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

Towards an Architecture for Handling Big Data in Oil and Gas Industries: Service-Oriented Approach

Existing architectures to handle big data in Oil & gas industry are based on industry-specific platforms and hence limited to specific tools and technologies. With these architectures, we are confined to big data single-...

An Optimized Analogy-Based Project Effort Estimation

Despite the predictive performance of Analogy-Based Estimation (ABE) in generating better effort estimates, there is no consensus on: (1) how to predetermine the appropriate number of analogies, (2) which adjustment tech...

Study of the Performance of Multi-hop Routing Protocols in Wireless Sensor Networks

Currently in the literature, there are quite a num-ber of multi-hop routing algorithms, some of which are subject to normalization. Routing protocols based on clustering provide an efficient method for extending the life...

Proposed an Adaptive Bitrate Algorithm based on Measuring Bandwidth and Video Buffer Occupancy for Providing Smoothly Video Streaming

Dynamic adaptive streaming via HTTP (DASH) has been popular disseminated over the Internet especially under the circumstances of the time varying network, which it is currently the most challenging for providing smoothly...

 Speaker Identification using Frequency Dsitribution in the Transform Domain

 In this paper, we propose Speaker Identification using the frequency distribution of various transforms like DFT (Discrete Fourier Transform), DCT (Discrete Cosine Transform), DST (Discrete Sine Transform), Hartley...

Download PDF file
  • EP ID EP376458
  • DOI 10.14569/IJACSA.2018.090851
  • Views 97
  • 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