Brain tumor segmentation and classification using KNN algorithm

Open

Suhartono, Phong Thanh Nguyen, K. Shankar, Wahidah Hashim, Andino Maseleno

2019 International Journal of Engineering and Advanced Technology Vol. 8 Issue 6 Special Issue Article Cited by 12 SDG 3SDG 17 Quartile

Abstract

Image processing plays a vital role in MRI image processing. MRI images are widely used in medical fields for analysis and detection of tumour growth from the 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 a study of various tumour detection methods for MRI images. A comparative analysis has been also performed for various methods.SAR images are the high resolution images which cannot be collected manually. In this work, we identified the SAR images randomly from web with different region inclusions. The regions in an image include water area, land area and the mountain area. The implementation of proposed model is done in MATLAB environment. © BEIESP.

Affiliations

Universitas Negeri Makassar, Indonesia; Department of Project Management, Ho Chi Minh City Open University, Viet Nam; Department of Computer Applications, Alagappa University, India; Institute of Informatics and Computing Energy, Universiti Tenaga Nasional, Malaysia

Research at a Glance

Premium content — register to unlock

Research at a Glance

Register to unlock

Topics & SDG Alignment

Premium content — register to unlock

Topics & SDG Alignment

Register to unlock

Collaboration

Premium content — register to unlock

Collaboration

Register to unlock

Author Profile (Selected)

Premium content — register to unlock

Author Profile (Selected)

Register to unlock

References Overview

Premium content — register to unlock

References Overview

Register to unlock

Journal & Source

Premium content — register to unlock

Journal & Source

Register to unlock

Metadata & Integrity

Premium content — register to unlock

Metadata & Integrity

Register to unlock