Medical images are now almost all gathered and stored in a digital
representation for easy transmission and archiving. High resolution
is mandatory for a detailed diagnosis, which requires accurately known location and density information regarding the important features of the image called the regions of interest (ROI). Such features may include non-displaced fractures or small tumors that
can often be difficult to identify. A reduction in size by using compression is necessary for efficient transmission over a wireless link where remote diagnosis may be an only option in many cases. Despite rapid advances in lossy compression, most research in the
compression of medical imagery specifies that the ROI must be conserved as much as possible or compressed with a lossless or near-lossless algorithm. To ensure diagnostic integrity of these crucial regions after transmission, a multiple watermarking technique has been developed which can be used to verify the integrity of the ROI prior to diagnosis. This has the benefit of assuring that incidental degradation has not affected any of the crucial regions. A strong focus is placed on the robustness of the watermarking technique to JPEG compression as well as the issue image file size and quality tradeoff. The most useful contribution in our work is assurance of ROI image content integrity after image files are subject to incidental degradation in these environments. This is made possible with extraction of DCT signature coefficients from the ROI and embedding multiply in the Region of Backgrounds (ROB).
Digital medical images used in radiology are quite different to everyday continuous tone images. Radiology images require that all detailed diagnostic information can be extracted, which traditionally constrains digital medical images to be of large size and stored without loss of information. In order to transmit diagnostic images
over a narrowband wireless communication link for remote diagnosis, lossy compression schemes must be used. This involves discarding detailed information and compressing the data, making it more susceptible to error. The loss of image detail and incidental degradation occurring during transmission have potential legal accountability issues, especially in the case of the null diagnosis of a tumor. The work proposed here investigates techniques
for verifying the voracity of medical images - in particular, detailing the use of embedded watermarking as an objective means to ensure that important parts of the medical image can be verified. We propose a result to show how embedded watermarking can be used to differentiate contextual from detailed information. The type of
images that will be used include spiral hairline fractures and small tumors, which contain the essential diagnostic high spatial frequency information.
The implementation of wavelets in differing areas of signal processing has been a popular research area over the last decade. However, utilising this technology in compressing two dimensional signals, such as digital images is relatively new. Wavelet compression has many distinct advantages over earlier compression methods, the most important of which is suitability to error protection as well as the ability to precisely truncate the compressed bitstream to achieve a desired bit rate for transmission. In this paper some of the recently emerging technologies pertaining to wavelet coding of images will be reviewed, particularly with the use of wireless channels. These developments include techniques to filter images that have been degraded through the addition of noise as well as reconstructing parts of images that have been lost as a result of the fading that characterises wireless mobile environments.
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