Systematic Approach for Brain Tumor Detection Using Rough Sets on DICOM Images
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 3
Abstract
This paper presents a systematic Automated way for diagnosing the human brain tumors (Astrocytoma tumors) using T1- weighted Magnetic Resonance Images with contrast. The proposed image processing method has four distinct modules: Preprocessing, Segmentation, Feature Extraction, and Classification. We develop a fuzzy rule base by aggregating the existing filtering methods for Pre-processing step. For Segmentation step, we extend the Possibilistic Fuzzy method by using the Approximation, Lower and Upper, Roughness Index. Feature Extraction is done by Multi-Thresholding algorithm. Finally, we develop a Type-II Approximate Reasoning method to recognize the tumor grade in brain MRI. The proposed Type-II expert system has been tested and validated to show its accuracy in the real world. The results show that the proposed system is superior in recognizing the brain tumor and its grade than Type-I fuzzy expert systems.
Authors and Affiliations
Abdul Kalam Abdul Salam, Anil V. Deorankar
Keywords
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