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Content Based Image Retrieval for Diagnosis of Brain Tumor

Author(s):

Dhruvisha Patel , L.D.College of Engineering; Dhruvisha Patel, L.D.College of Engineering; Arun Nandurbarkar, L.D.College of Engineering

Keywords:

CBMIR, Brain MRI, Global Feature, LBP, ANN, SVM

Abstract

Accurate diagnosis is important for treatment of any disease. Content based medical image retrieval (CBMIR) can assist radiologist in diagnosis by retrieving similar images from medical image database. Here we proposed CBMIR for brain tumor. Magnetic Resonance imaging is most commonly used for imaging the brain tumor. During the image acquisition there can be misalignment of MR images due to movement of patient and also low level semantics from MR image may not corresponds with high level semantics of brain tumor, for this two level CBMIR system used, which first classifies (using SVM and ANN) query image of brain tumor as cancerous and non-cancerous tumor using global feature (circularity, irregularity and texture feature) and then search for most similar images with identified class using local feature. This experiment has been performed on 94 brain MR images and result of classification is compare with precision rate, accuracy and recall rate.

Other Details

Paper ID: NCACSETT4P058
Published in: Conference 10 : NCACSET 2017
Publication Date: 06/05/2017
Page(s): 140-144

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