Recently, I had cause to have a Medical Resonance Imaging scan (MRI) at a local hospital.  When the scan was complete, my radiographer gave me a CD containing the scan and sent me on my way.

As I have a few medically curious colleagues, I uploaded the contents of the CD to a fileshare in the office so that others could look at the images.

We had fun looking through the images to try and identify body parts.  We also ran them through Replify Accelerator and noticed great offload when loading the images.


On initial load, we saw that the MRI viewer loaded 47MB of data, but with Replify optimizing this, only 17MB of data actually traversed the network.

If we closed the viewer and loaded the images again, we could see that the same 47MB download resulted in a  500KB transfer.  This was solely down to the fact that the Replify cache had been populated with all the images on the initial download.  This result is in line with what we would expect in this use case.


The great results above were down to the fact that the image data was uncompressed and the data contained a lot of duplication.  i.e. We detected over 2000 blocks of duplicate data on the initial load.  This meant that our caching algorithms could provide benefit immediately.

The images are stored in a format called DICOM which has been about for several decades now.  A large number of radiology imaging systems worldwide use it.  The data processed by these is important.  Hence changing the standard to make it more efficient without breaking anything is a huge challenge.

A consequence of this is that any inefficiencies in the storage format will remain for a long time.  Improving this without disrupting existing users of the technology is a large challenge.

The amount of this data available is always increasing.  Sharing images between healthcare professionals at different facilities is also becoming more common.  When using the DICOM format, this means that wide area networks are processing more data than they need to.

Having Replify Accelerator optimizing this data would free up bandwidth on critical hospital networks.  Not only that, it would do it without having to make changes to expensive medical equipment.  We could also ensure that the well established working practices of busy healthcare professionals does not have to change.

If you need to know more about how Replify Accelerator could help you optimize your medical imaging data, please contact

Oh and by the way, my MRI results came back absolutely normal!