• The Korean Journal of Nuclear Medicine Technology
• /
• v.18 no.1
• /
• pp.127-133
• /
• 2014

Purpose: Low dose of PET/CT is important because of Patient's X-ray exposure. The aim of this study was to evaluate the effectiveness of low-dose PET/ CT image through the CTAC and QAC of patient study and phantom study. Materials and Methods: We used the discovery 710 PET/CT (GE). We used the NEMA IEC body phantom for evaluating the PET data corrected by ultra-low dose CT attenuation correction method and NU2-94 phantom for uniformity. After injection of 70.78 MBq and 22.2 MBq of 18 F-FDG were done to each of phantom, PET/CT scans were obtained. PET data were reconstructed by using of CTAC of which dose was for the diagnosis CT and Q. AC of which was only for attenuation correction. Quantitative analysis was performed by use of horizontal profile and vertical profile. Reference data which were corrected by CTAC were compared to PET data which was corrected by the ultra-low dose. The relative error was assessed. Patients with over weighted and normal weight also underwent a PET/CT scans according to low dose protocol and standard dose protocol. Relative error and signal to noise ratio of SUV were analyzed. Results: In the results of phantom test, phantom PET data were corrected by CTAC and Q.AC and they were compared each other. The relative error of Q.AC profile was been calculated, and it was shown in graph. In patient studies, PET data for overweight patient and normal weight patient were reconstructed by CTAC and Q.AC under routine dose and ultra-low dose. When routine dose was used, the relative error was small. When high dose was used, the result of overweight patient was effectively corrected by Q.AC. Conclusion: In phantom study, CTAC method with 80 kVp and 10 mA was resulted in bead hardening artifact. PET data corrected by ultra- low dose CTAC was not quantified, but those by the same dose were quantified properly. In patients' cases, PET data of over weighted patient could be quantified by Q.AC method. Its relative difference was not significant. Q.AC method was proper attenuation correction method when ultra-low dose was used. As a result, it is expected that Q.AC is a good method in order to reduce patient's exposure dose.

• Investigative Magnetic Resonance Imaging
• /
• v.2 no.1
• /
• pp.113-119
• /
• 1998

Purpose : Because adenocarcinomas of the uterine cervix have lower 5-year survival rate than squamous cell carcinomas due to early lymph node metastasis and local extension, scrutiny of lymph node metastasis and local extension by radiologic examination is necessary in case of clinically diagnosed or suspected adenocarcinomas. The purpose of this study is to evaluate whether there are specific findings of these tumors, compared with squamous cell carcinomas, through the analysis of magnetic resonance (MR) imaging findings. Materials and Methods : Of 21 pathologically proven cervical adenocarcinomas, MR imaging findings of 18 tumors (histologic staging : two Ib, four IIa, two IIb, one IIIa, and one IIIb) were retrospectively analyzed and compared with those of 40 wquamous cell carcinoma in consecutive patients as a control group. T1-wetighted and fast spin echo T2-weighted images were obtained on the axial and sagittal planes, using a 1.5-T MR scanner. The largest diameter, location, signal intensity and degree of contrast enhancement contour, shape and longitudinal extent of the tumor and associated findings on MR image were analyzed. Results : The largest diameters of cervical adenocarcinomas ranged from 0.8 to 4.1 cm(mean, 2.2 cm). Of 18 adenocarcinomas, nine were of endocervical type. All adenocarcinomas were isointense to surrounding cervical stroma on T1-weighted images and hyperintense(homogeneous in ten, inhomogeneous in eight) on fast spin echo T2-weighted images. Adenocarcinomas enhanced on contrast study in all patients (homogeneous in six, inhomogeneous in 12 with hyperintese enhnacing rim in two). Eight adenocarcinomas had smooth contours and ten had irregular ones. The shape of adenocarcinoma was irregular in eight patients, barrel shape in six, papillary/polypod in three, and nodular in one. All adenocarcinomas involved lower half of the uterine cervix and six tumors extended up to the upper half. Pelvic lymph nodes of more than 1.5cm in diameter in two adenocarcinomas pateints and no detectable small pelvic lymph nodes on MR imaging in one patient were pathologically positive. Hydrometra was associated in two adenocarcinomas patients, and hematometra in one patient. Compared with squamous cell carcinomas, more frequent MR findings of endocervical type and barrel shape in cervical adenocarcinomas were statistically significant. Conclusion : Cervical adenocarcinomas had more frequent MR findings of endocervical type and barrel shape, compared with wquamous cell carcinomas. Adenocarcinoma of the uterine cervix may be suspected on MR imaging, when a cervical carcinoma is of barrel shape along the endocervical canal and tends to involve lymth nodes in earlier stages.

• Geophysics and Geophysical Exploration
• /
• v.6 no.3
• /
• pp.126-133
• /
• 2003

High-resolution shallow marine seismic surveys have been carried out for the resources exploration, engineering applications and Quaternary mapping. To improve the resolution of subsurface structure image, multichannel digital technique has been applied. The quality of the image depends on the vertical and horizontal resolution and signal to noise (S/N) ratio which are associated with the data acquisition parameters such as sample interval, common midpoint (CMP) interval and CMP fold. To understand the effect of the acquisition parameters, a test survey was carried out off Yeosu and the acquired data were analyzed. A 30 $in^3$ small air gun was used as a seismic source and 8 channel streamer cable with a 5 m group interval was used as a receiver. The data were digitally recorded with a shot interval of 2 s and sample interval of 0.1 ms. The acquired data were resampled with various sample intervals, CMP intervals and CMP folds. The resampled data were processed, plotted as seismic sections and compared each other. The analysis results show that thin bed structure with ${\~}1m$ thickness and ${\~}6^{\circ}$ slope can be imaged with good resolution and continuity and low noise using the acquisition parameters with a sample interval shorter than 0.2 ms, CMP interval shorter than 2.5 m and CMP fold more than 4. Because seismic resolution is associated with the acquisition parameters, the quality of the subsurface structure can be imaged successfully using suitable and optimum acquisition parameters.

• Tuberculosis and Respiratory Diseases
• /
• v.42 no.6
• /
• pp.862-870
• /
• 1995

Background: Oxygen free radicals have generally been considered as cytotoxic agents. On the other hand, recent results suggest that small nontoxic amounts of these radicals may act a role in intracellular signal transduction pathway and many efforts to reveal the role of these radicals as secondary messengers have been made. It is evident that the oxygen radicals are released by various cell types in response to extracellular stimuli including LPS, TNF, IL-1 and phorbol esters, all of which translocate the transcription factor $NF{\kappa}B$ from cytoplasm to nucleus by releasing an inhibitory protein subunit, $I{\kappa}B$. Activation of $NF{\kappa}B$ is mimicked by exposure to mild oxidant stress, and inhibited by agents that remove oxygen radicals. It means the cytoplasmic form of the inducible tanscription factor $NF{\kappa}B$ might provide a physiologically important target for oxygen radicals. At the same time, it is well known that LPS induces the release of oxygen radicals in neutrophil with the activation of $NF{\kappa}B$. From above facts, we can assume the expression of IL-8 and IL-$1{\beta}$ gene by LPS stimulation may occur through the activation of $NF{\kappa}B$, which is mediated through the release of $I{\kappa}B$ by increasing amounts of oxygen radicals. But definitive evidence is lacking about the role of oxygen free radicals in the expression of IL-8 and IL-$1{\beta}$ gene in mononuclear phagocytic cells. We conducted a study to determine whether oxygen radicals act a role in the expression of IL-8 and IL-$1{\beta}$ gene in mononuclear phagocytic cells. Method: Human peripheral blood monocytes were isolated from healthy volunteers. Time and dose relationship of $H_2O_2$-induced IL-8 and IL-$1{\beta}$ mRNA expression was observed by Northern blot analysis. To evaluate the role of oxygen radicals in the expression of IL-8 and IL-$1{\beta}$ mRNA by LPS stimulation, pretreatment of various antioxiants including PDTC, TMTU, NAC, ME, Desferrioxamine were done and Northern blot analysis for IL-8 and IL-$1{\beta}$ mRNA was performed. Results: In PBMC, dose and time dependent expression of IL-8 and IL-$1{\beta}$ mRNA by exogenous $H_2O_2$ was not observed. But various antioxidants suppressed the expression of LPS-induced IL-8 and IL-$1{\beta}$ mRNA expression of PBMC and the suppressive activity was most prominant when the pretreatment was done with TMTU. Conclusion: Oxygen free radical may have some role in the expression of IL-8 and IL-$1{\beta}$ mRNA of PBMC but that radical might not be $H_2O_2$.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.1-25
• /
• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.