Telepathology is defined as the practice of pathology at a distance using video imaging and telecommunications. In this thesis we address the two main technology challenges in implementing telepathology, viz. compression and transmission of digital pathology images.
One of the barriers to telepathology is the availability and the affordability of high bandwidth communication resources. High bandwidth links are required because of the large size of the uncompressed digital pathology images. For efficient utilization of available bandwidth, these images need to be compressed. However aggressive image compression may introduce objectionable artifacts and result in an inaccurate diagnosis. This discussion helps us to identify two main design challenges in implementing telepathology,
1. Compression: There is a need to develop or select an appropriate image compression algorithm and an image quality criterion to ensure maximum possible image compression, while ensuring that diagnostic accuracy is not compromised.
2. Transmission: There is a need to develop or select a smart image transmission scheme which can facilitate the transmission of the compressed image to the remote pathologist without violating the specified bandwidth and delay constraints.
We addressed the image compression problem by conducting subjective tests to determine the maximum compression that can be tolerated before the pathology images lose their diagnostic value. We concluded that the diagnostically lossless compression ratio is at least around 5 to 10 times higher than the mathematically lossless compression ratio, which is only about 2:1. We also set up subjective tests to compare the performance of the JPEG and the JPEG 2000 compression algorithms which are commonly used for compression of medical images. We concluded that JPEG 2000 outperforms JPEG at lower bitrates (bits/pixel), but both the algorithms perform equally well at higher bitrates.
We also addressed the issue of image transmission for telepathology by proposing a two-stage transmission scheme, where coarse image information compressed at diagnostically lossless level is sent to the clients at the first stage, and the Region of Interest is transmitted at mathematically lossless compression levels at the second stage, thereby reducing the total image transmission delay.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/29761 |
| Date | 08 July 2009 |
| Creators | Khire, Sourabh Mohan |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Thesis |
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