Physical characterization of a new CT iterative reconstruction method operating in sinogram space

نویسندگان

  • Caterina Ghetti
  • Francesca Palleri
  • Giulio Serreli
  • Ornella Ortenzia
  • Livia Ruffini
چکیده

Recently a new iterative reconstruction algorithm named Iterative Reconstruction (SAFIRE) has been released by Siemens. This algorithm works in the raw data domain with noise reduction as main purpose, providing five different strengths. In this study, the effect of SAFIRE on image quality has been investigated using selected phantoms and a comparison with standard filtered back projection (FBP) has been carried out. The following quantitative parameters have been evaluated: image noise, impact of different reconstruction kernels on noise reduction, noise power spectrum (NPS), contrast-to-noise ratio (CNR), spatial resolution, and linearity and accuracy of CT numbers. The influence of strengths on image quality parameters has also been examined. Results show that image noise reduction is independent of reconstruction kernel and strongly related to the strength of SAFIRE applied. The peak of NPS curve for SAFIRE reconstructions is shifted towards low frequencies; this effect is more marked at higher levels of strength. Contrast-to-noise ratio is always improved in SAFIRE reconstruction and increases with higher strength. At different dose levels SAFIRE preserves CT number accuracy, linearity, and spatial resolution, both in transversal and coronal planes. These results confirm that SAFIRE allows for image noise reduction with preserved image quality. First clinical data to validate this phantom analysis and confirm that commercially available iterative algorithms can play an effective role in dose containment.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Model-Based Iterative Algorithm for Dual-Energy X-Ray CT Reconstruction

Recent developments in dual-energy X-ray CT have shown a number of benefits over standard CT for object separation, contrast enhancement, artifact reduction, and material composition assessment. As with traditional CT, model-based iterative approaches to reconstruction offer the opportunity to reduce noise and artifacts in dual energy reconstructions. However, previous approaches to model-based...

متن کامل

High-Resolution Computed Tomography Image Reconstruction in Sinogram Space

An important part of any computed tomography (CT) system is the reconstruction method, which transforms the measured data into images. Reconstruction methods for CT can be either analytical or iterative. The analytical methods can be exact, by exact projector inversion, or nonexact based on Back projection (BP). The BP methods are attractive because of their simplicity and low computational cos...

متن کامل

Reconstruction of High Resolution Computed Tomography Image from Sinogram Space Using Adaptive Row Projection

We deal with the reconstruction of the high-resolution (HR) computed tomography (CT) image from the CT projection data (Sinogram). Spatial resolution is one of the important parameters of CT images. Spatial resolution is a measure of how close to each other two objects that can still be distinguished. The spatial resolution of CT images depends on the field of view which in turn depends on the ...

متن کامل

Deep-neural-network based sinogram synthesis for sparse-view CT image reconstruction

Recently, a number of approaches to low-dose computed tomography (CT) have been developed and deployed in commercialized CT scanners. Tube current reduction is perhaps the most actively explored technology with advanced image reconstruction algorithms. Sparse data sampling is another viable option to the low-dose CT, and sparse-view CT has been particularly of interest among the researchers in ...

متن کامل

Penalized Weighted Least-Squares Approach for Low-Dose X- Ray Computed Tomography

The noise of low-dose computed tomography (CT) sinogram follows approximately a Gaussian distribution with nonlinear dependence between the sample mean and variance. The noise is statistically uncorrelated among detector bins at any view angle. However the correlation coefficient matrix of data signal indicates a strong signal correlation among neighboring views. Based on above observations, Ka...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 14  شماره 

صفحات  -

تاریخ انتشار 2013