NDLI: Variational image segmentation models: Application to medical images MRI

Content Provider	IEEE Xplore Digital Library
Author	Bara, S. Kerroum, M.A. Hammouch, A. Aboutajdine, D.
Copyright Year	2011
Description	Author affiliation: UFR LRIT, Faculty of Sciences, Mohamed V-Agdal University B.P. 1014 Rabat, Morocco (Bara, S.; Kerroum, M.A.; Hammouch, A.; Aboutajdine, D.)
Abstract	Image segmentation is an important branch of computer vision. Its aim is to extract meaningful lying in objects images, either by dividing images into contiguous semantic regions, or by extracting one or several objects more specific in images, such as medical structures. In general, image segmentation task is very difficult to achieve it since natural images are diverse, complex and the way we perceive them, vary according to individuals. More than a decade ago, a promising mathematical framework, based on variational models and partial differential equations, have been investigated to solve the image segmentation problem. This new approach benefits from well-established mathematical theories that allow people to analyze, understand and extend segmentation methods. Moreover, this framework is defined in a continuous setting which makes the proposed models independent with respect to the grid of digital images.
Starting Page	1
Ending Page	4
File Size	677137
Page Count	4
File Format	PDF
ISBN	9781612847306
e-ISBN	9781612847320
DOI	10.1109/ICMCS.2011.5945667
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-04-07
Publisher Place	Morocco
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Level set Mathematical model Biomedical imaging Active contours Pixel Noise
Content Type	Text
Resource Type	Article

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