Ray Contribution Masks for Structure Adaptive Sinogram Filtering

• Published in: IEEE transactions on medical imaging Vol. 31; no. 6; pp. 1228 - 1239
• Main Authors: Balda, M., Hornegger, J., Heismann, B.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.06.2012; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computed tomography; Computed tomography (CT); Detectors; dose reduction; Humans; Image edge detection; Image reconstruction; Kernel; Noise; Noise reduction; nonlinear filters; Phantoms, Imaging; Radiation Dosage; Radiation Protection - methods; Radiographic Image Enhancement - methods; Radiographic Image Interpretation, Computer-Assisted - methods; Reproducibility of Results; Sensitivity and Specificity; Tomography, X-Ray Computed - instrumentation; Tomography, X-Ray Computed - methods
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/TMI.2012.2187213

The patient dose in computed tomography (CT) imaging is linked to measurement noise. Various noise-reduction techniques have been developed that adapt structure preserving filters like anisotropic diffusion or bilateral filters to CT noise properties. We introduce a structure adaptive sinogram (SAS) filter that incorporates the specific properties of the CT measurement process. It uses a point-based forward projector to generate a local structure representation called ray contribution mask (RCM). The similarities between neighboring RCMs are used in an enhanced variant of the bilateral filtering concept, where the photometric similarity is replaced with the structural similarity. We evaluate the performance in four different scenarios: The robustness against reconstruction artifacts is demonstrated by a scan of a high-resolution-phantom. Without changing the modulation transfer function (MTF) nor introducing artifacts, the SAS filter reduces the noise level by 13.6%. The image sharpness and noise reduction capabilities are visually assessed on in vivo patient scans and quantitatively evaluated on a simulated phantom. Unlike a standard bilateral filter, the SAS filter preserves edge information and high-frequency components of organ textures well. It shows a homogeneous noise reduction behavior throughout the whole frequency range. The last scenario uses a simulated edge phantom to estimate the filter MTF for various contrasts: the noise reduction for the simple edge phantom exceeds 80%. For low contrasts at 55 Hounsfield units (HU), the mid-frequency range is slightly attenuated, at higher contrasts of approximately 100 HU and above, the MTF is fully preserved.