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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jornsten, R. Bin Yu Wei Wang Ramchandran, K. |
| Copyright Year | 2002 |
| Description | Author affiliation: California Univ., Berkeley, CA, USA (Jornsten, R.; Bin Yu; Wei Wang; Ramchandran, K.) |
| Abstract | Microarray image technology is a powerful tool for monitoring the expression of thousands of genes simultaneously. Each microarray experiment produces immense amounts of image data, and efficient storage and transmission requires compression that utilizes the microarray image's structure and unique analysis goals. We have developed a progressive compression scheme for microarray images which can be either lossy or lossless. Our scheme has a coded data structure that allows fast decoding and reprocessing of image subsets, and includes summary statistics and image segmentation information. Since visual fidelity is not the end goal for microarray images, we introduce a new measure of distortion for lossy compression: the sensitivity of microarray information extraction to compression loss. We find that a lossy compression ratio of 8:1 for cDNA microarrays minimally affects downstream processing. The average lossless compression ratio is 1.83:1 for cDNA images and 2.43:1 for inkjet images, comparable to state-of-the-art lossless schemas, yet with added flexibility and information. |
| Sponsorship | IEEE Signal Process. Soc |
| Starting Page | 961 |
| Ending Page | 964 |
| File Size | 283221 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780376226 |
| ISSN | 15224880 |
| DOI | 10.1109/ICIP.2002.1039134 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2002-09-22 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image coding Image storage Monitoring Image analysis Data structures Decoding Statistics Image segmentation Distortion measurement Loss measurement |
| Content Type | Text |
| Resource Type | Article |
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