Purpose: Inter-frame and intra-frame motion can adversely impact the performance of dynamic brain PET imaging. Only correcting the former can still result in degraded qualitative and quantitative performance. Meanwhile, patient motion introduces mismatches between transmission and emission data which may lead to incorrect attenuation and scatter compensation in the reconstruction process. As a result, the reconstructed dynamic images may carry erroneous estimates of radioactivity distribution. We seek a solution to this problem.
Methods: We investigated the use of iterative deconvolution coupled with a proposed use of time-weighted averaging of motion-transformed transmission images to correct the transmission-emission mismatch artifacts in dynamic brain PET images. We performed simulations using real-patient motion profile acquired by the infrared Polaris Vicra motion tracking device which estimates 3-D motion transformations during PET acquisition. This was followed by frame-based motion correction employing three different transmission-emission alignment strategies: transmission image transformed by (1) mean motion transformation, (2) median motion transformation, and (3) the proposed time-weighted average of motion-transformed transmission images.
Results-: The results demonstrate that the proposed approach of using time-weighted averaging of motion transformed transmission images outperforms conventional methods by substantially reducing the transmission-emission mismatch artifacts in the reconstructed images. Coupled with an alignment of the reconstructed frames for inter-frame motion correction and a subsequent iterative deconvolution approach for intra-frame motion correction, the resulting motion compensated images showed superior quality, considerable reduction in error norm and enhanced noise-bias performance compared to conventional methods of transmission-emission mismatch compensation. The performance was consistent across different levels of intra-frame motion, and the algorithm was amenable to different framing schemes.
Conclusion: In frame-based motion correction of dynamic PET images, it is feasible to achieve intra-frame motion compensation using time-weighted averaging of motion transformed transmission images coupled with a post-reconstruction iterative deconvolution procedure to compensate for intra-frame motion.

Purpose: In external beam radiotherapy of dynamic tumors, several errors raise due to inter- and intra-fractional motions. In order to compensate these errors, signals obtained from different surrogates are used to infer with tumor motion as real time. Therefore, a comparative assessment may be worthwhile on the effect of different surrogates in tumor motion tracking.
Methods: The performance accuracy of three internal-external surrogates entitled: external markers, diaphragm movement and lung volume was done using 4 Dimensional Extended Cardiac-Torso (4D-XCAT) phantoms. Adaptive Neuro Fuzzy Inference System (ANFIS) model was implemented to correlate the motion of surrogates with several tumors located in liver and lung, separately. Finally, the Root Mean Square Error (RMSE) of ANFIS model outputs in tumor motion prediction of different surrogates was compared as metric tool.
Results- The average value of RMSE of lung and liver tumors were 0.4 mm, 0.6 mm and 0.8 mm for external markers, lung volume and diaphragm motion, respectively.
Conclusion- Among three investigated surrogates, the best performance belonged to external markers strategy, while optimum location of these markers determined using an input selection algorithm in this method.

Purpose: In elementary studies on brainstem evoked potentials a simple stimuli like click and sinusoidal tones is used, but in recent years Auditory Neuroscience oriented to use complex stimuli. These complex stimuli (e.g. speech and music) are more capable in representation of auditory pathway functions. Previous studies in this field, mainly attend to one single vowel or consonant-vowels. Until now no study has been done which considered the encoding of multi structurally meaning full combination of consonant-vowel. In this study, we try to extract information using suitable tools from Auditory Brainstem Responses (ABR) to stimuli ‘baba’.
Methods: At the first step we used a test to find an appropriate distance between two consecutive consonant- vowels ‘ba’ which is perceived ‘baba’. For this, a psychophysical test was designed. Subjects were asked to choose a suitable distance between two ‘ba’ that the combination perceived ‘baba’. After recording evoked potentials to ‘ba’ and ‘baba’, we searched distinctive features between the signals related two stimuli. So at first, we began with comparative time-frequency analyses like correlation and coherence.
Results: Correlation analyses show that the response to ‘ba’ and the response to first syllable of ‘baba’ in the Onset and also transient parts of responses are different and the response to first and second syllable of /baba/ become similar. The results of coherence analyses show that these differences could not be represented with a linear relation merely.
Conclusion: Brainstem neural activity was different in countering with single syllable stimuli in comparison with meaningful disyllabic stimuli. These changes can be consequences of activities in anatomical top-down pathway.

Purpose: Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is an effective tool for detection and characterization of breast lesions. Qualitative assessment of suspicious breast DCE-MRI is problematic and operator dependent. The purpose of this study is to evaluate diagnostic efficacy of the representative characteristic parameters, extracted from kinetic curves of DCE-MRI, for discrimination between benign from malignant suspicious breast tumors.
Methods: Pre-operative DCE-MR images of twenty-six histopathological approved breast lesions were analyzed. The images were reviewed by an expert radiologist and the regions of interests (ROI)s were selected on the most solid part of the lesion.Semi-quantitative kinetic parameters, namely: maximum signal enhancement (SI), max 60 initial area under the curve (IAUC), time to peak (TTP), wash in rate (WIR), wash out rate (WOR) and signal enhancement ratio (SER), were calculated within each ROI. Mean values of the calculated features among benign and malignant groups were compared using student’s t-test. Finally, a classification was performed employing support vector machines (SVM) using each of the parameters and their combinations in order to investigate the efficacy of the parameters in distinguishing between benign from malignant tumors.
Results: The performance of the classification procedure employing the combination of semi-quantitative features with (p-value< 0.001) was evaluated by means of several measures, including accuracy, sensitivity, specificity, positive predictive value and negative predictive value which returned amounts of 97.5%, 96.49%,100%, 100% and 95.61% respectively.
Conclusion: In conclusion, semi-quantitative analysis of the characteristic kinetic curves of suspicious breast lesions derived from SVM classifier provides an effective lesion classification in breast DCE-MR images.

Purpose: Although in the external beam radiotherapy tumor motionis a crucial and challenging issue due to respiration  motion, temporal changes in anatomy during imaging cause considerable problems. Moreover, the Four Dimensional Computed Tomography (4DCT) imaging has been proposed to track these changes at the different breathing phases. Also at real time tumor tracking, the accuracy of motion tracking models that are necessary can be increased by constructing virtual images due to obtaining additional motion data.
Methods: In this study, the 4DCT data set of five real patients who have had lung cancer were provided by DIR-lab site in addition to deformable image registration algorithms presented in MATLAB software and DIRART software respectively to calculate 2D and 3D vector felids between two respiratory volumes. Moreover, the 2D and 3D displacement vector were calculated by optical flow based on Horn-Schunck method, these vector fields were used to generate an interpolated image at the desired time by 2D and 3D interpolation methods. Although 2D interpolation methods included nearest, cubic, linear, and B-spline, the 3D interpolation method was based on the 3D spatial interpolation. In this study, the reconstructed image at the desired time by two methods was compared with real image at the same time. Considering Roots Mean Square Error (RMSE) between actual and interpolated imageis used to measure the accuracy of interpolated images. Also the accuracy of our reconstruction images depends on the accuracy of displacement field. 
Results: All of the methods are able to generate images at the desired time with less RMSE and high correlation coefficient. While the 2D interpolation methods that include nearest, cubic, linear, and B-spline were able to generate an image with less errors, the performance of the 2D interpolation method is less efficient than other methods.
Conclusion: The behavior and capability of the algorithmsare demonstrated by synthetic image examples. Furthermore, to compare 2D and 3D optical flow based interpolation methods, the RMSE quantitative measures are calculated. Results indicate that both 2D and 3D interpolation presented methods are outperformed significantly, and the patient is kept away from re-scanning for getting new images.

Purpose: MR only treatment planning for pediatric radiation therapy is helpful to reduce the patient dose and more precise target definition. Bone segmentation and assigning a suitable bulk electron density to bone tissue is important in this technique. Bone in children under 14 years old is still developing so the mineral density is changing during these ages. The objective of this study is to assess the effect of assigning the same bulk electron density to bone tissues of the children with different ages on dose distribution.
Methods: Seven sets of skull CT images of children under 19 years old were selected. Skull bones were segmented and the CT numbers extracted, then the CT numbers converted to density. In order to compare the differences of dose distribution due to differences in bone density, the percentage depth dose was calculated by Monte Carlo simulation in inhomogeneous phantoms.
Results: The results of PDDs in photon and electron sources did not show a significant difference (<2%) between different densities beneath the bone tissue.
Conclusion: When MR only treatment planning is to be used for a child, the bulk density method is accurate enough for treatment of brain or underneath area of bone. However, if the target of radiation therapy is bone, this method may cause a little error in dose calculation especially in superficial and electron therapy, so that voxel based methods are more reliable for these treatments.

Purpose: Plans for all types of therapies for cancer need to be updated according to new achievements in science and technology. Building models of in vitro cancer cell growth may make a predictive view for physicians about the behavior of these cells in the real world. 
Methods: In this study using experimental data which acquired from cultured cells and taking photos using a digital microscope lens, we designed a Cellular Automata model of death and growth of melanoma cancer cells in the presence of different concentration of FBS and different dose of Cisplatin as a chemotherapy drug. 
Results: This model is based oncellular automata although we used a genetic algorithm for this model.This combined model casts a dynamic in model and made which is adoptive based on the alternation of the environment. In the end, we achieved up to 75% prediction accuracy about the behavior of these cells. 
Conclusion: The proposed model showed approximately good results to predict tumor growth in the presence of different dosages of chemotherapy drug and it can make a perspective of tumor growth for us.

Purpose: In this report the design concept and experimental evaluation of the performance of HeliGuide have been illustrated. 
Methods: 14C-UBT system designed for detecting Helicobacter pylori. In order to assess the capability of the system, results of 221 reference cards have been analyzed.
Results: Results of the HeliGuide system are matched with the reference. 
Conclusion: Results of the evaluation indicated that HeliGuide is adequate as a Urea Breath Test system for detecting helicobacter pylori.