Wyniki wyszukiwania - Biblioteka Nauki

1

E.Cam DUET gamma camera model validation in GATE

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Borys D. , Szczucka K. , Gorczewski K. , Bekman B.

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tom Vol. 11

245--252

EN

Monte Carlo simulations are more and more popular trend in nuclear medicine imaging. They were also widely used in radiotherapy and brachytherapy with use of more general simulation software. GATE (Geant4 Application for Tomographic Emission) is a platform developed on general Monte Carlo code designed for simulating and tracking the passage of particles through matter (Geant4) but is specifically designed for nuclear medicine imaging purposes. The aim of this work was to create and validate a model of specific gamma-camera (E.Cam DUET), used in our department, for further use in image analysis and dosimetry field, with GATE simulation platform. We have modeled in first step a point source in the air in three configurations of gamma camera (without collimator, with low-energy high-resolution (LEHR) collimator and with high-energy (HE collimator)), then we have created a phantom with three spherical sources of different sizes but with the same concentration of the radiopharmaceutical. Simulation results were compared to the measured values of the energy spectrum and images obtained on the detectors, and show a good agreement for the point source experiments and revealed some differences for the phantom studies. This results shows that some additional tests and refinements are required but also allows us to study the image degrading quality factors, such as septal penetration and to work towards eliminating them from the pictures.

2

System matrix computation for iterative reconstruction algorithms in SPECT based on direct measurements

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Borys D. , Szczucka-Borys K. , Gorczewski K.

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tom Vol. 21, no 1

193-202

EN

A method for system matrix calculation in the case of iterative reconstruction algorithms in SPECT was implemented and tested. Due to a complex mathematical description of the geometry of the detector set-up, we developed a method for system matrix computation that is based on direct measurements of the detector response. In this approach, the influence of the acquisition equipment on the image formation is measured directly. The objective was to obtain the best quality of reconstructed images with respect to specified measures. This is indispensable in order to be able to perform reliable quantitative analysis of SPECT images. It is also especially important in non-hybrid gamma cameras, where not all physical processes that disturb image acquisition can be easily corrected. Two experiments with an 131I point source placed at different distances from the detector plane were performed allowing the detector response to be acquired as a function of the point source distance. An analytical Gaussian function was fitted to the acquired data in both the one- and the two-dimensional case. A cylindrical phantom filled with a water solution of 131I containing a region of 'cold' spheres as well as a uniform solution (without any spheres) was used to perform algorithm evaluation. The reconstructed images obtained by using four different of methods system matrix computation were compared with those achieved using reconstruction software implemented in the gamma camera. The contrast of the spheres and uniformity were compared for each reconstruction result and also with the ranges of those values formulated by the AAPM (American Association of Physicists in Medicine). The results show that the implementation of the OSEM (Ordered Subsets Expectation Maximization) algorithm with a one-dimensional fit to the Gaussian CDR (Collimator-Detector Response) function provides the best results in terms of adopted measures. However, the fit of the two-dimensional function also gives satisfactory results. Furthermore, the CDR function has the potential to be applied to a fully 3D OSEM implementation. The lack of the CDR in system matrix calculation results in a very noisy image that cannot be used for diagnostic purposes.

3

Node assignment problem in Bayesian networks

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Polańska J. , Borys D. , Polański A.

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tom Vol. 16, no 2

233-240

EN

This paper deals with the problem of searching for the best assignments of random variables to nodes in a Bayesian network (BN) with a given topology. Likelihood functions for the studied BNs are formulated, methods for their maximization are described and, finally, the results of a study concerning the reliability of revealing BNs’ roles are reported. The results of BN node assignments can be applied to problems of the analysis of gene expression profiles.

4

Study and adjustment of dermoscopic image processing algorithms for lesion border detection

88%

Borys D. , Szeremet M. , Psiuk-Maksymowicz K. , Ostrowski Z. , Frąckiewicz M.

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tom Vol. 37, nr 3B

33-46

EN

The goal of our work was an initial preprocessing of dermoscopic images towards accurate lesion border detection. Four algorithms were proposed and analyzed: MS – algorithm using mean shift clustering, HE – algorithm using histogram equalization, TTH – algorithm using the top-hat transform, PCA – algorithm using principal component analysis. Those algorithms were tested on PH2 images database that contains 200 dermoscopic images, each with a mask of the lesion. Those algorithms were optimized using lesion mask from database and Jaccard index as a measure of similarity of both sets. Simple statistical analysis of indexes was used to compare proposed algorithms in term of their accuracy.

PL

W artykule poruszono problem wstępnego przetwarzania obrazów dermatoskopowych w celu znalezienia konturu znamienia. Zaproponowano i porównano cztery algorytmy: MS – wykorzystujący klasteryzację ‘mean shift’, HE – wykorzystujący wyrównywanie histogramu, TTH – wykorzystujący transformację ‘top-hat’, PCA – wykorzystujący metodę analizy głównych składowych. Algorytmy przetestowano z wykorzystaniem obrazów z bazy PH2, zawierającej 200 obrazów wraz z obrysem ręcznym, a ich parametry dobrano optymalizując indeks Jaccarda. Proste statystyki wyników pozwoliły na porównanie proponowanych algorytmów.

5

Evaluation of SPECT-CT image fusion quality control

75%

Borys D. , Panek R. , Gorczewski K. , d'Amico A. , Steinhof K. , Psiuk-Maksymowicz K.

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2006

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tom Vol. 26, no. 4

79-90

EN

Co-registration of different types of studies into one multimodal image is a very powerful tool which provides more (complementary) information than both studies analyzed separately. The aim of this paper is to demonstrate the importance and to provide a measure of quality control in SPECT-CT studies. The resuIt of image fusion has a diagnostic value only when precision of co-registration is known and falls below an acceptable level. It is very important to evaluate an error of each fusion result. This parameter, while unknown, may lead to incorrect diagnostic decisions, especially when none of the anatomical structures are visualized, like in case of imaging iodine-131 patients.