earticle

논문검색

An Approach to Brain Tumor Segmentation and Severity Analysis using Particle Swarm Optimization

원문정보

Ganesh Prasad Bhatta

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

Medical image processing is one of the most challenging and emerging filed. Processing of medical image is one of the important tasks for the diagnosis of brain tumor. Image segmentation is required for detection of brain tumors, which is a quite complicated job if performed automatically. In recent time, scientists from various fields including medical, mathematical and computer science have collaborated to find out a better understanding of the disease and devise more cost-effective treatments. Due to advancements in the field of science and technology, we have innumerous methods for image segmentation which are used for the detection of brain tumor and to clearly recognize it from MRI imagery. Various methods and algorithms have been implemented for segmenting MRI imagery. This work implements particle swarm optimization technique to recognize brain tumor by characterizing MRI images. Machine learning algorithm is used for severity analysis of brain tumor.

목차

Abstract
1. Introduction
1.1 Research Objectives
2. Background
2.1 Statement of Problem
3. Research and methodology
3.1 Experiment and Process Flow
3.2 Image Acquisition
3.3 Image Preprocessing
3.4 Algorithm
4. Result and Discussion
5. Conclusion
References

저자정보

  • Ganesh Prasad Bhatta Academia International College, Nepal

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 기관로그인 시 무료 이용이 가능합니다.

      • 4,000원

      0개의 논문이 장바구니에 담겼습니다.