Physics in medicine and biology
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Quantitative MR imaging is a potential tool for tissue characterization; in particular, proton density and proton relaxation times can be derived from MR signal analysis. However, MR image noise affects the accuracy of measurements and the number of tissue parameters that can be reliably estimated. Filtering can be used to limit image noise; however this reduces spatial resolution. ⋯ Compared to other classical filters, this filter achieves the best compromise between spatial resolution and noise reduction. The filter was specifically used to reliably determine the bi-component transverse relaxation of protons in adipose tissue. Long and short relaxation times and the relative proton fraction of each component were obtained with a degree of uncertainty of less than 10% and an accuracy of 95%.
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Automatic beam angle selection is an important but challenging problem for intensity-modulated radiation therapy (IMRT) planning. Though many efforts have been made, it is still not very satisfactory in clinical IMRT practice because of overextensive computation of the inverse problem. In this paper, a new technique named BASPSO (Beam Angle Selection with a Particle Swarm Optimization algorithm) is presented to improve the efficiency of the beam angle optimization problem. ⋯ The optimization results of a simulated case with known optimal beam angles and two clinical cases (a prostate case and a head-and-neck case) show that PSO is valid and efficient and can speed up the beam angle optimization process. Furthermore, the performance comparisons based on the preliminary results indicate that, as a whole, the PSO-based algorithm seems to outperform, or at least compete with, the GA-based algorithm in computation time and robustness. In conclusion, the reported work suggested that the introduced PSO algorithm could act as a new promising solution to the beam angle optimization problem and potentially other optimization problems in IMRT, though further studies need to be investigated.
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Routine quality control (QC) and optimization of image quality of reconstructed images in single photon emission computed tomography (SPECT) and positron emission tomography (PET) remains a relatively qualitative exercise. With the advent of combined SPECT/CT and PET/CT devices, and accurate post hoc co-registration algorithms, the potential exists to utilize high resolution structural information for QC evaluation in addition to their use for anatomical correlation in clinical studies. The aim of this work was to explore, in principle, the uses of x-ray CT data of QC phantoms used in SPECT and PET to develop more objective assessments of performance of the emission tomographic (ET) devices and reconstructed data. ⋯ In this study, we have used this approach to estimate spatial resolution (full width at half maximum, FWHM) and recovered contrast in reconstructed images of a SPECT phantom. Two independent methods were used to measure spatial resolution, obtaining excellent agreement. In conclusion, the ability to produce high resolution synthetic phantoms in emission tomography QC affords an objective approach to assessing system performance and optimizing protocols which is readily automated and quantifiable.
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Comparative Study
Assessment of rigid multi-modality image registration consistency using the multiple sub-volume registration (MSR) method.
Registration of different imaging modalities such as CT, MRI, functional MRI (fMRI), positron (PET) and single photon (SPECT) emission tomography is used in many clinical applications. Determining the quality of any automatic registration procedure has been a challenging part because no gold standard is available to evaluate the registration. In this note we present a method, called the 'multiple sub-volume registration' (MSR) method, for assessing the consistency of a rigid registration. ⋯ The results of our MSR method agree with the classification obtained from visual inspection for all cases (p < 0.02 based on ANOVA of the good and bad groups). The proposed method is independent of the registration algorithm and similarity measure. It can be used for multi-modality image data sets and different anatomic sites of the patient.
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Comparative Study
Analysis of discrete and continuous distributions of ventilatory time constants from dynamic computed tomography.
In this study, an algorithm was developed to measure the distribution of pulmonary time constants (TCs) from dynamic computed tomography (CT) data sets during a sudden airway pressure step up. Simulations with synthetic data were performed to test the methodology as well as the influence of experimental noise. Furthermore the algorithm was applied to in vivo data. ⋯ Analysis of the in vivo data showed that in healthy lungs ventilation processes can be more likely characterized by discrete TCs whereas in ARDS lungs continuous distributions of TCs are observed. The temporal behaviour of lung inflation and deflation can be characterized objectively using the described new methodology. This study indicates that continuous distributions of TCs reflect lung ventilation mechanics more accurately compared to discrete TCs.