An efficient approach for brain image (tissue) compression based on the position of the brain tumor. Issue 4 (December 2016)

• Record Type: Journal Article
• Authors: Kumarganesh, S.; Suganthi, M.
• Is Part Of: International journal of imaging systems and technology. Volume 26:Issue 4(2016:Dec.)
• Page Start: 237
• Page End: 242
• Publication Date: 2016-12
• Subjects: brain tumor -- brain tissues -- compression -- morphological operations -- accuracy; Imaging systems -- Periodicals; Image processing -- Periodicals; 621.367
• DOI: 10.1002/ima.22194
• Languages: English
• ISSNs: 0899-9457

Abstract

ABSTRACT: Medical image processing plays an important role in brain tissue detection and segmentation. In this paper, a computer aided detection of brain tissue compression based on the estimation of the location of the brain tumor. The proposed system detects and segments the brain tissues and brain tumor using mathematical morphological operations. Further, the brain tissue with tumor is compressed using lossless compression technique and the brain tissue without tumor is compressed using lossy compression technique. The proposed method achieves 96.46% sensitivity, 99.20% specificity and 98.73% accuracy for the segmentation of white matter regions from the brain. The proposed method achieves 98.16% sensitivity, 99.36% specificity and 98.78% accuracy for the segmentation of cerebrospinal fluid (CSF) regions from the brain and also achieves 93.07% sensitivity, 98.79% specificity and 97.63% accuracy for the segmentation of grey matter regions from the brain. This paper focus the brain tissue compression based on the location of brain tumor. The grey matter of the brain is applied to lossless compression due to the presence of the tumor in grey matter of the brain. The proposed system achieves 29.23% of compression ratio for compressing the grey matter of the brain region. The white matter and CSF regions of the brain are applied to lossy compression due to the non‐presence of the tumor. The proposed system achieves 39.13% of compression ratio for compressing the white matter and also achieves 37.5% of compression ratio for compressing the CSF tissue. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 237–242, 2016