• Title/Summary/Keyword: corrected data

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Dye Leakage Measurement in Time Series Flucrescein Ocular Fundus Photographs (시계열 형광안저오진에서의 조경제 루출량 측정)

  • Kwon, Kap-Hyeon;Ha, Yeong-Ho;Kim, Soo-Joong
    • Journal of Biomedical Engineering Research
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    • v.12 no.4
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    • pp.295-302
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    • 1991
  • In this paper, the inter- and intra-frame distortions in the gray levels of a series of fluorescein ocular fundus photographs are corrected. For doing this, the background images are extracted from original images using the image blurring effect by decimation, and then shading corrected images are obtained by subtracting the background images from the original images pixel by pixel. In a series of fluorescein ocular fundus photographs, after the gray scale distoriton is corrected, the intensity volumes of dye leakage are measured and represented by a graph. These data may be useful for the prediction of prognosis and the therapeutic management.

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ATMOSPHERIC CORRECTION OF LANDSAT SEA SURFACE TEMPERATURE BY USING TERRA MODIS

  • Kim, Jun-Soo;Han, Hyang-Sun;Lee, Hoon-Yol
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.864-867
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    • 2006
  • Thermal infrared images of Landsat-5 TM and Landsat-7 ETM+ sensors have been unrivalled sources of high resolution thermal remote sensing (60m for ETM+, 120m for TM) for more than two decades. Atmospheric effect that degrades the accuracy of Sea Surface Temperature (SST) measurement significantly, however, can not be corrected as the sensors have only one thermal channel. Recently, MODIS sensor onboard Terra satellite is equipped with dual-thermal channels (31 and 32) of which the difference of at-satellite brightness temperature can provide atmospheric correction with 1km resolution. In this study we corrected the atmospheric effect of Landsat SST by using MODIS data obtained almost simultaneously. As a case study, we produced the Landsat SST near the eastern and western coast of Korea. Then we have obtained Terra/MODIS image of the same area taken approximately 30 minutes later. Atmospheric correction term was calculated by the difference between the MODIS SST (Level 2) and the SST calculated from a single channel (31 of Level 1B). This term with 1km resolution was used for Landsat SST atmospheric correction. Comparison of in situ SST measurements and the corrected Landsat SSTs has shown a significant improvement in $R^2$ from 0.6229 to 0.7779. It is shown that the combination of the high resolution Landsat SST and the Terra/MODIS atmospheric correction can be a routine data production scheme for the thermal remote sensing of ocean.

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Estimation of Ocean Current Velocity near Incheon using Radarsat-1 SAR and HF-radar Data

  • Kang, Moon-Kyung;Lee, Hoon-Yol
    • Korean Journal of Remote Sensing
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    • v.23 no.5
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    • pp.421-430
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    • 2007
  • This paper presents the results of the ocean surface current velocity estimation using 6 Radarsat-1 SAR images acquired in west coastal area near Incheon. We extracted the surface velocity from SAR images based on the Doppler shift approach in which the azimuth frequency shift is related to the motion of surface target in the radar direction. The Doppler shift was measured by the difference between the Doppler centroid estimated in the range-compressed, azimuth-frequency domain and the nominal Doppler centroid used during the SAR focusing process. The extracted SAR current velocities were statistically compared with the current velocities from the high frequency(HF) radar in terms of averages, standard deviations, and root mean square errors. The problem of the unreliable nominal Doppler centroid for the estimation of the SAR current velocity was corrected by subtracting the difference of averages between SAR and HF-radar current velocities from the SAR current velocity. The corrected SAR current velocity inherits the average of HF-radar data while maintaining high-resolution nature of the original SAR data.

T1 Map-Based Radiomics for Prediction of Left Ventricular Reverse Remodeling in Patients With Nonischemic Dilated Cardiomyopathy

  • Suyon Chang;Kyunghwa Han;Yonghan Kwon;Lina Kim;Seunghyun Hwang;Hwiyoung Kim;Byoung Wook Choi
    • Korean Journal of Radiology
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    • v.24 no.5
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    • pp.395-405
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    • 2023
  • Objective: This study aimed to develop and validate models using radiomics features on a native T1 map from cardiac magnetic resonance (CMR) to predict left ventricular reverse remodeling (LVRR) in patients with nonischemic dilated cardiomyopathy (NIDCM). Materials and Methods: Data from 274 patients with NIDCM who underwent CMR imaging with T1 mapping at Severance Hospital between April 2012 and December 2018 were retrospectively reviewed. Radiomic features were extracted from the native T1 maps. LVRR was determined using echocardiography performed ≥ 180 days after the CMR. The radiomics score was generated using the least absolute shrinkage and selection operator logistic regression models. Clinical, clinical + late gadolinium enhancement (LGE), clinical + radiomics, and clinical + LGE + radiomics models were built using a logistic regression method to predict LVRR. For internal validation of the result, bootstrap validation with 1000 resampling iterations was performed, and the optimism-corrected area under the receiver operating characteristic curve (AUC) with 95% confidence interval (CI) was computed. Model performance was compared using AUC with the DeLong test and bootstrap. Results: Among 274 patients, 123 (44.9%) were classified as LVRR-positive and 151 (55.1%) as LVRR-negative. The optimism-corrected AUC of the radiomics model in internal validation with bootstrapping was 0.753 (95% CI, 0.698-0.813). The clinical + radiomics model revealed a higher optimism-corrected AUC than that of the clinical + LGE model (0.794 vs. 0.716; difference, 0.078 [99% CI, 0.003-0.151]). The clinical + LGE + radiomics model significantly improved the prediction of LVRR compared with the clinical + LGE model (optimism-corrected AUC of 0.811 vs. 0.716; difference, 0.095 [99% CI, 0.022-0.139]). Conclusion: The radiomic characteristics extracted from a non-enhanced T1 map may improve the prediction of LVRR and offer added value over traditional LGE in patients with NIDCM. Additional external validation research is required.

DTM GENERATION OF RADARSAT AND SPOT SATELLITE IMAGERY USING GROUND CONTROL POINTS EXTRACTED FROM SAR IMAGE

  • PARK DOO-YOUL;KIM JIN-KWANG;LEE HO-NAM;WON JOONG-SUN
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.667-670
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    • 2005
  • Ground control points(GCPs) can be extracted from SAR data given precise orbit for DTM generation using optic images and other SAR data. In this study, we extract GCPs from ERS SAR data and SRTM DEM. Although it is very difficult to identify GCPs in ERS SAR image, the geometry of optic image and other SAR data are able to be corrected and more precise DTM can be constructed from stereo optic images. Twenty GCPs were obtained from the ERS SAR data with precise Delft orbit information. After the correction was applied, the mean values of planimetric distance errors of the GCPs were 3.7m, 12.1 and -0.8m with standard deviations of 19.9m, 18.1, and 7.8m in geocentric X, Y, and Z coordinates, respectively. The geometries of SPOT stereo pair were corrected by 13 GCPs, and r.m.s. errors were 405m, 705m and 8.6m in northing, easting and height direction, respectively. And the geometries of RADARS AT stereo pair were corrected by 12 GCPs, and r.m.s. errors were 804m, 7.9m and 6.9m in northing, easting and height direction, respectively. DTMs, through a method of area based matching with pyramid images, were generated by SPOT stereo images and RADARS AT stereo images. Comparison between points of the obtained DTMs and points estimated from a national 1 :5,000 digital map was performed. For DTM by SPOT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. For DTM by RADARSAT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. These results met the accuracy of DTED level 2

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Tolerability and Effect of Early High-Dose Amino Acid Administration in Extremely Low Birth Weight Infants

  • Choi, Jin Wha;Kim, Jisook;Ahn, So Yoon;Chang, Yun Sil;Park, Won Soon;Sung, Se In
    • Neonatal Medicine
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    • v.25 no.4
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    • pp.153-160
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    • 2018
  • Purpose: The aim of this study is to examine the tolerability and effect of early high-dose amino acid administration in extremely low birth weight infants (ELBWIs). Methods: This retrospective cohort study included ELBWI (birth weight <1,000 g, n=142). Biochemical, nutritional, and neurodevelopmental data were compared between infants who received conventional low amino acid (LAA; 1.5 g/kg/day) and those who received high amino acid (HAA; 3 g/kg/day) within the first 48 hours after birth. Neurodevelopmental data included weight, height, and head circumference at discharge, 12 to 14 and 18 to 24 months of corrected age and the Korean Bayley Scale of Infant Development II (K-BSID-II) score at 18 to 24 months of corrected age. Results: The HAA group demonstrated higher peak plasma albumin ($3.0{\pm}0.4$ vs. $3.2{\pm}0.5$, P<0.05) and lower serum creatinine ($1.7{\pm}0.9$ vs. $1.4{\pm}0.8$, P<0.05) during the first 14 days than the LAA group. Full enteral feeding was achieved significantly earlier in infants in the HAA group than in infants in the LAA group ($46.2{\pm}23.0days$ vs. $34.3{\pm}21days$, P<0.01). There was no difference between the two groups in the z score changes in all growth indicators from birth to discharge and at 12 to 14 and 18 to 24 months of corrected age, as well as in the K-BSID-II score at 18 to 24 months of corrected age. Conclusion: Aggressive administration of amino acids during the first 2 days of life in ELBWI was well tolerated and correlated with earlier full enteral feeding, but did not improve growth and neurodevelopment.

MR-based Partial Volume Correction for $^{18}$F-PET Data Using Hoffman Brain Phantom

  • Kim, D. H.;Kim, H. J.;H. K. Jeong;H. K. Son;W. S. Kang;H. Jung;S. I. Hong;M. Yun;Lee, J. D.
    • Proceedings of the Korean Society of Medical Physics Conference
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    • 2002.09a
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    • pp.322-323
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    • 2002
  • Partial volume averaging effect of PET data influences on the accuracy of quantitative measurements of regional brain metabolism because spatial resolution of PET is limited. The purpose of this study was to evaluate the accuracy of partial volume correction carried out on $^{18}$ F-PET images using Hoffman brain phantom. $^{18}$ F-PET Hoffman phantom images were co-registered to MR slices of the same phantom. All the MR slices of the phantom were then segmented to be binary images. Each of these binary images was convolved in 2 dimensions with the spatial resolution of the PET. The original PET images were then divided by the smoothed binary images in slice-by-slice, voxel-by-voxel basis resulting in larger PET image volume in size. This enlarged partial volume corrected PET image volume was multiplied by original binary image volume to exclude extracortical region. The evaluation of partial volume corrected PET image volume was performed by region of interests (ROI) analysis applying ROIs, which were drawn on cortical regions of the original MR image slices, to corrected and original PET image volume. From the ROI analysis, range of regional mean values increases of partial volume corrected PET images was 4 to 14%, and average increase for all the ROIs was about 10% in this phantom study. Hoffman brain phantom study was useful for the objective evaluation of the partial volume correction method. This MR-based correction method would be applicable to patients in the. quantitative analysis of FDG-PET studies.

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Reproducibility Assessment of K-Means Clustering and Applications (K-평균 군집화의 재현성 평가 및 응용)

  • 허명회;이용구
    • The Korean Journal of Applied Statistics
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    • v.17 no.1
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    • pp.135-144
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    • 2004
  • We propose a reproducibility (validity) assessment procedure of K-means cluster analysis by randomly partitioning the data set into three parts, of which two subsets are used for developing clustering rules and one subset for testing consistency of clustering rules. Also, as an alternative to Rand index and corrected Rand index, we propose an entropy-based consistency measure between two clustering rules, and apply it to determination of the number of clusters in K-means clustering.

Effect of the Dose Reduction Applied Low Dose for PET/CT According to CT Attenuation Correction Method (PET/CT 저선량 적용 시 CT 감쇠보정법에 따른 피폭선량 저감효과)

  • Jung, Seung Woo;Kim, Hong Kyun;Kwon, Jae Beom;Park, Sung Wook;Kim, Myeong Jun;Sin, Yeong Man;Kim, Yeong Heon
    • The Korean Journal of Nuclear Medicine Technology
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    • v.18 no.1
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    • pp.127-133
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    • 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.

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Bias-correction of Dual Polarization Radar rainfall using Convolutional Autoencoder

  • Jung, Sungho;Le, Xuan Hien;Oh, Sungryul;Kim, Jeongyup;Lee, GiHa
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.166-166
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    • 2020
  • Recently, As the frequency of localized heavy rains increases, the use of high-resolution radar data is increasing. The produced radar rainfall has still gaps of spatial and temporal compared to gauge observation rainfall, and in many studies, various statistical techniques are performed for correct rainfall. In this study, the precipitation correction of the S-band Dual Polarization radar in use in the flood forecast was performed using the ConvAE algorithm, one of the Convolutional Neural Network. The ConvAE model was trained based on radar data sets having a 10-min temporal resolution: radar rainfall data, gauge rainfall data for 790minutes(July 2017 in Cheongju flood event). As a result of the validation of corrected radar rainfall were reduced gaps compared to gauge rainfall and the spatial correction was also performed. Therefore, it is judged that the corrected radar rainfall using ConvAE will increase the reliability of the gridded rainfall data used in various physically-based distributed hydrodynamic models.

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