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JournalISSN: 1735-160X

Iranian Journal of Medical Physics 

About: Iranian Journal of Medical Physics is an academic journal. The journal publishes majorly in the area(s): Imaging phantom & Dosimetry. It has an ISSN identifier of 1735-160X. Over the lifetime, 410 publication(s) have been published receiving 1218 citation(s).


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Journal ArticleDOI
TL;DR: The results indicate that the proposed combinatorial model produces optimum and efficacious parameters in comparison to other parameters and can improve the capability and power of globalizing the artificial neural network.
Abstract: Introduction This study is an effort to diagnose breast cancer by processing the quantitative and qualitative information obtained from medical infrared imaging. The medical infrared imaging is free from any harmful radiation and it is one of the best advantages of the proposed method. By analyzing this information, the best diagnostic parameters among the available parameters are selected and its sensitivity and precision in cancer diagnosis is improved by utilizing genetic algorithm and artificial neural network. Materials and Methods In this research, the necessary information is obtained from thermal imaging of 200 people, and 8 diagnostic parameters are extracted from these images by the research team. Then these 8 parameters are used as input of our proposed combinatorial model which is formed using artificial neural network and genetic algorithm. Results Our results have revealed that comparison of the breast areas; thermal pattern and kurtosis are the most important parameters in breast cancer diagnosis from proposed medical infrared imaging. The proposed combinatorial model with a 50% sensitivity, 75% specificity and, 70% accuracy shows good precision in cancer diagnosis. Conclusion The main goal of this article is to describe the capability of infrared imaging in preliminary diagnosis of breast cancer. This method is beneficial to patients with and without symptoms. The results indicate that the proposed combinatorial model produces optimum and efficacious parameters in comparison to other parameters and can improve the capability and power of globalizing the artificial neural network. This will help physicians in more accurate diagnosis of this type of cancer.

31 citations

Journal ArticleDOI
TL;DR: It was showed that increasing J/Φ, as a measure of beam directionality, leads to improvement of beam performance and survival of healthy tissues surrounding the tumor, and the proposed system based on D-T neutron source, which is suitable for in-hospital installations, satisfies all in-air parameters.
Abstract: Introduction BNCT is an effective method to destroy brain tumoral cells while sparing the healthy tissues. The recommended flux for epithermal neutrons is 109 n/cm2s, which has the most effectiveness on deep-seated tumors. In this paper, it is indicated that using D-T neutron source and optimizing of Beam Shaping Assembly (BSA) leads to treating brain tumors in a reasonable time where all IAEA recommended criteria are met. Materials and Methods The proposed BSA based on a D-T neutron generator consists of a neutron multiplier system, moderators, reflector, and collimator. The simulated Snyder head phantom is used to evaluate dose profiles in tissues due to the irradiation of designed beam. Monte Carlo Code, MCNP-4C, was used in order to perform these calculations. Results The neutron beam associated with the designed and optimized BSA has an adequate epithermal flux at the beam port and neutron and gamma contaminations are removed as much as possible. Moreover, it was showed that increasing J/Φ, as a measure of beam directionality, leads to improvement of beam performance and survival of healthy tissues surrounding the tumor. Conclusion According to the simulation results, the proposed system based on D-T neutron source, which is suitable for in-hospital installations, satisfies all in-air parameters. Moreover, depth-dose curves investigate proper performance of designed beam in tissues. The results are comparable with the performances of other facilities.

17 citations

Journal ArticleDOI
TL;DR: The results of this study showed that old X-ray equipments with poor or no maintenance are probably the main sources of reducing radiographic image quality and increasing patient radiation dose.
Abstract: Introduction In radiography, dose and image quality are dependent on radiographic parameters. The problem is caused from incorrect use of radiography equipment and from the radiation exposure to patients much more than required. Therefore, the aim of this study was to implement a quality-control program to detect changes in exposure parameters, which may affect diagnosis or patient radiation dose. Materials and Methods This cross-sectional study was performed on seven stationary X-ray units in sixhospitals of Lorestan province. The measurements were performed, using a factory-calibrated Barracuda dosimeter (model: SE-43137). Results According to the results, the highest output was obtained in A Hospital (M1 device), ranging from 107×10-3 to 147×10-3 mGy/mAs. The evaluation of tube voltage accuracy showed a deviation from the standard value, which ranged between 0.81% (M1 device) and 17.94% (M2 device) at A Hospital. The deviation ranges at other hospitals were as follows: 0.30-27.52% in B Hospital (the highest in this study), 8.11-20.34% in C Hospital, 1.68-2.58% in D Hospital, 0.90-2.42% in E Hospital and 0.10-1.63% in F Hospital. The evaluation of exposure time accuracy showed that E, C, D and A (M2 device) hospitals complied with the requirements (allowing a deviation of ±5%), whereas A (M1 device), F and B hospitals exceeded the permitted limit. Conclusion The results of this study showed that old X-ray equipments with poor or no maintenance are probably the main sources of reducing radiographic image quality and increasing patient radiation dose.

14 citations

Journal ArticleDOI
TL;DR: A hierarchical classification method for breast cancer detection is developed by including two Adaptive Boosting classifiers, the first classifier is devoted to separate normal and tumorous cases and the second layer is designed to detect tumor type.
Abstract: Introduction Breast cancer is the second cause of mortality among women. Early detection of it can enhance the chance of survival. Screening systems such as mammography cannot perfectly differentiate between patients and healthy individuals. Computer-aided diagnosis can help physicians make a more accurate diagnosis. Materials and Methods Regarding the importance of separating normal and abnormal cases in screening systems, a hierarchical classification system is defined in this paper. The proposed system is including two Adaptive Boosting (AdaBoost) classifiers, the first classifier separates the candidate images into two groups of normal and abnormal. The second classifier is applied on the abnormal group of the previous stage and divides them into benign and malignant categories. The proposed algorithm is evaluated by applying it on publicly available Mammographic Image Analysis Society (MIAS) dataset. 288 images of the database are used, including 208 normal and 80 abnormal images. 47 images of the abnormal images showed benign lesion and 33 of them had malignant lesion. Results Applying the proposed algorithm on MIAS database indicates its advantage compared to previous methods. A major improvement occurred in the first classification stage. Specificity, sensitivity, and accuracy of the first classifier are obtained as 100%, 95.83%, and 97.91%, respectively. These values are calculated as 75% in the second stage Conclusion A hierarchical classification method for breast cancer detection is developed in this paper. Regarding the importance of separating normal and abnormal cases in screening systems, the first classifier is devoted to separate normal and tumorous cases. Experimental results on available database shown that the performance of this step is adequately high (100% specificity). The second layer is designed to detect tumor type. The accuracy in the second layer is obtained 75%.

14 citations

Journal ArticleDOI
TL;DR: This phantom could be used with a range of radionuclide doses in simulation situations such as cold, hot, and background uptakes for the assessment of detection characteristics when a new similar clinical SPECT procedure is being simulated.
Abstract: Introduction Quality control is an important phenomenon in nuclear medicine imaging. A Jaszczak SPECT Phantom provides consistent performance information for any SPECT or PET system. This article describes the simulation of a Jaszczak phantom and creating an executable phantom file for comparing assessment of SPECT cameras using SIMIND Monte Carlo simulation program which is well-established for SPECT. Materials and Methods The simulation was based on a Deluxe model of Jaszczak Phantom with defined geometry. Quality control tests were provided together with initial imaging example and suggested use for the assessment of parameters such as spatial resolution, limits of lesion detection, and contrast comparing with a Siemens E.Cam SPECT system. Results The phantom simulation was verified by matching tomographic spatial resolution, image contrast, and also uniformity compared with the experiment SPECT of the phantom from filtered backprojection reconstructed images of the spheres and rods. The calculated contrasts of the rods were 0.774, 0.627, 0.575, 0.372, 0.191, and 0.132 for an experiment with the rods diameters of 31.8, 25.4, 19.1, 15.9, 12.7, and 9.5 mm, respectively. The calculated contrasts of simulated rods were 0.661, 0.527, 0.487, 0.400, 0.23, and 0.2 for cold rods and also 0.92, 0.91, 0.88, 0.81, 0.76, and 0.56 for hot rods. Reconstructed spatial tomographic resolution of both experiment and simulated SPECTs of the phantom obtained about 9.5 mm. An executable phantom file and an input phantom file were created for the SIMIND Monte Carlo program. Conclusion This phantom may be used for simulated SPECT systems and would be ideal for verification of the simulated systems with real ones by comparing the results of quality control and image evaluation. It is also envisaged that this phantom could be used with a range of radionuclide doses in simulation situations such as cold, hot, and background uptakes for the assessment of detection characteristics when a new similar clinical SPECT procedure is being simulated.

14 citations

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Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
20219
202055
201956
201870
201734
201632