An Enhanced Implementation PTPSA Algorithm for Fractal Feature Extraction and Abnormal Tissue Segmentation

G. Saravanan; Dr. K. Krishnamoorthy

Two novel fractal-based texture features are exploited for pediatric brain tumor segmentation and classification in MRI. One of the two texture features uses Piecewise-Triangular Prism Surface Area (PTPSA) algorithm for fractal feature extraction. The other texture feature exploits our novel fractional Brownian motion (fBm) framework that combines both fractal and wavelet analysis for fractal wavelet feature extraction. Three modalities such as T1 (Gadolinium-enhanced), T2 and Fluid Attenuated Inversion Recovery (FLAIR) are exploited in this work. The Self Organizing Map (SOM) algorithm is used for tumor segmentation. For a total of 204 T1 contrast-enhanced,T2 and FLAIR MR Images obtained from nine different pediatric patients. In this paper, we are using support vector machine (SVM) to classify the tumor regions from non-tumor regions.

Select Volume / Issues:

• Volume 5,Issue 3,May 2014

Year:

2014

Type of Publication:

Article

Keywords:

MRI; PTPSA; Support Vector Machine; SOM

Journal:

IJECCE

Volume:

5

Number:

3

Pages:

623-625

Month:

May