Lossless and near lossless compression of pharynx and esophagus in fluoroscopy medical images


Arif, Arif Sameh (2015) Lossless and near lossless compression of pharynx and esophagus in fluoroscopy medical images. PhD thesis, Multimedia University.

Full text not available from this repository.


Hospitals and medical centres produce an increasing amount of digital medical data for health examinations. Fluoroscopy is one of imaging modalities that is produced daily and generates an enormous amount of data over time, requiring a large storage space in addition to the increasing transmission costs over the internet and intranet for telemedicine and local applications. The crucial aspect in medical image compression is to maintain all vital diagnostic information without any loss. Therefore, most existing methods employ lossless compression. However, lossy compression is well known to produce higher compression performance. Controlled lossy compression that is near lossless may be employed as diagnosis of images are almost always done exclusively in terms of visual inspection. The main motivation of this study is to achieve high compression performance on Fluoroscopy medical images for the Pharynx and Esophogus without affecting the diagnosis information. Due to the variability in acquisition and image quality, preprocessing step is required to standardize images, making them more compressible. In this work, the preprocessing stage consists of two main phases - the first extracts the Region of Coding (ROC) using a derived general equation; the second employs correlation coefficients to classify the set of images depending on the acquisition view. Three efficient lossless and near lossless image compression approaches are proposed to achieve high compression performance of the Flouroscopy images.

Item Type: Thesis (PhD)
Additional Information: Call No.: TA1638 A75 2015
Uncontrolled Keywords: Image compression
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 13 Jan 2016 01:22
Last Modified: 13 Jan 2016 01:22
URII: http://shdl.mmu.edu.my/id/eprint/6271


Downloads per month over past year

View ItemEdit (login required)