DocumentCode :
794604
Title :
Region-based wavelet coding methods for digital mammography
Author :
Penedo, Mónica ; Pearlman, William A. ; Tahoces, Pablo G. ; Souto, Miguel ; Vidal, Juan J.
Author_Institution :
Dept. of Radiol., Santiago de Compostela Univ., Spain
Volume :
22
Issue :
10
fYear :
2003
Firstpage :
1288
Lastpage :
1296
Abstract :
Spatial resolution and contrast sensitivity requirements for some types of medical image techniques, including mammography, delay the implementation of new digital technologies, namely, computer-aided diagnosis, picture archiving and communications systems, or teleradiology. In order to reduce transmission time and storage cost, an efficient data-compression scheme to reduce digital data without significant degradation of medical image quality is needed. In this study, we have applied two region-based compression methods to digital mammograms. In both methods, after segmenting the breast region, a region-based discrete wavelet transform is applied, followed by an object-based extension of the set partitioning in hierarchical trees (OB-SPIHT) coding algorithm in one method, and an object-based extension of the set partitioned embedded block (OB-SPECK) coding algorithm in the other. We have compared these specific implementations against the original SPIHT and the new standard JPEG 2000, both using reversible and irreversible filters, on five digital mammograms compressed at rates ranging from 0.1 to 1.0 bit per pixel (bbp). Distortion was evaluated for all images and compression rates by the peak signal-to-noise ratio. For all images, OB-SPIHT and OB-SPECK performed substantially better than the traditional SPIHT and JPEG 2000, and a slight difference in performance was found between them. A comparison applying SPIHT and the standard JPEG 2000 to the same set of images with the background pixels fixed to zero was also carried out, obtaining similar implementation as region-based methods. For digital mammography, region-based compression methods represent an improvement in compression efficiency from full-image methods, also providing the possibility of encoding multiple regions of interest independently.
Keywords :
data compression; discrete wavelet transforms; image coding; image resolution; image segmentation; mammography; medical image processing; JPEG 2000; background pixels; compression efficiency; contrast sensitivity requirements; digital mammography; hierarchical trees; medical diagnostic imaging; multiple regions of interest encoding; peak signal-to-noise ratio; region-based wavelet coding methods; set partitioned embedded block; set partitioning; spatial resolution; Biomedical imaging; Delay; Discrete wavelet transforms; Image coding; Image storage; Mammography; Medical diagnostic imaging; Partitioning algorithms; Spatial resolution; Transform coding; Algorithms; Breast Diseases; Breast Neoplasms; Calcinosis; Data Compression; Humans; Mammography; Pattern Recognition, Automated; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2003.817812
Filename :
1233926
Link To Document :
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