• Smart Media Journal
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• v.13 no.10
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• pp.28-34
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• 2024

Alzheimer's disease is a form of dementia that can be managed by identifying the disease in its initial phases. In recent times, numerous computer-aided diagnostic techniques utilizing magnetic resonance imaging (MRI) have demonstrated promising outcomes in the categorization of Alzheimer's disease (AD). The OASIS MRI dataset was utilized which has 80,000 brain MRI images. It is suggested to resample this dataset as it is highly imbalanced and posed a challenge in preventing bias toward majority class while employing the convolution neural network (CNN) model for classification. This paper examines and extracts patterns and features of 461 patients taken from the OASIS dataset. The research has aimed at utilizing the Base Model of EfficientNetV2B0 with custom classification layers, and simplified custom CNN model, also exploring Multi-class classification across four distinct classes: Non-Demented, Very Mild Demented, Mild Demented, Moderate Demented in addition to binary classification as Non-Demented and treating other classes as demented. Furthermore, different dataset sizes were experimented with 5,000 and 20,000 for each class to be discussed in this paper. The experiment results indicate that EfficientNetV2B0 achieved the accuracy of 98% in binary classification, 99% in multiclass. Whereas custom sequential CNN model in multiclass classification presents the accuracy of 96% for 20,000 dataset size and 98% for 80,000 dataset size.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.182-189
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• 2023

CT is a medical device that acquires medical images based on Attenuation coefficient of human organs related to X-rays. In addition, using this theory, it can acquire sagittal and coronal planes and 3D images of the human body. Then, CT is essential device for universal diagnostic test. But Exposure of CT scan is so high that it is regulated and managed with special medical equipment. As the special medical equipment, CT must implement quality control. In detail of quality control, Spatial resolution of existing phantom imaging tests, Contrast resolution and clinical image evaluation are qualitative tests. These tests are not objective, so the reliability of the CT undermine trust. Therefore, by applying an artificial intelligence classification model, we wanted to confirm the possibility of quantitative evaluation of the qualitative evaluation part of the phantom test. We used intelligence classification models (VGG19, DenseNet201, EfficientNet B2, inception_resnet_v2, ResNet50V2, and Xception). And the fine-tuning process used for learning was additionally performed. As a result, in all classification models, the accuracy of spatial resolution was 0.9562 or higher, the precision was 0.9535, the recall was 1, the loss value was 0.1774, and the learning time was from a maximum of 14 minutes to a minimum of 8 minutes and 10 seconds. Through the experimental results, it was concluded that the artificial intelligence model can be applied to CT implements quality control in spatial resolution and contrast resolution.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1062-1070
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• 2022

In the present communication, pure and stable α-Bismuth Oxide (Bi₂O₃) nanoparticles (NPs) were synthesized by low temperature solution combustion method using urea as a fuel and calcined at 500℃. The synthesized sample was characterized by using powder X-ray Diffraction (PXRD), Scanning Electron Microscopy (SEM), Energy dispersive X-ray analysis (EDAX), Transmission Electron Microscopy (TEM), Fourier Transform Infrared Spectroscopy (FTIR) and UV-Visible absorption spectroscopy. The PXRD pattern confirms the formation of mono-clinic, stable and low temperature phase α-Bi₂O₃. The direct optical energy band gap was estimated by using Wood and Tauc's relation which was found to be 2.81 eV. The characterized sample was studied for X-ray/gamma ray shielding properties in the energy range 0.081-1.332 MeV using NaI (Tl) detector and multi channel analyzer (MCA). The measured shielding parameters agrees well with the theory, whereas, slight deviation up to 20% is observed below 356 keV. This deviation is mainly due to the influence of atomic size of the target medium. Furthermore an accurate theory is necessary to explain the interaction of X-ray/gamma ray with the NPs.The present work opens new window to use this facile, economical, efficient, low temperature method to synthesize nanomaterials for X-ray/gamma ray shielding purpose.

• Nuclear Engineering and Technology
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• v.47 no.3
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• pp.380-387
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• 2015

A lead slowing-down spectrometer (LSDS) system is a promising nondestructive assay technique that enables a quantitative measurement of the isotopic contents of major fissile isotopes in spent nuclear fuel and its pyroprocessing counterparts, such as $^{235}U$, $^{239}Pu$, $^{241}Pu$, and, potentially, minor actinides. The LSDS system currently under development at the Korea Atomic Energy Research Institute (Daejeon, Korea) is planned to utilize a high-flux ($>10^{12}n/cm^2{\cdot}s$) neutron source comprised of a high-energy (30 MeV)/high-current (~2 A) electron beam and a heavy metal target, which results in a very intense and complex radiation field for the facility, thus demanding structural shielding to guarantee the safety. Optimization of the structural shielding design was conducted using MCNPX for neutron dose rate evaluation of several representative hypothetical designs. In order to satisfy the construction cost and neutron attenuation capability of the facility, while simultaneously achieving the aimed dose rate limit (< $0.06{\mu}Sv/h$), a few shielding materials [high-density polyethylene (HDPE)eBorax, $B_4C$, and $Li_2CO_3$] were considered for the main neutron absorber layer, which is encapsulated within the double-sided concrete wall. The MCNP simulation indicated that HDPE-Borax is the most efficient among the aforementioned candidate materials, and the combined thickness of the shielding layers should exceed 100 cm to satisfy the dose limit on the outside surface of the shielding wall of the facility when limiting the thickness of the HDPE-Borax intermediate layer to below 5 cm. However, the shielding wall must include the instrumentation and installation holes for the LSDS system. The radiation leakage through the holes was substantially mitigated by adopting a zigzag-shape with concrete covers on both sides. The suggested optimized design of the shielding structure satisfies the dose rate limit and can be used for the construction of a facility in the near future.