G. Kontaxakis

List-mode-based reconstruction for respiratory motion correction in PET using non-rigid body transformations

Respiratory motion in emission tomography leads to reduced image quality. Developed correction methodology has been concentrating on the use of respiratory synchronized acquisitions leading to gated frames. Such frames, however, are of low signal-to-noise ratio as a result of containing reduced statistics. In this work, we describe the implementation of an elastic transformation within a list-mode-based reconstruction for the correction of respiratory motion over the thorax, allowing the use of all data available throughout a respiratory motion average acquisition. The developed algorithm was evaluated using datasets of the NCAT phantom generated at different points throughout the respiratory cycle. List-mode-data-based PET-simulated frames were subsequently produced by combining the NCAT datasets with Monte Carlo simulation. A non-rigid registration algorithm based on B-spline basis functions was employed to derive transformation parameters accounting for the respiratory motion using the NCAT dynamic CT images. The displacement matrices derived were subsequently applied during the image reconstruction of the original emission list mode data. Two different implementations for the incorporation of the elastic transformations within the one-pass list mode EM (OPL-EM) algorithm were developed and evaluated. The corrected images were compared with those produced using an affine transformation of list mode data prior to reconstruction, as well as with uncorrected respiratory motion average images. Results demonstrate that although both correction techniques considered lead to significant improvements in accounting for respiratory motion artefacts in the lung fields, the elastic-transformation-based correction leads to a more uniform improvement across the lungs for different lesion sizes and locations.

Real-Time Digital Timing in Positron Emission Tomography

Positron emission tomography (PET) requires accurate timing of scintillation events to properly discriminate between coincident and noncoincident pairs. The traditional solution to timing is based on custom application specific integrated circuits (ASIC) designs, whose cost may not be justified in the design of experimental small animal PET scanners. The new generation of PET scanners introduces the idea of continuous sampling of the detected scintillation pulse, replacing event-triggered acquisition front-ends. This approach enables new options to the timing procedure based on digital processing of the sampled pulse signal. This work proposes a time stamping algorithm based on the optically matched filter and compares the potential performance benefits of this approach versus other FIR-based timing algorithms, some of which have been already implemented by different authors. Results show that the coincidence timing resolution may be as low as 1.5 ns without the need of expensive high-speed converters when the proper signal processing is applied.

Respiratory motion correction in PET with super-resolution techniques and non-rigid registration

Respiratory motion causes image degradation and artifacts in positron emission tomography (PET) images and constitutes an important source or error for the interpretation and proper quantization of thoracic and abdominal studies. Current work towards the correction of respiratory motion effects is mostly based on the acquisition of respiratory synchronized data which, on the other hand, leads to images with low statistics and therefore increased noise level. Super- Resolution (SR) techniques deal with how to combine several images into an enhanced high-resolution image, and in this work we study the application of SR to respiratory-gated PET images to produce a respiratory motion compensated image that incorporates the information provided by all the gated frames acquired. A B-spline based non-rigid registration algorithm is used for estimating the deformations among frames. We present preliminary results on a simulated PET/CT image sequence, corresponding to a thoracic study where a number of different sized nodular lesions were included inside the lungs. The resulting PET image allows better discrimination of the lesions and improved contrast, compared to each of the gated frames and to simple averaging of all the frames after registration.

New embedded digital front-end for high resolution PET scanner

This work describes a new digital front-end for a high-resolution low-cost animal PET scanner which is currently under development. The advances in flexibility and size of modern FPGAs together with the release of new tools enable the integration of most of the front-end electronics in a single FPGA. The implemented system includes a small 32-bit RISC processor, several peripherals attached to the internal buses and a special DSP unit closely attached to the processor which is dedicated to the detection of the gamma events. On top of these, a small footprint real time operating system abstracts the underlying hardware, providing the mechanisms to combine on-chip slow control and data streaming.

Incorporation of elastic transformations in list-mode based reconstruction for respiratory motion correction in PET

Respiratory motion in emission tomography leads to reduced image quality. Proposed correction methodology has been concentrating on the use of respiratory synchronised acquisitions leading to gated frames. Such frames however are of low signal to noise ratio as a result of containing reduced statistics. Therefore a method accounting for respiratory motion effects without affecting the statistical quality of the reconstructed images is necessary. In this work we describe the implementation of an elastic transformation within a list-mode based reconstruction for the correction of respiratory motion over the thorax. The developed algorithm was evaluated using datasets of the NCAT phantom generated at different points throughout the respiratory cycle. List mode data based PET simulated frames were subsequently produced by combining the NCAT datasets with a Monte Carlo simulation. Transformation parameters accounting for respiratory motion were estimated according to an elastic registration of the NCAT dynamic CT images and were subsequently applied during the image reconstruction of the original emission list mode data. The One-pass list mode EM (OPL-EM) algorithm was modified to integrate the elastic transformation. The corrected images were compared with those produced using an affine transformation of list mode data prior to reconstruction, as well as with uncorrected respiratory motion average images. Results demonstrate that although both correction techniques considered lead to significant improvements in accounting for respiratory motion artefacts in the lungs and heart, the elastic transformation based correction leads to a more uniform improvement across the lung field for different lesion sizes.

Super-resolution in 4D positron emission tomography

Respiratory synchronized acquisitions lead to noisy images. Super-resolution techniques deal with the enhancement of several slightly different low-resolution images into a single high-resolution image. A maximum a-posteriori (MAP) super-resolution algorithm has been implemented and applied to respiratory gated PET images for motion compensation. The algorithm was tested on a GATE simulated datasets. It consisted of 8 frames of the NCAT phantom with lesions between 15–22mm placed throughout the lungs. Images were reconstructed using the OPLEM algorithm. Super-resolution was performed on the gated frames through a MAP algorithm, using a Huber prior as a regularization term to ensure convergence. The optimization of the function yielded by the MAP method was performed through a steepest descent algorithm. Motion fields were recovered using a previously presented elastic registration algorithm. Image enhancement was assessed by estimating signal to noise ratio (SNR) and contrast in regions of interest.

Respiratory Motion Correction in 4D PET/CT: Comparison of Implementation Methodologies for Incorporation of Elastic Transformations in the Reconstruction System Matrix

Respiratory motion in emission tomography leads to reduced image quality. Proposed correction methodology has been concentrating on the use of respiratory synchronised acquisitions leading to gated frames. Such frames however are of low signal to noise ratio as a result of containing reduced statistics. Therefore a method accounting for respiratory motion effects without affecting the statistical quality of the reconstructed images is necessary. In this work we describe the implementation of an elastic transformation within a list-mode based reconstruction for the correction of respiratory motion over the thorax. The developed algorithm was evaluated using datasets of the NCAT phantom generated at different points throughout the respiratory cycle. List mode data based PET simulated frames were subsequently produced by combining the NCAT datasets with a Monte Carlo simulation. Transformation parameters accounting for respiratory motion were estimated according to an elastic registration of the NCAT dynamic CT images and were subsequently applied during the image reconstruction of the original emission list mode data. The One-pass list mode EM (OPL-EM) algorithm was modified to integrate the elastic transformation in the sensitivity matrix. Three different implementations have been investigated (no interpolation, trilinear interpolation, b-spline functions incorporation). The corrected images were compared with uncorrected respiratory motion average images. Results demonstrate that the use of elastic transformations in the reconstruction system matrix lead to uniform improvement across the lung field for different lesion sizes. The use of a trilinear interpolation or the incorporation of the b-spline functions lead to times of execution equivalent to standard image reconstruction. However, trilinear interpolation leads to artefacts in areas such as the diaphragm where the largest elastic deformations are occurring.