An Efficient Brain Tumor Detection Algorithm Using Watershed & Thresholding Based Segmentation | Zendy

Anam Mustaqeem | Zendy; Javed Ali | Zendy; Tehseen Fatima | Zendy

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An Efficient Brain Tumor Detection Algorithm Using Watershed & Thresholding Based Segmentation

Author(s) -

Anam Mustaqeem,

Javed Ali,

Tehseen Fatima

Publication year - 2012

Publication title -

international journal of image graphics and signal processing

Language(s) - English

Resource type - Journals

eISSN - 2074-9082

pISSN - 2074-9074

DOI - 10.5815/ijigsp.2012.10.05

Subject(s) - thresholding , segmentation , brain tumor , artificial intelligence , computer science , image segmentation , magnetic resonance imaging , computer vision , mathematical morphology , watershed , algorithm , pattern recognition (psychology) , image (mathematics) , image processing , radiology , medicine , pathology

During past few years, brain tumor segmentation in magnetic resonance imaging (MRI) has become an emergent research area in the field of medical imaging system. Brain tumor detection helps in finding the exact size and location of tumor. An efficient algorithm is proposed in this paper for tumor detection based on segmentation and morphological operators. Firstly quality of scanned image is enhanced and then morphological operators are applied to detect the tumor in the scanned image.

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