NDLI: A hybrid segmentation approach for brain tumor extraction and detection

Content Provider	IEEE Xplore Digital Library
Author	Idrissi, N. Ajmi, F.E.
Copyright Year	2014
Description	Author affiliation: Fac. of Sci. & Tech., Sultan Moulay Slimane Univ., Beni Mellal, Morocco (Ajmi, F.E.) \|\| Fac. of Sci. & Tech., TIT Team, Sultan Moulay Slimane Univ., Beni Mellal, Morocco (Idrissi, N.)
Abstract	Nowadays, medical image processing and particularly MRI images is the one of the most challenging field and emerging to help specialists in their diagnostics. In this context and to detect automatically suspicious regions or tumors, this paper presents a new approach called hybrid segmentation inspired by both mathematical morphology operators and morphological watershed segmentation. Our approach's advantage comes from the complementarity between these two approaches. The morphological operators extract roughly the tumor region and eventually can affect healthy structures while the watershed method provides details of various brain's structures and therefore the fusion of these two approaches improves significantly the segmentation and the extraction of the tumor zone.
Starting Page	235
Ending Page	240
File Size	966578
Page Count	6
File Format	PDF
e-ISBN	9781479938247
DOI	10.1109/ICMCS.2014.6911131
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-04-14
Publisher Place	Morocco
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Tumors Image segmentation Magnetic resonance imaging Morphology Biomedical imaging Object segmentation Cancer fusion MRI brain tumor segmentation mathematical morphology watershed
Content Type	Text
Resource Type	Article

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