Research Journal of Pharmacy and Technology

P. Ganesan ¹, B. S. Sathish ², L. M. I. Leo Joseph ³, K. M. Subramanian ⁴, V. Kalist ⁵, K. Vasanth ¹

Affiliations
1 Department of Electronics and Communication Engineering, Vidya Jyothi Institute of Technology, Hyderabad, IN
2 Department of Electronics and Communication Engineering, Ramachandra College of Engineering, Eluru, IN
3 Department of Electronics and Communication Engineering, S.R.Engineering College, Warangal, IN
4 Department of Computer Science and Engineering, Shadan College of Engineering, Hyderabad, IN
5 School of Electrical and Electronics, Sathyabama University, Chennai, IN

Abstract

The segmentation of retinal blood vessels and optical disc is the most vital and challenging task to investigate the rigorousness of the various retinal diseases such as branch retinal vein occlusion. There are lot of methods and algorithms are developed to address this issue i.e., for the precise segmentation of optical disc and blood vessels. However, every method has its own pros and cons. Retinal vein occlusion (RVO) happens due to the obstruction (blockage) of veins transporting blood with required nutrients and oxygen to the nerve cells in the eye’s retina. An obstruction in any one of the four smaller branch veins is referred to as a branch retinal vein occlusion (BRVO). It is one of the main retinal illnesses next only to diabetic retinopathy. Our proposed approach is a simple image processing based detection of optical disc and retinal blood vessels of branch retinal vein occluded fundus images.

Keywords

Branch Retinal Vein Occlusion, Mathematical Morphology, Retinal Blood Vessel Segmentation, Optical Disc, Contrast Enhanced Adaptive Histogram Equalization, Median Filtering.

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P. Ganesan ¹, B. S. Sathish ², R. Murugesan ³

Affiliations
1 Department of Electronics and Communication Engineering, Vidya Jyothi Institute of Technology, Hyderabad, IN
2 Department of Electronics and Communication Engineering, Ramachandra College of Engineering, Eluru, IN
3 Department of Electronics and Communication Engineering, Malla Reddy College of Engineering and Technology, Secunderabad, Telangana, IN

Abstract

Brain tumor is the abnormal growth of superfluous cells in central nervous system or brain. It is fact that brain tumor is second most common of cancer death among young people. There are two key categories of brain tumor as cancerous and non cancerous. The cancerous brain tumor is called as Malignant. It spreads very quickly and difficult to remove. The non-cancerous tumor, called Benign, growth rate is very slow as compared to malignant one and easy to remove. The work proposes a simple but more efficient method to detect and segment the brain tumor from the MRI image. The proposed work based on the threshold segmentation for the segmentation of the brain tumor. The MRI image of the brain is taken and processed in such a way so that the tumor is extracted from the given MRI image and displays the segmented part of the image which contains the tumor. The otsu global threshold performs tumor segmentation and image area opening applies to remove the small components form the tumor portion. The gray level co-occurrence matrix and other image quality measures computes (extracts) the features from the segmented image. Support vector machine classifier is finally classifies the tumor, either benign or malignant, based on the extracted features.

Keywords

Brain Tumor, Threshold, Principal Component Analysis, Discrete Wavelet Transform, Gray-Level Co-Occurrence Matrix, Support Vector Machine.

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