IRIS

IRIS allows to enhance spatial resolution and to reduce image noise by introducing multiple iteration steps in the reconstruction process, thus enabling dose reduction by up to 60%.

To accelerate the convergence of the reconstruction and to avoid long reconstruction times the new 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. The new technique results in artifact and noise reduction, increased image sharpness, and dose savings of up to 60% for a wide range of clinical applications.


Features & Benefits

• Up to 60% dose reduction
• Image quality improvement
• Fast recon in image space
• Well-established image impression

Cechy i korzyści

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