• Journal of applied mathematics & informatics
• /
• v.29 no.3_4
• /
• pp.697-712
• /
• 2011

We present in this paper two versions of a general correction procedure applied to a classical linear iterative method. This gives us the possibility, under certain assumptions, to obtain an extension of it to inconsistent linear least-squares problems. We prove that some well known extended projection type algorithms from image reconstruction in computerized tomography fit into one or the other of these general versions and are derived as particular cases of them. We also present some numerical experiments on two phantoms widely used in image reconstruction literature. The experiments show the importance of these extension procedures, reflected in the quality of reconstructed images.

• Nuclear Engineering and Technology
• /
• v.54 no.2
• /
• pp.479-485
• /
• 2022

At the Korea Institute of Radiological and Medical Sciences, physical human phantoms were developed to evaluate various radiation protection quantities, based on the mesh-type reference computational phantoms of the International Commission on Radiological Protection. The physical human phantoms were fabricated such that a radiophotoluminescent glass dosimeter (RPLGD) with a Tin filter, namely GD-352M, could be inserted into them. A Tin filter is used to eliminate the overestimated signals in low-energy photons below 100 keV. The measurement uncertainty of the RPLGD reader system based on GD-352M should be analyzed for obtaining reliable protection quantities before using it for practical applications. Generally, the measurement uncertainty of RPLGD systems without Tin filters is analyzed for quality assurance of radiotherapy units using a high-energy photon beam. However, in this study, the measurement uncertainty of GD-352M was analyzed for evaluating the protection quantities. The measurement uncertainty factors in the RPLGD include the reference irradiation, regression curve, reproducibility, uniformity, energy dependence, and angular dependence, as described by the International Organization for Standardization (ISO). These factors were calculated using the Guide to the Expression of Uncertainty in Measurement method, applying ISO/ASTM standards 51261(2013), 51707(2015), and SS-ISO 22127(2019). The measurement uncertainties of the RPLGD reader system with a coverage factor of k = 2 were calculated to be 9.26% from 0.005 to 1 Gy and 8.16% from 1 to 10 Gy. A blind test was conducted to validate the RPLGD reader system, which demonstrated that the readout doses included blind doses of 0.1, 1, 2, and 5 Gy. Overall, the E_n values were considered satisfactory.

• Nuclear Engineering and Technology
• /
• v.55 no.11
• /
• pp.4019-4025
• /
• 2023

Recently, a new monkey computational phantom, called Visible Monkey, was developed for non-ionizing radiation studies in animal research. In this study, we extended its applications to ionizing radiation studies by implementing the voxel model of the Visible Monkey into three general-purpose Monte Carlo (MC) codes: MCNP6, PHITS, and Geant4. The implementation work for MCNP and PHITS was conducted using the LATTICE, UNIVERSE, and FILL cards. The G4VNestedParameterisation class was used for Geant4. Then, organ dose coefficients (DCs) for idealized photon beams in the antero-posterior direction were calculated using the three codes and compared, showing excellent agreement (differences <3%). Additionally, organ DCs in other directions (postero-anterior, left-lateral, and right-lateral) were calculated and compared with those of the newborn and 1-year-old reference phantoms. Significant differences were observed (e.g., the stomach DC of the monkey was 5-fold greater than that of the 1-year-old phantom at 0.03 MeV) while the differences tended to decrease with increasing energy (mostly <20% at 10 MeV). The results of this study allows conducting MC simulations using the Visible Monkey to estimate organ-level doses, which should be valuable to support/improve monkey experiments involving ionizing radiation exposures.

• Progress in Medical Physics
• /
• v.26 no.1
• /
• pp.52-58
• /
• 2015

The automated dental cavity detection program for a new concept intra-oral dental x-ray imaging device, an auxiliary diagnosis system, which is able to assist a dentist to identify dental caries in an early stage and to make an accurate diagnosis, was to be developed. The primary theory of the automatic dental cavity detection program is divided into two algorithms; one is an image segmentation skill to discriminate between a dental cavity and a normal tooth and the other is a computational method to analyze feature of an tooth image and take an advantage of it for detection of dental cavities. In the present study, it is, first, evaluated how accurately the DRLSE (Direct Regularized Level Set Evolution) method extracts demarcation surrounding the dental cavity. In order to evaluate the ability of the developed algorithm to automatically detect dental cavities, 7 tooth phantoms from incisor to molar were fabricated which contained a various form of cavities. Then, dental cavities in the tooth phantom images were analyzed with the developed algorithm. Except for two cavities whose contours were identified partially, the contours of 12 cavities were correctly discriminated by the automated dental caries detection program, which, consequently, proved the practical feasibility of the automatic dental lesion detection algorithm. However, an efficient and enhanced algorithm is required for its application to the actual dental diagnosis since shapes or conditions of the dental caries are different between individuals and complicated. In the future, the automatic dental cavity detection system will be improved adding pattern recognition or machine learning based algorithm which can deal with information of tooth status.

• Journal of Radiation Protection and Research
• /
• v.27 no.3
• /
• pp.155-164
• /
• 2002

Methodology to evaluate the effective doses to adults undergoing various diagnostic x-ray examinations were established by Monte Carlo simulation of the x-ray examinations. Anthropomorphic mathematical phantoms, the MIRD5 male phantom and the ORNL female phantom, were used as the target body and x-ray spectra were produced by the x-ray spectrum generation code SPEC78. The computational procedure was validated by comparing the resulting doses to the results of NRPB studies for the same diagnostic procedures. The effective doses as well as the organ doses due to chest, abdomen, head and spine examinations were calculated for x-rays incident from AP, PA, LLAT and RLAT directions. For instance, the effective doses from the most common procedures, chest PA and abdomen AP, were 0.029 mSv and 0.44 mSv, respectively. The fact that the effective dose from PA chest x-ray is far lower than the traditional value of 0.3 mSv(or 30 mrem), which results partly from the advances of technology in diagnostic radiology and partly from the differences in the dose concept employed, emphasizes necessities of intensive assessment of the patient doses in wide ranges of medical exposures. The methodology and tools established in this study can easily be applied to dose assessments for other radiology procedures; dose from CT examinations, dose to the fetus due to examinations of pregnant women, dose from pediatric radiology.

• Journal of Radiation Protection and Research
• /
• v.41 no.4
• /
• pp.389-394
• /
• 2016

Background: Tetrahedral-mesh geometries can be used in the MCNP code, but the MCNP code accepts only the geometry in the Abaqus input file format; hence, the existing tetrahedral-mesh models first need to be converted to the Abacus input file format to be used in the MCNP code. In the present study, we developed a simple but useful computer program, TET2MCNP, for converting TetGen-generated tetrahedral-mesh models to the Abacus input file format. Materials and Methods: TET2MCNP is written in C++ and contains two components: one for converting a TetGen output file to the Abacus input file and the other for the reverse conversion process. The TET2MCP program also produces an MCNP input file. Further, the program provides some MCNP-specific functions: the maximum number of elements (i.e., tetrahedrons) per part can be limited, and the material density of each element can be transferred to the MCNP input file. Results and Discussion: To test the developed program, two tetrahedral-mesh models were generated using TetGen and converted to the Abaqus input file format using TET2MCNP. Subsequently, the converted files were used in the MCNP code to calculate the object- and organ-averaged absorbed dose in the sphere and phantom, respectively. The results show that the converted models provide, within statistical uncertainties, identical dose values to those obtained using the PHITS code, which uses the original tetrahedral-mesh models produced by the TetGen program. The results show that the developed program can successfully convert TetGen tetrahedral-mesh models to Abacus input files. Conclusion: In the present study, we have developed a computer program, TET2MCNP, which can be used to convert TetGen-generated tetrahedral-mesh models to the Abaqus input file format for use in the MCNP code. We believe this program will be used by many MCNP users for implementing complex tetrahedral-mesh models, including computational human phantoms, in the MCNP code.

• Progress in Medical Physics
• /
• v.26 no.4
• /
• pp.258-266
• /
• 2015

The modern radiotherapy technique which delivers a large amount of dose to patients asks to confirm the positions of patients or tumors more accurately by using X-ray projection images of high-definition. However, a rapid increase in patient's exposure and image information for CT image acquisition may be additional burden on the patient. In this study, by introducing structural similarity (SSIM) index that can effectively extract the structural information of the image, we analyze the differences between daily acquired x-ray images of a patient to verify the accuracy of patient positioning. First, for simulating a moving target, the spherical computational phantoms changing the sizes and positions were created to acquire projected images. Differences between the images were automatically detected and analyzed by extracting their SSIM values. In addition, as a clinical test, differences between daily acquired x-ray images of a patient for 12 days were detected in the same way. As a result, we confirmed that the SSIM index was changed in the range of 0.85~1 (0.006~1 when a region of interest (ROI) was applied) as the sizes or positions of the phantom changed. The SSIM was more sensitive to the change of the phantom when the ROI was limited to the phantom itself. In the clinical test, the daily change of patient positions was 0.799~0.853 in SSIM values, those well described differences among images. Therefore, we expect that SSIM index can provide an objective and quantitative technique to verify the patient position using simple x-ray images, instead of time and cost intensive three-dimensional x-ray images.