Earticle

초록

영어

Colloid Cysts, also called neuroepithelial cysts are located in the rostral aspect of the third ventricle in the brain [1]. It appears near the center of the brain and grows along the roof of the third ventricle that holds spinal fluid. Increase in the size of cyst can block the flow of cerebrospinal fluid causing hydrocephalus (water on the brain or a buildup of CSF in the brain). The buildup of CSF in the brain can increase intracranial pressure that compresses surrounding brain tissues in the skull and may cause enlargement of the brain, convulsions, brain damage and even sudden death [2]. Detection of Colloid Cyst at early stages is very important. Analysis and manual interpretation of Magnetic Resonance Images and Computed Tomography Images by radiologists are time consuming and sometimes difficult and error prone. In this paper we propose an algorithm to automate the process of detecting Colloid Cysts in Brain through the use of image processing techniques.

목차

Abstract
 1. Introduction
 2. Literature Review
 3. Proposed Methodology
  3.1. Proposed Algorithm to Detect Colloid Cyst
 4. Algorithm Analysis
  4.1. Input Image and Gray Scale Image
  4.2. Median Filtering and Gaussian High-Pass Filtering
  4.3. Detection of Colloid Cyst and its Approximate Size
 5. Result Analysis
 6. Conclusion and Future Work
 References

키워드

저자

• Debapriya Hazra [ Atos India Pvt. Ltd., Salt Lake City, Sector – 5, Kolkata-700091, India ]
• Debnath Bhattacharyya [ Department of Computer Science and Engineering, Vignan’s Institute of Information Technology, Visakhapatnam- 530049, AP, India ]
• Hye-Jin Kim [ Sungshin Women's University, 2, Bomun-ro 34da-gil, Seongbuk-gu, Seoul, Republic of Korea, South Korea ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605