Segmentation Method for Pathological Brain Tumor and Accurate Detection using MRI

Abstract

Image segmentation is challenging task in field of medical image processing. Magnetic resonance imaging is helpful to doctor for detection of human brain tumor within three sources of images (axil, corneal, sagittal). MR images are nosier and detection of brain tumor location as feature is more complicated. Level set methods have been applied but due to human interaction they are affected so appropriate contour has been generated in discontinuous regions and pathological human brain tumor portion highlighted after applying binarization, removing unessential objects; therefore contour has been generated. Then to classify tumor for segmentation hybrid Fuzzy K Mean-Self Organization Mapping (FKM-SOM) for variation of intensities is used. For improved segmented accuracy, classification has been performed, mainly features are extracted using Discrete Wavelet Transformation (DWT) then reduced using Principal Component Analysis (PCA). Thirteen features from every image of dataset have been classified for accuracy using Support Vector Machine (SVM) kernel classification (RBF, linear, polygon) so results have been achieved using evaluation parameters like Fscore, Precision, accuracy, specificity and recall.

Authors and Affiliations

Khurram Ejaz, Mohd Shafry Mohd Rahim, Amjad Rehman, Huma Chaudhry, Tanzila Saba, Anmol Ejaz, Chaudhry Farhan Ej

Keywords

Related Articles

WE-MQS-VoIP Priority: An enhanced LTE Downlink Scheduler for voice services with the integration of VoIP priority mode

The Long Term Evolution (LTE) is a high data rates and fully All-IP network. It is developed to support well to multimedia services such as Video, VoIP, Gaming, etc. So that, the real-time services such as VoIP, video, e...

Improved Appliance Coordination Scheme with Waiting Time in Smart Grids

Smart grids aim to merge the advances in communications and information technologies with traditional power grids. In smart grids, users can generate energy and sell it to the local utility supplier. The users can reduce...

 Performance Analysis of MIMO-OFDM System Using Singular Value Decomposition and Water Filling Algorithm

  In this paper, MIMO is paired up with OFDM to improve the performance of wireless transmission systems. Multiple antennas are employed both at the transmitting as well as receiving ends. The performance of an OFDM...

Cloud Based Public Collaboration System in Developing Countries

Governments in developing countries are increasingly making efforts to provide more access to information and services for citizens, businesses, and civil servants through smart devices. However, providing strategically...

Validation Policy Statement on the Digital Evidence Storage using First Applicable Algorithm

Digital Evidence Storage is placed to store digital evidence files. Digital evidence is very vulnerable to damage. Therefore, making digital evidence storage need access control. Access control has several models, one o...

Download PDF file
  • EP ID EP376458
  • DOI 10.14569/IJACSA.2018.090851
  • Views 101
  • Downloads 0

How To Cite

Khurram Ejaz, Mohd Shafry Mohd Rahim, Amjad Rehman, Huma Chaudhry, Tanzila Saba, Anmol Ejaz, Chaudhry Farhan Ej (2018). Segmentation Method for Pathological Brain Tumor and Accurate Detection using MRI. International Journal of Advanced Computer Science & Applications, 9(8), 394-401. https://europub.co.uk/articles/-A-376458