Iterative reconstruction in image space
Instead of reducing the amount and complexity of corrective models to gain reconstruction speed Siemens Healthineers has developed a new method for iterative reconstruction which maintains the image correction quality of theoretical iterative reconstruction.
To accelerate the convergence of the reconstruction and to avoid long reconstruction times IRIS applies the raw data reconstruction only once. During this newly developed initial raw data reconstruction a so-called master image is generated that contains the full amount of raw data information yet at the expense of significant image noise. The following iterative corrections known from theoretical iterative reconstruction are consecutively performed in the image space. They “clean up” the image and remove the image noise without degrading image sharpness. Therefore, a time-consuming repeated projection and corresponding back projection can be avoided. In addition, the noise texture of the images is comparable to standard well-established convolution kernels.
Features & Benefits
• Image quality improvement
• Fast recon in image space
• Well-established image impression