INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
REVIEW OF VARIOUS MRI IMAGE PROCESSING METHODS FOR EFFICIENT TUMOUR DETECTION
Authors Name:
Deepak Kokate
, Jijo Nair
Unique Id:
IJSDR1806057
Published In:
Volume 3 Issue 6, June-2018
Abstract:
Image processing is a new era of data mining. Day by day the sizes of digital images are getting increases. In a medical field such as diagnostics of the tumour, cancer MRI images are used. Image mining techniques have a vital role in tumour detection from MRI images. MRI images are widely used in medical fields for analysis and detection of tumour growth from the body. It is a monotonous process for the radiologist to physical segmentation of MRI or medical images. Magnetic resonance images (also called MRI) are basically a technique, which widely used by the radiologist to detect disease from the body such as a tumour or any abnormal disease. An MRI scanner machine uses high-level radio waves, a strong field of magnetic areas, and field gradients to generates and captures images of the complete internal body. There are varieties of efficient brain tumour detection and segmentation methods have been suggested by various researchers for efficient tumour detection. Existing methods encounter with several challenges such as detection time, accuracy and quality of tumour. In this review paper, we are presenting an analysis and study of various tumour detection methods for MRI images. A comparative analysis has been also performed for various methods
Keywords:
Data Mining, Image Processing, Brain Tumour, MRI images, Image Processing and Segmentation
Cite Article:
"REVIEW OF VARIOUS MRI IMAGE PROCESSING METHODS FOR EFFICIENT TUMOUR DETECTION", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.3, Issue 6, page no.353 - 357, June-2018, Available :http://www.ijsdr.org/papers/IJSDR1806057.pdf
Downloads:
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Publication Details:
Published Paper ID: IJSDR1806057
Registration ID:180438
Published In: Volume 3 Issue 6, June-2018
DOI (Digital Object Identifier):
Page No: 353 - 357
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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