Experimental Investigation of Angular Stackgram Filtering for Noise Reduction of SPECT Projection Data: Study with Linear and Nonlinear Filters

We discuss data filtering prior to image reconstruction. For this kind of filtering, the radial direction of the sinogram is routinely employed. Recently, we have introduced an alternative approach to sinogram data processing, exploiting the angular information in a novel way. This new stackgram representation can be regarded as an intermediate form of the sinogram and image domains. In this experimental study, we compare the radial sinogram and angular stackgram filtering methods using physical SPECT phantoms. Our study is carried out by employing simple linear and nonlinear filters with ten different Gaussian kernels, in order to provide a comparable investigation. According to our results, angular stackgram filtering with the nonlinear filters provides the best resolution-noise tradeoff of the compared methods. Besides, stackgram filtering with these filters seems to preserve the resolution in an exceptional way. Visually, noise in the reconstructed images after stackgram filtering appears more “powdery” in comparison with radial sinogram filtering

Capabilities of multi-pinhole SPECT with two stationary detectors for in vivo rat imaging

We aimed to investigate the image quality of the U-SPECT5/CT E-Class a micro single-photon emission computed tomography (SPECT) system with two large stationary detectors for visualization of rat hearts and bones using clinically available Tc-99m-labelled tracers. Sensitivity, spatial resolution, uniformity and contrast-to-noise ratio (CNR) of the small-animal SPECT scanner were investigated in phantom studies using an ultra-high-resolution rat and mouse multi-pinhole collimator (UHR-RM). Point source, hot-rod, and uniform phantoms with Tc-99m-solution were scanned for high-count performance assessment and count levels equal to animal scans, respectively. Reconstruction was performed using the similarity-regulated ordered-subsets expectation maximization (SROSEM) algorithm with Gaussian smoothing. Rats were injected with similar to 100 MBq [Tc-99m]Tc-MIBI or similar to 150 MBq [Tc-99m]Tc-HMDP and received multi-frame micro-SPECT imaging after tracer distribution. Animal scans were reconstructed for three different acquisition times and post-processed with different sized Gaussian filters. Following reconstruction, CNR was calculated and image quality evaluated by three independent readers on a five-point scale from 1="very poor" to 5="very good". Point source sensitivity was 567 cps/MBq and radioactive rods as small as 1.2 mm were resolved with the UHR-RM collimator. Collimator-dependent uniformity was 55.5%. Phantom CNR improved with increasing rod size, filter size and activity concentration. Left ventricle and bone structures were successfully visualized in rat experiments. Image quality was strongly affected by the extent of post-filtering, whereas scan time did not have substantial influence on visual assessment. Good image quality was achieved for resolution range greater than 1.8 mm in bone and 2.8 mm in heart. The recently introduced small animal SPECT system with two stationary detectors and UHR-RM collimator is capable to provide excellent image quality in heart and bone scans in a rat using standardized reconstruction parameters and appropriate post-filtering. However, there are still challenges in achieving maximum system resolution in the sub-millimeter range with in vivo settings under limited injection dose and acquisition time

Use of total variation filters in SPECT medical imaging

Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2016, Tutors: Artur Carnicer, Ignasi JuvellsTotal variation denoising filtering is proposed as an alternative to the Butterworth filter, which is widely used in the reconstruction of SPECT medical images. Its advantages lie in the preservation of the image edges while the noise is removed, as opposed to the blurring that characterizes Butterworth filtered images. However, results show that total variation filtering application to SPECT medical images doesn’t represent an improvement in terms of similarity to the reference imag

Tomographic image quality of rotating slat versus parallel hole-collimated SPECT

Parallel and converging hole collimators are most frequently used in nuclear medicine. Less common is the use of rotating slat collimators for single photon emission computed tomography (SPECT). The higher photon collection efficiency, inherent to the geometry of rotating slat collimators, results in much lower noise in the data. However, plane integrals contain spatial information in only one direction, whereas line integrals provide two-dimensional information. It is not a trivial question whether the initial gain in efficiency will compensate for the lower information content in the plane integrals. Therefore, a comparison of the performance of parallel hole and rotating slat collimation is needed. This study compares SPECT with rotating slat and parallel hole collimation in combination with MLEM reconstruction with accurate system modeling and correction for scatter and attenuation. A contrast-to-noise study revealed an improvement of a factor 2-3 for hot lesions and more than a factor of 4 for cold lesion. Furthermore, a clinically relevant case of heart lesion detection is simulated for rotating slat and parallel hole collimators. In this case, rotating slat collimators outperform the traditional parallel hole collimators. We conclude that rotating slat collimators are a valuable alternative for parallel hole collimators

J-PET Framework: Software platform for PET tomography data reconstruction and analysis

J-PET Framework is an open-source software platform for data analysis, written in C++ and based on the ROOT package. It provides a common environment for implementation of reconstruction, calibration and filtering procedures, as well as for user-level analyses of Positron Emission Tomography data. The library contains a set of building blocks that can be combined by users with even little programming experience, into chains of processing tasks through a convenient, simple and well-documented API. The generic input-output interface allows processing the data from various sources: low-level data from the tomography acquisition system or from diagnostic setups such as digital oscilloscopes, as well as high-level tomography structures e.g. sinograms or a list of lines-of-response. Moreover, the environment can be interfaced with Monte Carlo simulation packages such as GEANT and GATE, which are commonly used in the medical scientific community.Comment: 14 pages, 5 figure