Non-Stationary CT Image Noise Spectrum Analysis

نویسندگان

  • Michael Balda
  • Björn Heismann
  • Joachim Hornegger
چکیده

We investigate the spatial dependency of noise characteristics in CT images. The perceived image quality depends on the noisegranularity. Especially in low-dose applications the noise granularity influences the diagnostic value. A model is presented, that provides two-dimensional, stationary noise realizations for arbitrary image pixel locations from which two-dimensional Noise Power Spectrum estimates can be computed. It fully incorporates the CT reconstruction process for (indirect) fan-beam reconstruction, the quarter offset of the detector channels and the detector noise characteristics. It can be used with simulated and measured data and allows for the assessment of spectral noise characteristics for arbitrary objects.

برای دانلود رایگان 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

Shearlet-Based Adaptive Noise Reduction in CT Images

The noise in reconstructed slices of X-ray Computed Tomography (CT) is of unknown distribution, non-stationary, oriented and difficult to distinguish from main structural information. This requires the development of special post-processing methods based on the local statistical evaluation of the noise component. This paper presents an adaptive method of reducing noise in CT images employing th...

متن کامل

Statistical characterization of noise for spatial standardization of CT scans: Enabling comparison with multiple kernels and doses

Computerized tomography (CT) is a widely adopted modality for analyzing directly or indirectly functional, biological and morphological processes by means of the image characteristics. However, the potential utilization of the information obtained from CT images is often limited when considering the analysis of quantitative information involving different devices, acquisition protocols or recon...

متن کامل

A Time-Frequency approach for EEG signal segmentation

The record of human brain neural activities, namely electroencephalogram (EEG), is generally known as a non-stationary and nonlinear signal. In many applications, it is useful to divide the EEGs into segments within which the signals can be considered stationary. Combination of empirical mode decomposition (EMD) and Hilbert transform, called Hilbert-Huang transform (HHT), is a new and powerful ...

متن کامل

Non-Gaussian Anisotropic Diffusion for Medical Image Processing using the OsiriX DICOM

We present a method for reducing noise in CT (Computed Tomography) and MR (Magnetic Resonance) images that, in addition to other noise sources, is characteristic of the numerical procedures required to construct the images, namely, the (inverse) Radon Transform. In both cases, MR imaging in particular, an additional noise source is due to non-stationary diffusion thereby predicating use of the ...

متن کامل

Noise Properties of Low-Dose CT Projections and Noise Treatment by Scale Transformations

--Projection data acquired for image reconstruction of low-dose computed tomography (CT) are degraded by many factors. These factors complicate noise analysis on the projection data and render a very challenging task for noise reduction. In this study, we first investigate the noise property of the projection data by analyzing a repeatedly acquired experimental phantom data set, in which the ph...

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010