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
한국AI디지털융합학회(구 한국디지털융합학회) [The Korean Academic Society of AI Digital Convergence]
설립연도
2015
분야
사회과학>경영학
소개
본 학회는 디지털 경영에 관련된 디지털 미디어, 디지털 통신, 디지털 방송, 디지털 콘텐츠, 디지털 문화, 디지털 사회, 디지털 유통, 디지털 금융, 디지털 물류, 디지털 정책, 디지털 기술, 디지털 교육 그리고 디지털과 아날로그의 비교 등에 대한 학제간 연구와 실사구시적인 적용을 통하여 디지털 경영의 발전과 한국이 세계적인 디지털 강국으로 성장하기 위한 학술적인 기반과 실무적인 지침을 조성하는 것을 목적으로 하고 있습니다.
간행물
간행물명
IJICTDC [International Journal of Information Communication Technology and Digital Convergence]