Thiagarajan, named India's Junior Scientist of the Year in 2001, has run a shop of 40 mathematicians for the past five years to research Adaptive Binary Optimization technology, the backbone of .Muv, resulting in what he says are new limits to algorithm compression.
"The .Muv is a completely new image," he said, adding that because of the lower complexity of compression it makes less demand on hardware, and is much faster to transfer and compress.
"Based on the algorithm [ABO] we have shown that we can exceed the so-called theoretical limits of compression.
"For example, if an original image size was 368,000 bytes, theoretical limits so far calculate it [the image] can be compressed one-way to 142,000 bytes, but we have shown it can be compressed up to 48,000 bytes -- it is almost optimizing the binary system."
Thiagarajan said the process works through compiling the image matrix (the array of rows and columns) of a picture to a number of byte values and if various pixels are the same throughout the image then the same number is used and the values stored and sent separately.
The first product released by MatrixView using the .Muv is Echoview, which compresses ultrasonic or cardiogram images and stores them in a central server so doctors can access the images without hardware upgrading or loosing image quality.
The Adaptive Binary Optimization technology is being used by Indian-based Chartered Image Management Analysis and Report Medical Networks for Indian doctors to remotely diagnose patients. The first-phase rollout includes six radiology imaging groups in South India with a national rollout expected in 2006.
MatrixView managing director Ravi Govindan said the ABO technology is ideally suited to the teleradiology market which has so far been limited by high-end computing power and bandwidth resources due to the large sizes of medical data. Govindan added ABO is suited to applications within teleradiology due to the ability to compress data with higher compression ratios.
MatrixView is based in Singapore.