title: A segmentation-based lossless image coding method for high-resolution medical image compression.
abstract: Lossless compression techniques are essential in archival and communication of medical images. In this paper, a new segmentation-based lossless image coding (SLIC) method is proposed, which is based on a simple but efficient region growing procedure. The embedded region growing procedure produces an adaptive scanning pattern for the image with the help of a very-few-bits-needed discontinuity index map. Along with this scanning pattern, an error image data part with a very small dynamic range is generated. Both the error image data and the discontinuity index map data parts are then encoded by the Joint Bi-level Image experts Group (JBIG) method. The SLIC method resulted in, on the average, lossless compression to about 1.6 h/pixel from 8 b, and to about 2.9 h/pixel from 10 b with a database of ten high-resolution digitized chest and breast images. In comparison with direct coding by JBIG, Joint Photographic Experts Group (JPEG), hierarchical interpolation (HINT), and two-dimensional Burg Prediction plus Huffman error coding methods, the SLIC method performed better by 4% to 28% on the database used.
authors.affiliation: Department of Electrical and Computer Engineering, University of Calgary, Alta, Canada.
authors.forename: L
authors.initials: L
authors.lastname: Shen
authors.forename: R M
authors.initials: RM
authors.lastname: Rangayyan
mesh_terms: D000465:Algorithms; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008327:Mammography; D011856:Radiographic Image Enhancement; D013902:Radiography, Thoracic