Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Computer Science

First Advisor

John M. Tyler


Today, hospitals are desirous of better methods for replacing their traditional film-based medical imaging. A major problem associated with a "film-less hospital" is the amount of digital image data that is generated and stored. Image compression must be used to reduce the storage size. This dissertation presents several techniques involving wavelet analysis, lifting, image prediction and image scanning to achieve an efficient diagnostically lossless compression for sets of medical images. This dissertation experimentally determines the optimal wavelet basis for medical images. Then, presents a new wavelet based prediction method for prediction of the intermediate images in a similar set of medical images. The technique uses the correlation between coefficients in the wavelet transforms of the image set to produce a better image prediction compared to direct image prediction. New methods for scanning similar sets of medical images are introduced in this dissertation. These methods significantly reduce the image edges needed for compression with wavelet lifting. Lifting plus new scanning methods have the following advantages: (a) images in the set do not have to be the same size, (b) additional compression is obtained from the continuous image background, and (c) lifting produces better compression. The scanning techniques, introduced in this dissertation, reduce the number of edges. These scanning techniques separate the diagnostic foreground from the continuous background of each image in the set. A theoretical approach for determining an optimal orthogonal wavelet basis with compact support is presented and then demonstrated on medical images. Orthogonal wavelet bases were constructed with this theoretical approach and then another algorithm was used to determine the optimal wavelet basis for each medical image set. One result of this research is that the new image scanning techniques plus lifting and standard compression methods resulted in improved and better compression of medical image sets than achieved by the standard compression alone.