 February 2010. doi:10.1117/12.840019


Author Malmberg, Filip
Nyström, Ingela
Mehnert, Andrew
Engstrom, Craig
Bengtsson, Ewert
Title of paper Relaxed image foresting transforms for interactive volume image segmentation
Conference name Medical Imaging 2010: Image Processing
Conference location San Diego, California, USA
Conference dates 14 February 2010
Proceedings title Proceedings of SPIE
Journal name Progress in Biomedical Optics and Imaging
Place of Publication Bellingham, Wash., U.S.A.
Publisher SPIE
Publication Year 2011
Sub-type Poster
DOI 10.1117/12.840019
ISBN 9780819480248
ISSN 1605-7422
Editor Benoit M. Dawant
David R. Haynor
Volume 7623
Issue 762340
Start page 1
End page 11
Total pages 11
Collection year 2011
Language eng
Abstract/Summary The Image Foresting Transform (IFT) is a framework for image partitioning, commonly used for interactive segmentation. Given an image where a subset of the image elements (seed-points) have been assigned correct segmentation labels, the IFT completes the labeling by computing minimal cost paths from all image elements to the seed-points. Each image element is then given the same label as the closest seed-point. Here, we propose the relaxed IFT (RIFT). This modified version of the IFT features an additional parameter to control the smoothness of the segmentation boundary. The RIFT yields more intuitive segmentation results in the presence of noise and weak edges, while maintaining a low computational complexity. We show an application of the method to the refinement of manual segmentations of a thoracolumbar muscle in magnetic resonance images. The performed study shows that the refined segmentations are qualitatively similar to the manual segmentations, while intra-user variations are reduced by more than 50%. ©2010 COPYRIGHT SPIE--The International Society for Optical Engineering.
Subjects 0906 Electrical and Electronic Engineering
Keyword Seeded segmentation
Image Foresting Transform
Interactive segmentation
Minimum cost paths
Q-Index Code EX
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Tue, 12 Oct 2010, 12:45:31 EST by Ms May Balasaize on behalf of Faculty Of Engineering, Architecture & Info Tech