File Compression for Remote Diagnosis

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A big challenge these days in remote diagnosis technology is getting those big images sent from one place to another. World Changing reported recently about File Compression for Remote Diagnosis. Jamais Cascio said:

Researchers have known for a few years now that applying a mathematical transformation method known as “wavelets” to radiological images can improve the ability of doctors to detect cancer. But Bradley Lucier’s team of mathematicians at Purdue has taken the process to a new level — by using the wavelets method to compress mammogram images by 98%, not only can radiologists still detect cancer better than they can with unmodified images, the mammograms become small enough to send easily over the dial-up computer networks common in poorer parts of the world. The work will appear in the next edition of Radiology.

A single uncompressed mammogram can run up to 50 megabytes in size, and diagnosis typically requires four different images. The wavelet process cuts the file size down to approximately one megabyte per image, well within the capabilities of most dial-up or even cell-phone Internet connections. Although other researchers have demonstrated that the use of wavelets can improve radiological diagnosis, Lucier’s group managed to shrink the image files far more than ever before, using an algorithm Lucier himself created a decade earlier.


Shahid N. Shah

Shahid Shah is an internationally recognized enterprise software guru that specializes in digital health with an emphasis on e-health, EHR/EMR, big data, iOT, data interoperability, med device connectivity, and bioinformatics.