Purpose The aim of this study was to evaluate the diagnostic image quality of low dose abdominal digital radiography processed with a new post-processing technique. Materials and Methods Abdominal radiographs from phantom pilot studies were post-processed by the novel and conventional post-processing methods of our institution; the proper dose for the subsequent patient study of 49 subjects was determined by comparing image quality of the two preceding studies. Two radiographs of each patient were taken using the conventional and derived dose protocols with the proposed post-processing method. The image details and quality were evaluated by two radiologists. Results The radiation dose for the patient study was derived to be half of the conventional method. Overall half-dose image quality with the proposed method was significantly higher than that of the conventional method (p < 0.05) with moderate inter-rater agreement (κ = 0.60, 0.47). Conclusion By applying the new post-processing technique, half-dose abdominal digital radiography can demonstrate feasible image quality compared to the full-dose images.
Woo Kyoung Jeong;Hyo-Jin Kang;Sang Hyun Choi;Mi-Suk Park;Mi Hye Yu;Bohyun Kim;Myung-Won You;Sanghyeok Lim;Young Seo Cho;Min Woo Lee;Jeong Ah Hwang;Jae Young Lee;Jung Hoon Kim;Ijin Joo;Jae Seok Bae;So Yeon Kim;Yong Eun Chung;Dong Hwan Kim;Jeong Min Lee
Korean Journal of Radiology
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v.24
no.6
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pp.482-497
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2023
Sonazoid, a second-generation ultrasound contrast agent, was introduced for the diagnosis of hepatic nodules. To clarify the issues with Sonazoid contrast-enhanced ultrasonography for the diagnosis of hepatocellular carcinoma (HCC), the Korean Society of Radiology and Korean Society of Abdominal Radiology collaborated on the guidelines. The guidelines are de novo, evidence-based, and selected using an electronic voting system for consensus. These include imaging protocols, diagnostic criteria for HCC, diagnostic value for lesions that are inconclusive on other imaging results, differentiation from non-HCC malignancies, surveillance of HCC, and treatment response after locoregional and systemic treatment for HCC.
Seul Bi Lee;Youngtaek Hong;Yeon Jin Cho;Dawun Jeong;Jina Lee;Soon Ho Yoon;Seunghyun Lee;Young Hun Choi;Jung-Eun Cheon
Korean Journal of Radiology
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v.24
no.4
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pp.294-304
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2023
Objective: We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction methods. Materials and Methods: We collected contrast-enhanced dual-energy CT of the abdomen that was obtained using various reconstruction methods, including filtered back projection, iterative reconstruction, optimum contrast, and monoenergetic images with 40, 60, and 80 keV. A deep learning based image conversion algorithm was developed to standardize the CT images using 142 CT examinations (128 for training and 14 for tuning). A separate set of 43 CT examinations from 42 patients (mean age, 10.1 years) was used as the test data. A commercial software program (MEDIP PRO v2.0.0.0, MEDICALIP Co. Ltd.) based on 2D U-NET was used to create liver segmentation masks with liver volume. The original 80 keV images were used as the ground truth. We used the paired t-test to compare the segmentation performance in the Dice similarity coefficient (DSC) and difference ratio of the liver volume relative to the ground truth volume before and after image standardization. The concordance correlation coefficient (CCC) was used to assess the agreement between the segmented liver volume and ground-truth volume. Results: The original CT images showed variable and poor segmentation performances. The standardized images achieved significantly higher DSCs for liver segmentation than the original images (DSC [original, 5.40%-91.27%] vs. [standardized, 93.16%-96.74%], all P < 0.001). The difference ratio of liver volume also decreased significantly after image conversion (original, 9.84%-91.37% vs. standardized, 1.99%-4.41%). In all protocols, CCCs improved after image conversion (original, -0.006-0.964 vs. standardized, 0.990-0.998). Conclusion: Deep learning-based CT image standardization can improve the performance of automated hepatic segmentation using CT images reconstructed using various methods. Deep learning-based CT image conversion may have the potential to improve the generalizability of the segmentation network.
Ilsang Woo;Areum Lee;Seung Chai Jung;Hyunna Lee;Namkug Kim;Se Jin Cho;Donghyun Kim;Jungbin Lee;Leonard Sunwoo;Dong-Wha Kang
Korean Journal of Radiology
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v.20
no.8
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pp.1275-1284
/
2019
Objective: To develop algorithms using convolutional neural networks (CNNs) for automatic segmentation of acute ischemic lesions on diffusion-weighted imaging (DWI) and compare them with conventional algorithms, including a thresholding-based segmentation. Materials and Methods: Between September 2005 and August 2015, 429 patients presenting with acute cerebral ischemia (training:validation:test set = 246:89:94) were retrospectively enrolled in this study, which was performed under Institutional Review Board approval. Ground truth segmentations for acute ischemic lesions on DWI were manually drawn under the consensus of two expert radiologists. CNN algorithms were developed using two-dimensional U-Net with squeeze-and-excitation blocks (U-Net) and a DenseNet with squeeze-and-excitation blocks (DenseNet) with squeeze-and-excitation operations for automatic segmentation of acute ischemic lesions on DWI. The CNN algorithms were compared with conventional algorithms based on DWI and the apparent diffusion coefficient (ADC) signal intensity. The performances of the algorithms were assessed using the Dice index with 5-fold cross-validation. The Dice indices were analyzed according to infarct volumes (< 10 mL, ≥ 10 mL), number of infarcts (≤ 5, 6-10, ≥ 11), and b-value of 1000 (b1000) signal intensities (< 50, 50-100, > 100), time intervals to DWI, and DWI protocols. Results: The CNN algorithms were significantly superior to conventional algorithms (p < 0.001). Dice indices for the CNN algorithms were 0.85 for U-Net and DenseNet and 0.86 for an ensemble of U-Net and DenseNet, while the indices were 0.58 for ADC-b1000 and b1000-ADC and 0.52 for the commercial ADC algorithm. The Dice indices for small and large lesions, respectively, were 0.81 and 0.88 with U-Net, 0.80 and 0.88 with DenseNet, and 0.82 and 0.89 with the ensemble of U-Net and DenseNet. The CNN algorithms showed significant differences in Dice indices according to infarct volumes (p < 0.001). Conclusion: The CNN algorithm for automatic segmentation of acute ischemic lesions on DWI achieved Dice indices greater than or equal to 0.85 and showed superior performance to conventional algorithms.
Journal of Korean Society of Occupational and Environmental Hygiene
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v.34
no.1
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pp.18-25
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2024
Objectives: The primary aim of this study is to create an Occupational Safety and Health (OSH) guide for high-risk maintenance tasks, specifically one designed for maintenance work (MW) in the electronics industry. Methods: The methodology involved a literature review, field investigations, and discussions. An initial draft of the OSH guide was created and then refined through consultations with experts possessing extensive experience in MW for electronic processes. Results: Specific MW tasks within electronics processing facilities identified as high-risk by the research were selected. A comprehensive OSH guide for these tasks was developed consisting of approximately 11 to 12 components and encompassing about 20-25 pages. Implementing safety and health measures before, during, and after MW is crucial for the protection of maintenance personnel. The guide is enriched with real-case scenarios of industrial accidents and occupational diseases to enhance maintenance workers' comprehension of the OSH principles. For a clearer understanding of and adherence to the safety protocols, the guide incorporates visual aids, including cartoons and photographs. Conclusions: This OSH guide is designed to ensure the protection of workers involved in maintenance activities in the electronics industry. It aligns with global standards set by the International Organization for Standardization (ISO) and Semiconductor Equipment and Material International (SEMI) to ensure a high level of safety and compliance.
Plant regeneration protocols for adventitious shoot organogenesis from apple (Malus domestica 'Fuji') leaf explants were developed in the present study. The effects of dark incubation periods in the early stages of culture, pre-treatment methods, the number of explants per culture container, the type of culture containers, and the orientation of the explants on culture media were evaluated to determine the optimal shoot regeneration conditions for 'Fuji' apple leaf explants. Light incubation of explants produced minimal response. However, dark incubation of explants for 4 weeks during the initial culture period enhanced shoot regeneration frequency. Comparing the number of explants per container, a higher percentage of shoot regeneration was obtained with nine explants per container compared with four explants per container. Pre-treatment, before culture, by dipping explants in a liquid regeneration medium containing 40 g/L of sorbitol for 2 hours produced the highest shoot formation rate, and the time of shoot formation was accelerated. The percentage of shoot regeneration and number of shoots per regenerating explant reached a maximum of 87.5% and 4.7, respectively. The regenerated shoots were elongated and rooted on a rooting medium of 1/4 MS with 0.2 mg/L IBA. The plantlets were successfully acclimatized, and the regenerated plants produced normal phenotypes.
In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.
Global warming is a key challenge subjecting animals to heat stress conditions resulting in multiple physiological alterations in tropical climate. Dietary approach seems to be the more friendly approach to curb the adverse effects of heat stress in rabbits. Some herbs have been categorized to have high potential for promotion of immune responses for amelioration of heat stress. Thus, this research aims to evaluate the potential of Mistletoe (Viscum album), Moringa (Moringa oleifera) and Phyllanthus (Phyllanthus amarus) leaf meal as herbal supplements for the alleviation of heat stress in female rabbits by measuring improvement in sex and stress hormonal responses in serum biochemistry. 80 Rabbit does were exposed to 4 dietary groups supplemented with each of Mistletoe, Moringa, Phyllanthus and a control in an 84-day trial at the summit of thermal stress in South west Nigeria. Growth indices were monitored throughout the study, blood samples were compiled at the end of the trial to assess serum biochemistry, stress and sex hormonal responses of the Does using standard protocols. The results revealed that final weight and weight gain of Does fed on Phyllanthus were significantly (p < 0.05) higher (11.46% and 14.25%, respectively) than Does on control. The herbal supplements enhance glucose, protein, albumin and globulin, reduced cholesterol, and creatinine of Does under heat stress conditions. Among the herbal treatment groups, mistletoe, moringa and phyllanthus had 12.42%, 18.39% and 16.90%, respectively, lower corticosterone than control groups which had 39.76ng/ml. Triiodothyronine of Does fed control were significantly (p < 0.05) lower than Does on Moringa oleifera and Phyllanthus amarus supplements. Estradiol and Follicle stimulating hormone of rabbit Does fed on moringa supplement were significantly (p < 0.05) higher than other treatments. In conclusion, the herbal supplements tend to mitigate the detrimental outcome of thermal stress on Does by suppressing stress hormones. Moringa oleifera and Phyllanthus amarus enhanced sex hormones while Phyllanthus amarus confered growth promoting effects on the Does.
Journal of The Korean Institute of Defense Technology
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v.5
no.3
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pp.8-17
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2023
The current weapon system is operated as a complex weapon system with various standards and protocols applied, so there is a risk of failure in smooth information exchange during combined and joint operations on the battlefield. The interoperability of weapon systems to carry out precise strikes on key targets through rapid situational judgment between weapon systems is a key element in the conduct of war. Since the Korean military went into service, there has been a need to change the configuration and improve performance of a large number of software and hardware, but there is no verification system for the impact on interoperability, and there are no related test tools and facilities. In addition, during combined and joint training, errors frequently occur during use after arbitrarily changing the detailed operation method and software of the weapon/power support system. Therefore, periodic verification of interoperability between weapon systems is necessary. To solve this problem, rather than having people schedule an evaluation period and conduct the evaluation once, AI should continuously evaluate the interoperability between weapons and power support systems 24 hours a day to advance warfighting capabilities. To solve these problems, To this end, preliminary research was conducted to improve defense interoperability capabilities by applying natural language processing techniques (①Word2Vec model, ②FastText model, ③Swivel model) (using published algorithms and source code). Based on the results of this experiment, we would like to present a methodology (automated evaluation of interoperability requirements evaluation / level measurement through natural language processing model) to implement an automated defense interoperability evaluation tool without relying on humans.
Mason D. Vialonga;Luke G. Menken;Alex Tang;John W. Yurek;Li Sun;John J. Feldman;Frank A. Liporace;Richard S. Yoon
Hip & pelvis
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v.34
no.1
/
pp.25-34
/
2022
Purpose: Mortality rates following hip fracture surgery have been well-studied. This study was conducted to examine mortality rates in asymptomatic patients presenting for treatment of acute hip fractures with concurrent positive COVID-19(+) tests compared to those with negative COVID-19(-) tests. Materials and Methods: A total of 149 consecutive patients undergoing hip fracture surgery during the COVID-19 pandemic at two academic medical centers were reviewed retrospectively. Patients were divided into two groups for comparative analysis: one group included asymptomatic patients with COVID-19+ tests versus COVID-19- tests. The primary outcome was mortality at 30-days and 90-days. Results: COVID-19+ patients had a higher mortality rate than COVID-19- patients at 30-days (26.7% vs 6.0%, P=0.005) and 90-days (41.7% vs 17.2%, P=0.046) and trended towards an increased length of hospital stay (10.1±6.2 vs 6.8±3.8 days, P=0.06). COVID-19+ patients had more pre-existing respiratory disease (46.7% vs 11.2%, P=0.0002). Results of a Cox regression analysis showed an increased risk of mortality at 30-days and 90-days from COVID-19+ status alone without an increased risk of death in patients with pre-existing chronic respiratory disease. Conclusion: Factors including time to surgery, age, preexisting comorbidities, and postoperative ambulatory status have been proven to affect mortality and complications in hip fracture patients; however, a positive COVID-19 test result adds another variable to this process. Implementation of protocols that will promote prompt orthogeriatric assessments, expedite patient transfer, limit operating room traffic, and optimize anesthesia time can preserve the standard of care in this unique patient population.
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