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RELAXED ORIENTED IMAGE FORESTING TRANSFORM FOR SEEDED IMAGE SEGMENTATION

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Citation Author(s):
Caio L. Demario, Paulo A.V. Miranda
Submitted by:
Paulo Miranda
Last updated:
22 September 2019 - 6:12pm
Document Type:
Poster
Document Year:
2019
Event:
Presenters:
Paulo A. V. Miranda
Paper Code:
3317
 

In this work, we propose a hybrid method for seeded image segmentation, named Relaxed OIFT, which extends a method by Malmberg et al. to directed graphs, to properly incorporate the boundary polarity constraint. Relaxed OIFT lies between the pure Oriented Image Foresting Transform (OIFT) at one end and the extension of Random Walks (RW) to directed graphs as proposed by Singaraju et al. Relaxed OIFT is evaluated in MR and CT medical images, producing more intuitively correct segmentation results than both OIFT and RW, and being easy to be extended to multi-dimensional images.

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