In this work we present a comparison of different methods for reconstructing the position of the events detected by gamma cameras with small Field of View. This task was completed within a project aimed to the develop...
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In this work we present a comparison of different methods for reconstructing the position of the events detected by gamma cameras with small Field of View. This task was completed within a project aimed to the development of an ultra high resolution, MR compatible PET detector camera head based on SiPM detector. It is well known that the spatial resolution deteriorates and the displacement error (defined as the deviation of the reconstructed position from the true position) increases at the edges of the detector. Here we investigate the possibility of improving the detector performance by using different reconstructionmethods. The usual algorithm based on the barycenter fails to track the true position near the edges of the detector. We implemented and tested four different algorithms: the classic barycenter, a modified barycenter method where we consider not the charge collected, but the charge squared (named "barycenter squared") [1], an algorithm based on the estimation of the skewness of the distribution of the light ("skewness") [2], and finally a method based on the minimization of the difference between the distribution of light and a suitable fitting function ("Newton"). It turns out that the use of reconstructionalgorithms different from the classic barycenter can help to improve the performance of the system. In particular, the reconstruction error improves, especially at the edges of the detector. Our simulations show that it is feasible to get submillimeter planar spatial resolutions at the center of the detector and of about 1 mm at the edges of the detector.
The new generation of photon counting pixelated X-ray detectors like the Medipix2 detector are gaining increasing interest in medical imaging. In contrast to conventional systems which integrate the charge released in...
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The new generation of photon counting pixelated X-ray detectors like the Medipix2 detector are gaining increasing interest in medical imaging. In contrast to conventional systems which integrate the charge released in the sensor they are able to count single photons. With this imaging detector it is possible to determine the energy of the incoming X-rays which opens up a new field of applications. One application is the detection of contrast agents in medical imaging which was shown for a silicon sensor. However the absorption efficiency of silicon is very low for the X-ray energies used in medical imaging. High-Z materials such as Cadmium Telluride (CdTe) are therefore promising candidates for the sensor material. With the hybrid design of the Medipix2 detector we are able to realize a photon counting pixelated X-ray detector with CdTe sensor. Crucial for material reconstruction are the energy response functions. With our simulation tool RoSi we are able to simulate these response functions. In this work first results and simulations concerning material reconstruction with a Medipix2 detector with CdTe sensor are shown.
Antiprotons whose potential in clinical applications has not yet been fully studied and explored, interact in a way similar to the widely used protons. The great advantage of antiprotons over protons is that at the en...
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Antiprotons whose potential in clinical applications has not yet been fully studied and explored, interact in a way similar to the widely used protons. The great advantage of antiprotons over protons is that at the end of their path annihilate and release about 1.88GeV more energy. Although many particles are produced by annihilation most of them escape from the target. Detecting a portion of these particles during patient's irradiation would offer the possibility to monitor the beam in the target in real time. In the current work we investigate the feasibility of real time imaging during radiotherapy by using antiproton beam. In this study a prostate case is simulated using one field and given a typical dose fraction of 2Gy to the target. Monte Carlo code is used to calculate the energy spectrum of the most prominent particles that escape from the target which could be detected outside the patient, as well as the degree of scattering of these particles, as an indication of merit for their use in order to produce an image which represents the absorption of the beam in the target. Results based on these criteria suggest that real time imaging is possible by detecting either charged pions or photons which mainly come from pi(0) decays or e(+)e(-) annihilation.
A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The thr...
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A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
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