Methods and limits of digital image compression of retinal images for telemedicine.

PURPOSE To investigate image compression of digital retinal images and the effect of various levels of compression on the quality of the images. METHODS JPEG (Joint Photographic Experts Group) and Wavelet image compression techniques were applied in five different levels to 11 eyes with subtle retinal abnormalities and to 4 normal eyes. Image quality was assessed by four different methods: calculation of the root mean square (RMS) error between the original and compressed image, determining the level of arteriole branching, identification of retinal abnormalities by experienced observers, and a subjective assessment of overall image quality. To verify the techniques used and findings, a second set of retinal images was assessed by calculation of RMS error and overall image quality. RESULTS Plots and tabulations of the data as a function of the final image size showed that when the original image size of 1.5 MB was reduced to 29 KB using JPEG compression, there was no serious degradation in quality. The smallest Wavelet compressed images in this study (15 KB) were generally still of acceptable quality. CONCLUSIONS For situations where digital image transmission time and costs should be minimized, Wavelet image compression to 15 KB is recommended, although there is a slight cost of computational time. Where computational time should be minimized, and to remain compatible with other imaging systems, the use of JPEG compression to 29 KB is an excellent alternative.

[1]  Philip F. Judy,et al.  Acceptable compression ratios for CR images for PACS archives , 1999, Medical Imaging.

[2]  Michel Barlaud,et al.  Image coding using wavelet transform , 1992, IEEE Trans. Image Process..

[3]  Robert H. Eikelboom,et al.  Digital image compression of retinal images for telemedicine applications , 1998 .

[4]  A. R. Potter,et al.  Avoidable blindness. , 1991, BMJ.

[5]  A. Manduca,et al.  Wavelet compression of medical images. , 1998, Radiology.

[6]  I J Constable,et al.  Non-mydriatic fundus photography: a viable alternative to fundoscopy for identification of diabetic retinopathy in an Aboriginal population in rural Western Australia? , 1998, Australian and New Zealand journal of ophthalmology.

[7]  A Bittorf,et al.  Resolution requirements for digital images in dermatology. , 1997, Journal of the American Academy of Dermatology.

[8]  L G Yamamoto,et al.  Using JPEG image compression to facilitate telemedicine. , 1995, The American journal of emergency medicine.

[9]  N A Blackwell,et al.  Telemedicine ophthalmology consultation in remote Queensland , 1997, The Medical journal of Australia.

[10]  R H Eikelboom,et al.  Tele-ophthalmic screening using digital imaging devices. , 1998, Australian and New Zealand journal of ophthalmology.

[11]  J D Hazle,et al.  Introduction to wavelet-based compression of medical images. , 1998, Radiographics : a review publication of the Radiological Society of North America, Inc.

[12]  Crump Wj,et al.  A field trial of the NASA telemedicine instrument pack in a family practice , 1996 .

[13]  Douglas G. Altman,et al.  Practical statistics for medical research , 1990 .

[14]  G. W. Snedecor Statistical Methods , 1964 .

[15]  Christopher Y. Kim Reevaluation of JPEG image compression to digitalized gastrointestinal endoscopic color images: a pilot study , 1999, Medical Imaging.

[16]  D M Marcus,et al.  Telemedicine diagnosis of eye disorders by direct ophthalmoscopy. A pilot study. , 1998, Ophthalmology.

[17]  Walter F. Good,et al.  Visually weighted assessment of image degradation resulting from image compression , 1996, Medical Imaging.

[18]  R D Billica,et al.  A field trial of the NASA Telemedicine Instrument Pack in a family practice. , 1996, Aviation, space, and environmental medicine.