Parallax Innovations is pleased to preview another cutting-edge product – the CT Sabre.  The CT Sabre is a robotic arm that fits inside the bore of a micro-CT scanner and is controlled remotely through software, allowing you to perform procedures, such as the delivery of therapeutic agents, biopsies, blood sampling, etc.

You can operate the arm during fluoroscopy:
✔ Full control of needle position
✔ Live view of needle under robotic control
✔ Highly accurate needle positioning
✔ Control of animal position
✔ Full control of x-ray angle

Alternatively, you can plan an intervention from a reconstructed 3D volume:
✔ Plan trajectory of needle with full anatomical information
✔ Easy-to-use, interactive planner – point and click to define trajectory
✔ No need to re-position the animal between acquisition and intervention

Safe and effective interventions for:
  ✔ Cardiac perfusion
  ✔ Biopsy
  ✔ Tissue injection
  ✔ Cannulation
  ✔ Blood sampling

If you have any questions or comments about the CT Sabre, we would love to hear from you.  Also, continue to watch this blog for future CT Sabre updates.

Another GPU reconstruction progress update day:  See below two line profiles drawn through an aluminum stack phantom, imaged on a CT-120 microCT scanner.  A typical "cupping" artifact, caused by beam hardening, is clearly visible in the left-hand, uncorrected image. The right image demonstrates the advantage of the basic beam hardening correction algorithm integrated into our GPU reconstruction engine.

Click on the image to see a larger version.

Our efforts to integrate our GPU reconstruction engine into different CT scanner platforms continue:  see below a video showing the installation process for the Parallax Innovations GPU engine on an eXplore CT-120 console computer.  The total install time is about 2 minutes, not including the download of the software.  We recommend upgrading to NVidia driver version 295.49, since this driver provides the aforementioned Fermi architecture support such as on the GTX 680 and 690 GPU adapters.

And here's a video comparing CPU vs. GPU CT engines on the same machine:

As before, if you're interested in helping to test this release, don't hesitate to contact us.

Thanks to our friends at Endra Inc., we've had an opportunity to involve ourselves in GPU-based algorithm acceleration. This has ended up, for us, being a substantial deep-dive into technologies such as CUDA and OpenCL, but with significant results. The advantages of GPU acceleration over conventional computing are well known, even in the face of impressive improvements in generalized CPU multi-core capabilities in recent years. These advantages are especially true in the medical imaging field, where almost all compute-intensive tasks in the imaging pipeline are embarrassingly parallel. CT reconstruction is one example that we've chosen to focus on recently - we've started by implementing a flexible GPU-accelerated CT reconstruction framework, that can act as both a platform for algorithm design and development, as well as a de facto replacement for legacy CPU-based reconstruction engines. At the moment, it is capable of reconstructing scan data from GE's Locus, eXplore and Ultra CT products - depending on reception, we may choose to port it to more systems. Our reference implementation uses the well-known stock Feldcamp conebeam backprojection algorithm and is written in python for maximum flexibility. It uses pycuda for the heavy lifting. See below reconstruction results from a variety of platforms -- of particular interest, perhaps, is the NVidia GTX 580 results, for sheer speed, and the NVidia GTX 460M, which is running on a laptop. The latter results compare favorably against a 9-computer beowulf cluster, showing just how far GPU technology has come in recent years. The results are preliminary, and will be updated frequently as our recon engine improves and is tested more widely.

(Note: It seems that the interactive graph does not show up, if you are viewing with Internet Explorer. We apologize for that, but for now, you will have to use one of the other browsers, if you wish to see the results).

Gizmodo has picked up on our friends at Cornell University, with Cornell's $500,000 Micro-CT Scanner Lets You See Small Things in Color 3D, which really demonstrates both the breadth of  capabilities of their eXplore CT-120 scanner, as well as how organized and tech-savy their group is.  It`s worth a perusal.