Technology - Medicvision




Image enhancement – Noise reduction: Volumetric iterative image reconstruction algorithms

The patented non-linear, volumetric iterative image reconstruction algorithms perform post-scan processing of volumetric scans (e.g. CT, MRI) that dramatically improves signal-to-noise ratio (SNR) and enhances the processed images. The algorithms deconstruct and then reconstruct the scanned volume (e.g. head, chest) in 3D space. Using a proprietary statistical model, noise and signal are differentiated and separated and a perfected image is reconstructed with no loss off detail and valuable information. The images can be reconstructed in multiple reformats (axial, sagittal, coronal) and slice thickness. The company’s volumetric iterative image reconstruction algorithms are protected by two patents granted in USA, EU, Japan and China.


Real time: Parallel image processing on multiple Graphic Processing Units (GPUs)

The volumetric iterative image reconstruction algorithms described above are computational intensive. In order to process large image-sets, Medic Vision developed the capability to process the images by multiple GPUs in parallel to make the algorithm run in real-time. With that, processing of a typical CT scan of 400 images is completed within one minute.


Robust: DICOM and workflow interface software

A software package manages the interfaces between the 3D algorithms and the imaging modality (e.g. CT, MRI) and PACS systems. It is capable of interfacing seamlessly with any scanner (any vendor, any model), PACS and other DICOM stations without affecting the clinical workflow.


Compliance: XR-29 Dose Check and Dose Reporting

An innovative patent-pending CT vendor neutral method for implementing XR-29 functionality, under the most stringent requirements and limitations imposed by the FDA. This method allows performing XR-29 functions without interfering or interrupting the scanner’s design or operation.


High availability: Clustering

In order to support large organizations, with numerous scanners, we developed an application-level clustering software that provides high-availability, failover and load balancing capabilities for such implementations.


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