Cost-effective handling of digital medical images in the telemedicine environment

Choong, Miew Keen; Logeswaran, Rajasvaran; Bister, Michel

doi:10.1016/j.ijmedinf.2006.05.007

Cited by 23 publications

(7 citation statements)

References 14 publications

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“…There is another issue that is important for considering telemedicine applications; as stated in the following:"Some real-time telemedicine applicationsh aveb een taken up with enthusiasm,evenifformal evidence of cost effectiveness maybelacking" [24]. We thinkthatmosttelemedicine systemsare high cost.Incontrast to the mostofthe telemedicine systems, our telediagnosis system is reasonablyl ow cost,w ith internet-connected PC andD Vc ameras, so thati tm ay substantiallyr esolvet he issue of telemedicine cost.W ec onsider that it is one of the advantageso fo ur telediagnosis system as comparedwith the others [25].…”

Section: Rarelymentioning

confidence: 99%

Development of a Telediagnosis Endoscopy System over Secure Internet

et al. 2008

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Summary Objectives: We developed a new telediagnosis system to securely transmit high-quality endoscopic moving images over the Internet in real time. This system would enable collaboration between physicians seeking advice from endoscopists separated by long distances, to facilitate diagnosis. Methods: We adapted a new type of digital video streaming system (DVTS) to our teleendoscopic diagnosis system. To investigate its feasibility, we conducted a two-step experiment. A basic experiment was first conducted to transmit endoscopic video images between hospitals using a plain DVTS. After investigating the practical usability, we incorporated a secure and reliable communication function into the system, by equipping DVTS with “TCP2”, a new security technology that establishes secure communication in the transport layer. The second experiment involved international transmission of teleendoscopic image between Hawaii and Japan using the improved system. Results: In both the experiments, no serious transmission delay was observed to disturb physicians’ communications and, after subjective evaluation by endoscopists, the diagnostic qualities of the images were found to be adequate. Moreover, the second experiment showed that “TCP2-equipped DVTS” successfully executed high-quality secure image transmission over a long distance network. Conclusions: We conclude that DVTS technology would be promising for teleendoscopic diagnosis. It was also shown that a high quality, secure teleendoscopic diagnosis system can be developed by equipping DVTS with TCP2.

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Section: Rarelymentioning

confidence: 99%

Development of a Telediagnosis Endoscopy System over Secure Internet

et al. 2008

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“…Sone et al proved that there is no loss in diagnostic accuracy for compression ratios up to 9:1 [11]. Compression of medical images is vital in achieving a low bit rate in the representation of radiology images in order to reduce the data volume, without loss in diagnostic information [12,13]. Persons et al discussed diagnostic accuracy and reported that reconstructed medical images with a compression ratio of 9:1 do not result in visual degradation [14].…”

Section: Introductionmentioning

confidence: 99%

Medical Image Compression using Adaptive Subband Threshold

Vidhya¹

2016

Journal of Electrical Engineering and Technology

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-Medical imaging techniques such as Magnetic Resonance Imaging (MRI), ComputedTomography (CT) and Ultrasound (US) produce a large amount of digital medical images. Hence, compression of digital images becomes essential and is very much desired in medical applications to solve both storage and transmission problems. But at the same time, an efficient image compression scheme that reduces the size of medical images without sacrificing diagnostic information is required. This paper proposes a novel threshold-based medical image compression algorithm to reduce the size of the medical image without degradation in the diagnostic information. This algorithm discusses a novel type of thresholding to maximize Compression Ratio (CR) without sacrificing diagnostic information. The compression algorithm is designed to get image with high optimum compression efficiency and also with high fidelity, especially for Peak Signal to Noise Ratio (PSNR) greater than or equal to 36 dB. This value of PSNR is chosen because it has been suggested by previous researchers that medical images, if have PSNR from 30 dB to 50 dB, will retain diagnostic information. The compression algorithm utilizes one-level wavelet decomposition with threshold-based coefficient selection.

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“…The annual volume of imaging data in modern paperless hospitals can approach up to 10 terabytes, heavily pressing the storage and transmission requirements (Choong et al, 2007).…”

Section: Introductionmentioning

confidence: 99%