Taiga Yamaya

DOI-PET image reconstruction with accurate system modeling that reduces redundancy of the imaging system

A high-performance positron emission tomography (PET) scanner, which measures depth-of-interaction (DOI) information, is under development at the National Institute of Radiological Sciences in Japan. Image reconstruction methods with accurate modeling of the system response functions have been successfully used to improve PET image quality. It is, however, difficult to apply these methods to the DOI-PET scanner because the dimension of DOI-PET data increases in proportion to the square of the number of DOI layers. In this paper, we propose a compressed imaging system model for DOI-PET image reconstruction, in order to reduce computational cost while keeping image quality. The basic idea of the proposed method is that the DOI-PET imaging system is highly redundant. First, DOI-PET data is transformed into compact data so that data bins with highly correlating sensitivity functions are combined. Then image reconstruction methods based on accurate system modeling, such as the maximum likelihood expectation maximization (ML-EM), are applied. The proposed method was applied to simulated data for the DOI-PET scanner operated in 2-D mode. Then the tradeoff between the background noise and the spatial resolution was investigated. Numerical simulation results show that the proposed method followed by ML-EM reduces computational cost effectively while keeping the advantages of the accurate system modeling and DOI information.

High-resolution image reconstruction method for time-of-flight positron emission tomography.

We present a new image reconstruction method for time-of-flight positron emission tomography (TOF-PET). The TOF-PET measurement system is modelled using the continuous-discrete mapping model, and images are reconstructed using an algebraic technique. The proposed method can produce images with better spatial resolution than conventional methods based on the filtered backprojection method. Numerical simulation results show that accurate modelling of the measurement system improves the spatial resolution and the contrast recovery, while the utilization of TOF information improves the signal-to-noise ratios of images.

On-clock non-paralyzable count-loss model

This paper proposes a new count-loss model that is applicable to radiation detection systems in the field of nuclear medicine. The proposed model, represented by n = (1 - exp(-tau(n)0))/tau(n)0: input rate, n: output rate,tau: system clock duration), gives higher count rates than the well-known standard nonparalyzable (non-extensible) model represented by n = n0/(1 + tau(n)0) does, being equally simple. This model assumes that a part of the data processing is performed on a fixed system clock, requiring a data buffering function (latch) to retain digital event information temporarily, and that input timing is random. The models simple interpretation and expression also offers an advantage over various other advanced count-loss models proposed so far. This model was found to be a better fit to a data-acquisition system for a positron emission tomography scanner.

A performance study of the next generation PET using a new histogramming method for the DOI detector

The next generation PET scanner named jPET-D4 is being carried out at the National Institute of Radiological Sciences (NIRS) in Japan. At this stage, we plan to apply the reconstruction techniques after the histogramming of list-mode data because it is easy to implement and has low computational cost. The jPET-D4 has 4 layers DOI detectors and it can obtain true list-mode data. However, the conventional histogramming technique is inapplicable to 4 layer DOI detectors, so in this paper we propose a new histogramming method which is suitable for the multi-layer DOI detector. In this method, DOI-PET list-mode data is transformed into sinogram with an accurate system model of the crystal block. We also applied the method to simulated data for the JPET-D4 scanner. Numerical simulation results show that the proposed method reduces sampling error effectively while keeping the advantage of DOI information, and the image quality of JPET-D4 is superior to a conventional nonDOI PET scanner.

Algebraic PET image reconstruction with pre-computed reconstruction operators using subsets of sensitivity functions

Algebraic reconstruction methods have been successfully used to improve quality of positron emission tomography (PET) images by accurate modeling of measurement system, but they have computational burden. The authors propose a fast PET image reconstruction method based on an algebraic technique. In this method, reconstruction operators are pre-computed approximately using subsets of sensitivity functions. The subsets contain the sensitivity functions that contribute significantly to each point to be reconstructed. The proposed method was applied to simulated data and experimental data for the ECAT EXACT HR+ (Siemens/CTI) scanner operating in 2D mode. These results show that the proposed method produces images with almost the same quality as the conventional algebraic methods do and has a similar computation time to the filtered backprojection method.

GPU-based optical propagation simulator of a laser-processed crystal block for the X'tal cube PET detector.

The X’tal cube is a next-generation DOI detector for PET that we are developing to offer higher resolution and higher sensitivity than is available with present detectors. It is constructed from a cubic monolithic scintillation crystal and silicon photomultipliers which are coupled on various positions of the six surfaces of the cube. A laser-processing technique is applied to produce 3D optical boundaries composed of micro-cracks inside the monolithic scintillator crystal. The current configuration is based on an empirical trial of a laser-processed boundary. There is room to improve the spatial resolution by optimizing the setting of the laser-processed boundary. In fact, the laser-processing technique has high freedom in setting the parameters of the boundary such as size, pitch, and angle. Computer simulation can effectively optimize such parameters. In this study, to design optical characteristics properly for the laser-processed crystal, we developed a Monte Carlo simulator which can model arbitrary arrangements of laser-processed optical boundaries (LPBs). The optical characteristics of the LPBs were measured by use of a setup with a laser and a photo-diode, and then modeled in the simulator. The accuracy of the simulator was confirmed by comparison of position histograms obtained from the simulation and from experiments with a prototype detector composed of a cubic LYSO monolithic crystal with 6xa0×xa06xa0×xa06 segments and multi-pixel photon counters. Furthermore, the simulator was accelerated by parallel computing with general-purpose computing on a graphics processing unit. The calculation speed was about 400 times faster than that with a CPU.

DOI-PET image reconstruction with accurate system model reducing redundancy of imaging system

A high-performance PET scanner, which measures depth-of-interaction (DOI) information, is in progress at the National Institute of Radiological Sciences in Japan. Image reconstruction methods with accurate modeling of the system response functions have been successfully used to improve PET image quality. It is, however, difficult to apply these methods to the DOI-PET system because the dimension of DOI-PET data increases in proportion to the square of the number of DOI layers. In this paper, we propose a compressed imaging system model for DOI-PET image reconstruction, in order to reduce computational cost with keeping image quality. The basic idea of the proposed method is that the DOI-PET system is highly redundant. First, DOI-PET data are transformed into compact data so that data bins of which sensitivity functions highly correlate are combined. Then image reconstruction methods based on accurate system modeling, such as the maximum likelihood expectation maximization (NIL-EM), are applied. The proposed method was applied to simulated data for the DOI-PET operated in 2D mode. Then the trade-off between the background noise and the spatial resolution was investigated. Numerical simulation results show that the proposed method followed by ML-EM reduces computational cost effectively with keeping the advantages of the accurate system modeling and DOI information.

Fast algebraic reconstruction using subsets of PET data

Filtered backprojection (FBP) method for positron emission tomography (PET) produces artifacts in the reconstructed images when the measurement system has the shift-variant characteristics. On the other hand, the conventional algebraic reconstruction methods, such as the generalized analytic reconstruction from discrete samples (CARDS), the natural pixel decomposition (NPD) and the algebraic reconstruction technique (ART), can correct these characteristics, while these methods have computational burden. Here, the authors propose a fast image reconstruction method for PET using an algebraic technique. In this method, a reconstruction operator is given approximately using subsets of sensitivity functions. The subsets are designed by selecting the sensitivity functions that have high sensitivity to each point to be reconstructed and by keeping an accuracy of the reconstructed images. The proposed method was applied to simulated data for the scanner, ECAT EXACT HR+ (Siemens/CTI) working in the 2D mode. This result shows that the proposed method produces images with almost the same quality as the conventional algebraic methods do and has a similar computation time to FBP method.

Fingerprint verification for smart-card holders based on an optical image encryption scheme

Fingerprint verification for smart card holders is one of the methods which are able to identify smart card holders with a high level of security. However, an ingenious implementation is needed to execute it in the embedded processor quickly and safely, because of its computational burden and the limitation of the smart card performance. For this purpose, we propose a hybrid method which is a combination of personal identification number (PIN) verification with a smart card and an optical fingerprint verification method. The result of a preliminary computer simulation to evaluate the proposed system shows that false acceptance rate is completely zero, though false rejection rate is a little inferior to the conventional figerprint verification system.