An Enhanced Approach for Medical Brain Image Enhancement
J. Umamaheswari1 & G. Radhamani1 Show affiliations
- Affiliated to Bharathiyar University, India
Journal of Computer Science, Volume 8, Issue 8, pp. 1329–1337 · doi.org/10.3844/jcssp.2012.1329.1337
Abstract
Problem statement: One of the most common degradations in medical images is their poor contrast quality and noise. The DICOM image consists of speckle (multiplicative noise). While the image is enhanced, the multiplicative noise present in the image is also enhanced. Approach: This study describes the hybrid method to improve the image quality of Digital Imaging and Communications in Medicine (DICOM) images. The idea of image enhancement technique is to improve the quality of an image for early diagnosis. Then followed by a noise reduction using speckle reduction anisotropic filter. This suggests the use of contrast enhancement methods as an attempt to modify the intensity distribution of the image and to reduce the multiplicative noise. Results: In this research study, a new approach for DICOM image is done by applying contrast stretching and anisotropic diffusion where denoising of multiplicative noise is carried out and the level of contrast is improved. The quality of the image is enhanced and noise free for DICOM image analysis. The effectiveness of hybrid method is proved by quantitative approach. Conclusion and Recommendation: The performance of the proposed study is compared with the existing traditional algorithm and real time medical diagnosis image.
Licence and reuse
Free to read. This article carries the publisher’s copyright, as printed on it: © 2012 Science Publications. It is free to read; ask us before reusing it.
How to reuse this articleResponses (0)
About this article
Umamaheswari, J. & Radhamani, G. (2012). An Enhanced Approach for Medical Brain Image Enhancement. Journal of Computer Science, 8(8), 1329–1337. https://doi.org/10.3844/jcssp.2012.1329.1337
- Licence
- © Science Publications
- Issue
- Volume 8, Issue 8
- Policies
- Editorial independenceUse of generative AIData availabilityAppeals and complaints
- Version
- Version of record
