VoxelCube platform version Axelson released
We are pleased to announce the first release of our VoxelCube medical imaging platform, codenamed Axelson.
- 12 June 2016
We are pleased to announce the first release of our VoxelCube medical imaging platform, codenamed Axelson. The Axelson release consists of a number of core platform building blocks, from user authentication to image storage. With these foundations in place, we can continue to build a platform that is scalable, resilient and secure.
The following functionality is included:
- Account registration
- Account activation
- Log in and log off the platform
- Forgotten password reset
- Change password
- Update account details
Upload and view Analyze images
- Upload an Analyze image, consisting of .hdr and .img files
- View image details (the parameters stored in an Analyze header file)
- View image sections as thumbnails
- View image section scaled to fit browser window
Axelson release showing coronal brain sections
The Axelson release supports 2D and 3D Analyze images with voxel intensities encoded by 8-bit unsigned or 16-bit signed integers. The heights and widths of voxels comprising image sections should be isotropic. Finally, the platform colour mapper assigns a greyscale to each voxel according to its intensity, with the smallest intensity coloured black and the largest intensity coloured white.
The platform can store hundreds of Terabytes of image data and is geo-redundant. Image data is replicated between primary and secondary datacentres that are hundreds of miles apart. This ensures image data is durable even in the case of a datacentre outage or a disaster in which the primary datacenter is not recoverable.
Now that Axelson is live, we aim to deploy future iterations of the platform quickly and we encourage early adopters to give feedback and help us build a platform that can truly benefit the medical imaging community. The next release of the platform will include volume estimation using Cavalieri's principle.
If you would like to trial the platform, please contact us via our Twitter account, @getvoxelcube, or email us using the address hello at VoxelCube dot com.