Interactively variable isotropic resolution in computed tomography

Abstract

An individual balancing between spatial resolution and image noise is necessary to fulfil the diagnostic requirements in medical CT imaging. In order to change influencing parameters, such as reconstruction kernel or effective slice thickness, additional raw-data-dependent image reconstructions have to be performed. Therefore, the noise versus resolution trade-off is time consuming and not interactively applicable. Furthermore, isotropic resolution, expressed by an equivalent point spread function (PSF) in every spatial direction, is important for the undistorted visualization and quantitative evaluation of small structures independent of the viewing plane. Theoretically, isotropic resolution can be obtained by matching the in-plane and through-plane resolution with the aforementioned parameters. Practically, however, the user is not assisted in doing so by current reconstruction systems and therefore isotropic resolution is not commonly achieved, in particular not at the desired resolution level. In this paper, an integrated approach is presented for equalizing the in-plane and through-plane spatial resolution by image filtering. The required filter kernels are calculated from previously measured PSFs in x/y- and z-direction. The concepts derived are combined with a variable resolution filtering technique. Both approaches are independent of CT raw data and operate only on reconstructed images which allows for their application in real time. Thereby, the aim of interactively variable, isotropic resolution is achieved. Results were evaluated quantitatively by measuring PSFs and image noise, and qualitatively by comparing the images to direct reconstructions regarded as the gold standard. Filtered images matched direct reconstructions with arbitrary reconstruction kernels with standard deviations in difference images of typically between 1 and 17 HU. Isotropic resolution was achieved within 5% of the selected resolution level. Processing times of 20-100 ms per frame allow for interactive use.

Physical characterization and performance evaluation of an x-ray micro-computed tomography system for dimensional metrology applications

“…Generally, a limit of contrast transmission and resolution in CT imaging is usually linked to the magnification factor, the effective focal spot size, the spatial transmission properties (resolution) of the detector system, the reconstruction method and the voxel size itself, whereas the voxel size should not significantly affect the system's resolution (Nyquist criterion) [43]. By PSF measurements, it is possible to investigate the contrast transmission locally in the measuring volume.…”

To bin or not to bin? The effect of CT system limiting resolution on noise and detectability

“…The variance weighs the noise in all frequencies of the reconstructed image equally but the task of detecting a target depends on the frequency content of the target being imaged. Because of this, the noise analysis was extended to study the frequency dependent noise properties (Riederer et al 1978, Kijewski and Judy 1987, Siewerdsen and Jaffray 2000, Wagner et al 1979, Kak and Slaney 2001, Baek and Pelc 2010, 2011a, 2011b, Boedeker et al 2007, Tward and Siewerdsen 2009, Lapp et al 2008.…”

A GPU-Accelerated Modified Unsharp-Masking Method for High-Frequency Background- Noise Suppression

“…In fact, the mask often contains highfrequency noise components along with edge-information, and thus can lead to noise-amplification. Over the past several years, quite a few UM-inspired techniques [18][19][20][21][22][23][24][25][26][27][28][29][30][31] were reported which have significantly improved the image quality and a few of them further dealt with the noise amplification issue as well.…”