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Due to the limited resolution of Positron Emission Tomography (PET), loss of signal through Partial Volume is significant for small structures. Consequently, Partial Volume Correction (PVC) is often used in PET imaging to recover this lost signal within images. Numerous methods have been proposed, and can be divided in multiple ways. One division is the separation of methods utilising image based...
We describe a scatter and randoms weighted (SRW) iterative PET reconstruction algorithm. The SRW method is based on the estimation of the trues fraction (TF) within the prompts. Once the TF is estimated, it is then incorporated into the weighting component of the system matrix, and the net result is a scatter and randoms weighting in the sensitivity image similar to the attenuation correction weighting...
TV constrained reconstruction could obtain perfect results from incomplete data, and has been applied to reduce metal artifact by assuming that the projection contaminated by metal is missing. In TV constrained reconstruction, the selection of a proper step parameter for TV minimization procedure is a key point. However, this parameter is usually selected empirically, and it is a constant for all...
Stochastic methods based on Maximum Likelihood Estimation (MLE) provide accurate tomographic reconstruction for emission imaging. Moreover methods based on MLE allow to include an accurate physical model of the imaging setup in the reconstruction process, thus enabling quantitative reconstruction of radio-tracer activity distribution. It has been shown that inclusion of a spatially dependent PSF that...
To improve the estimation at the voxel level in dynamic Positron Emission Tomography (PET) imaging, we propose to develop a convex optimization approach based on a recently proposed parallel proximal method (PPXA). This class of algorithms was successfully employed for 2D deconvolution in the presence of Poisson noise and it is extended here to (dynamic) space + time PET image reconstruction. Hybrid...
This paper presents a generalization of the Bowsher prior for SPECT reconstruction using anatomical prior. Instead of considering a binary selection of the neighbors of each reconstructed voxel based on the anatomical prior values, each neighbors are taken into account with a suitable weight. We tried three different weights. We showed that, for brain SPECT reconstruction using MRI, in the case of...
A general limitation in PET is represented by the poor spatial resolution of the system. To compensate for this limitation by using iterative reconstruction algorithms it is possible to account for the response of the PET system (Point Spread Function, PSF) in the reconstruction scheme to improve PET image quality and quantitative accuracy. Unfortunately, a common behaviour of iterative reconstruction...
In this paper, a Maximum a Posteriori Reconstruction algorithm is applied for the first time to the Siemens 3TMR BrainPET scanner. The implementation of this algorithm is done in the PET REconstruction Software TOolkit. This software is able to cope with 3D PET listmode data and can deal with the specificities of the Siemens 3TMR BrainPET scanner. Simulated data was used to assess the performance...
Tomographic reconstruction based on origin ensembles (OE) is a new procedure for estimation of emission intensity distributions from projection measurements. The advantages of this method over standard iterative approaches are shorter computation time and easier implementation of complex system models in emission tomography (ET) inverse problems. The approach is not based on data likelihood, as are...
We have recently developed a novel x-ray computed tomography (CT) system capable of dense spectral measurements along the energy axis using a photon-counting single-pixel detector. The reconstructions have high energy axis resolution but suffer from noise due to dividing the total x-ray counts into multiple energy bins. We have recently developed two methods to suppress the noise along the energy...
Previously, we presented a direct 4D EM method for producing kinetic parameter images from list mode PET data, where the time-activity curve for each voxel is described by a one tissue compartment model (1T). The initial evaluation was performed with simulation, without random and scatter included. In addition, a practical single-scatter simulation (SSS) method was proposed so that the direct 4D method...
Respiratory motion artifact is one of the factors limiting the diagnostic accuracy of SPECT or PET. Full-torso respiratory motion correction in general requires non-rigid respiratory motion estimation and correction due to different organs moving at different rates and possibly directions. In work we presented a method to reduce noise and equalize organ counts in SPECT, to aid non-rigid motion estimation...
Patient movement during SPECT and PET data acquisition makes serious distortions in reconstructed images. In most conventional methods a correction of this movement is conducted in the sinogram space. However, the direction of movement occurs at an angle that is parallel to collimator holes, making it is difficult to detect the movement of an object. This paper proposes a new correction method of...
Time of flight information is used in PET to improve image quality. However, the nature of the improvement and its relationship with the precision of the time of flight measurement remains to be well-characterized, particularly in the framework of iterative reconstruction. In this work, hot-spheres phantoms are imaged, and the list data are then degraded to simulate systems with poorer timing resolution...
In PET imaging, Noise Equivalent Counts (NEC) represents an estimate of the number of true coincidences necessary in an ideal system to reach the Signal-to-Noise Ratio (SNR) obtained in a real system in the presence of scatter and random coincidences. NEC has been shown to be proportional to the square of image SNR and it is used as an index of the general system performance for conventional PET images...
The core of common statistical iterative reconstruction methods is the maximization of the likelihood that the reconstructed image belongs to the measured data. Since the underlying inverse problem is ill-posed, the likelihood function is often extended by a penalty term to form an objective function, which contains assumptions about the content of the image, most often by favoring smooth images....
During image guided interventional procedures, superior resolution and image quality is critically important. Operating the MAF in the new High Definition (HD) fluoroscopy mode provides high resolution and increased contrast-to-noise ratio. The MAF has a CCD camera and a 300 micron cesium iodide x-ray convertor phosphor coupled to a light image intensifier (LII) through a fiber-optic taper. The MAF...
Early clinical results with time-of-flight (TOF) PET systems have demonstrated the advantages of TOF information in PET reconstruction. Reconstruction approaches in TOF-PET systems include list-mode and binned iterative algorithms as well as confidence-weighted analytic methods. List-mode iterative TOF reconstruction retains the full accuracy of the data in the spatial and temporal domains but is...
With modern cardiac CT scanners detection and classification of coronary artery diseases is a common task. More and more low dose cardiac CT prevails the clinical routine. To suppress noise, a smooth reconstruction kernel is used. Unfortunately this inducts an additional blurring to the images. At high contrast graduations this so-called blooming makes it hard to identify small structures especially...
We describe a new exact analytical algorithm for estimating the single event rates in detectors from random coincidence data (for randoms variance reduction), and detector efficiencies from true coincidence data (for normalization), in positron emission tomography (PET). The estimates are derived from the ratios of the co-fan sums of coincidence events between individual detectors. The co-fan for...
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