• Archives of Plastic Surgery
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• v.41 no.3
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• pp.258-263
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• 2014

Background For early breast cancer patients, skin-sparing mastectomy or nipple-sparing mastectomy with sentinel lymph node biopsy has become the mainstream treatment for immediate breast reconstruction in possible cases. However, a few cases of skin necrosis caused by methylene blue dye (MBD) used for sentinel lymph node localization have been reported. Methods Immediate breast reconstruction using a silicone implant was performed on 35 breasts of 34 patients after mastectomy. For sentinel lymph node localization, 1% MBD (3 mL) was injected into the subareolar area. The operation site was inspected in the postoperative evaluation. Results Six cases of immediate breast reconstruction using implants were complicated by methylene blue dye. One case of local infection was improved by conservative treatment. In two cases, partial necrosis and wound dehiscence of the incision areas were observed; thus, debridement and closure were performed. Of the three cases of wide skin necrosis, two cases underwent removal of the dead tissue and implants, followed by primary closure. In the other case, the breast implant was salvaged using latissimus dorsi musculocutaneous flap reconstruction. Conclusions The complications were caused by MBD toxicity, which aggravated blood disturbance and skin tension after implant insertion. When planning immediate breast reconstruction using silicone implants, complications of MBD should be discussed in detail prior to surgery, and appropriate management in the event of complications is required.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.329-329
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• 2022

Accurate characterization of terrestrial precipitation variation from high spatial resolution satellite sensors is beneficial for urban hydrology and microscale agriculture modeling, as well as natural disasters (e.g., urban flooding) early warning. However, the widely-used top-down approach for precipitation retrieval from microwave satellites is limited in several hydrological and agricultural applications due to their coarse spatial resolution. In this research, we aim to apply a novel bottom-up method, the parameterized SM2RAIN, where precipitation can be estimated from soil moisture signals based on an inversion of water balance model, to generate high spatial resolution terrestrial precipitation estimates at 0.01º grid (roughly 1-km) from the C-band SAR Sentinel-1. This product was then tested against a common reanalysis-based precipitation data and a domestic rain gauge network from the Korean Meteorological Administration (KMA) over central South Korea, since a clear difference between climatic types (coasts and mainlands) and land covers (croplands and mixed forests) was reported in this area. The results showed that seasonal precipitation variability strongly affected the SM2RAIN performances, and the product derived from separated parameters (rainy and non-rainy seasons) outperformed that estimated considering the entire year. In addition, the product retrieved over the mainland mixed forest region showed slightly superior performance compared to that over the coastal cropland region, suggesting that the 6-day time resolution of S1 data is suitable for capturing the stable precipitation pattern in mainland mixed forests rather than the highly variable precipitation pattern in coastal croplands. Future studies suggest comparing this product to the traditional top-down products, as well as evaluating their integration for enhancing high spatial resolution precipitation over entire South Korea.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.497-510
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• 2022

Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.17-24
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• 2018

Grounding line of a glacier or ice shelf where ice bottom meets the ocean is sensitive to changes in the polar environment. Recent rapid changes of grounding lines have been observed especially in southwestern Antarctica due to global warming. In this study, ERS-1/2 and Sentinel-1A Synthetic Aperture Radar (SAR) image were interferometrically acquired in 1996 and 2015, respectively, to monitor the movement of the grounding line in the western part of Ronne Ice Shelf near the Antarctic peninsula. Double-Differential Interferometric SAR (DDInSAR) technique was applied to remove gravitational flow signal to detect grounding line from the interferometric phase due to the vertical displacement of the tide. The result showed that ERS-1/2 grounding lines are almost consistent with those from Rignot et al. (2011) which used the similar dataset, confirming the credibility of the data processing. The comparison of ERS-1/2 and Sentinle-1A DDInSAR images showed a grounding line retreat of $1.0{\pm}0.1km$ from 1996 to 2015. It is also proved that the grounding lines based on the 2004 MODIS Mosaic of Antarctica (MOA) images and digital elevation model searching for ice plain near coastal area (Scambos et al., 2017), is not accurate enough especially where there is a ice plain with no tidal motion.

• Korean journal of applied entomology
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• v.57 no.3
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• pp.177-183
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• 2018

This study examined the seasonal, regional distribution of mosquito vectors related with disease vectors in the Jeju. From March to November, sample were collected from 11 points in four environmentally different sites in Jeju Island. Samples were collected twice a month using a black-light trap and a BG sentinel trap. Overall, five genera and seven species types of 6,042 female mosquitos were collected. Among the collected mosquitos, 4,159 (68.8%) and 1,348 (24.4%) were Culex pipiens and Aedes albopictus, respectively, making them the dominant species. Additionally, collection using the black light trap produced 72.8 entities per trap in Jungang-dong service center in the center of the city, which was the highest value, while the lowest amount of 1.4 per trap was recovered from the airport. When the BG sentinel trap was used, the largest recovery was observed in the port, where there were 71.7 entities per trap, while the lowest amount of 28.3 entities per trap was recovered at Gealmae Eco Park. The overall number of mosquitoes collected started to increase from May, and reached the largest value of 1,156 (19.1%) in August. Trapped mosquitoes are created 364 pools of up to 50 grains per pool, by season, by environmental, and by species. When the pools were used, no flaviviral infection was observed upon real time RT-PCR.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10451-10456
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• 2015

Background: We defined melanoma distribution in a large series of Turkish patients and evaluated the prognostic parameters of melanomas. Materials and Methods: A total of 1574 patients' data was retrospectively collected at 18 centers in Turkey. Demographic characteristics were questioned and noted. Prognostic parametres were evaluated based on sentinel lymph node involvement. Results: Mean age was 56.7 (4-99) years. While 844 (53.6%) cases were male, 730 (46.4%) cases were female. One thousand four hundred forty-seven (92%) cases were invasive melanoma and 127 (8%) cases were in-situ melanoma. The most common histopathological form was the superficial spreading melanoma (SSM) which was found in 549 patients (37.9%). It was followed by nodular melanoma in 379 (26.2%), acral lentiginous melanoma (ALM) in 191 (13.2%) and lentigo maligna melanoma in 132 (9.1%), respectively. On univariate analysis, lymphovascular invasion (p<0.001), tumor thickness (p<0.001), histopathological subtype (p<0.001), Clark level (p=0.001), ulceration (p<0.001), ${\geq}6/mm^2$ mitosis (p=0.005), satellite formation (p=0.001) and gender (p=0.03) were found to be associated with sentinel lymph node positivity. Regression was associated with sentinel lymph node negativity (p=0.017). According to multivariate analysis, lymphovascular invasion and tumor thickness were significant independent predictive factors of SLN positivity. Patient age, tumor localization, precursor lesions, lymphocytic infiltration and neurotropism were not related with sentinel lymph node involvement. Conclusions: In this retrospective analysis, it was found that the prevalence of SSM is at a lower rate while the prevalence of ALM is at a higher rate when compared to western countries. According to Breslow index; most of the melanoma lesions' thickness were greater than 2 mm, corresponding Clark IV. Vascular invasion and tumor thickness are the most important factors for sentinel lymph node involvement.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.535-544
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• 2020

In synthetic aperture radar (SAR) based ship detection application, false alarms frequently occur due to various noises caused by the radar imaging process. Among them, radio frequency interference (RFI) and azimuth smearing produce substantial false alarms; the latter also yields longer length estimation of ships than the true length. These two noises are prominent at cross-polarization and relatively weak at co-polarization. However, in general, the cross-polarization data are suitable for ship detection, because the radar backscatter from background sea surface is much less in comparison with the co-polarization backscatter, i.e., higher ship-sea image contrast. In order to improve the ship detection accuracy further, the RFI and azimuth smearing need to be mitigated. In the present letter, Sentinel-1 VV- and VH-polarization intensity data are used to show a novel technique of removing these noises. In this method, median image intensities of noises and background sea surface are calculated to yield arithmetic tendency. A band-math formula is then designed to replace the intensities of noise pixels in VH-polarization with adjusted VV-polarization intensity pixels that are less affected by the noises. To verify the proposed method, the adaptive threshold method (ATM) with a sliding window was used for ship detection, and the results showed that the 74.39% of RFI false alarms are removed and 92.27% false alarms of azimuth smearing are removed.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1321-1330
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• 2023

Normalized Difference Vegetation Index (NDVI) is the most widely used remote sensing data in the agricultural field and is currently provided by most optical satellites. In particular, as high-resolution optical satellite images become available, the selection of optimal optical satellite images according to agricultural applications has become a very important issue. In this study, we aim to define the most optimal optical satellite image when monitoring NDVI in rice fields in Korea and derive the resolution-related requirements necessary for this. For this purpose, we compared and analyzed the spatial distribution and time series patterns of the Dangjin rice paddy in Korea from 2019 to 2022 using NDVI images from MOD13, Landsat-8, Sentinel-2A/B, and PlanetScope satellites, which are widely used around the world. Each data is provided with a spatial resolution of 3 m to 250 m and various periods, and the area of the spectral band used to calculate NDVI also has slight differences. As a result of the analysis, Landsat-8 showed the lowest NDVI value and had very low spatial variation. In comparison, the MOD13 NDVI image showed similar spatial distribution and time series patterns as the PlanetScope data but was affected by the area surrounding the rice field due to low spatial resolution. Sentinel-2A/B showed relatively low NDVI values due to the wide near-infrared band area, and this feature was especially noticeable in the early stages of growth. PlanetScope's NDVI provides detailed spatial variation and stable time series patterns, but considering its high purchase price, it is considered to be more useful in small field areas than in spatially uniform rice paddy. Accordingly, for rice field areas, 250 m MOD13 NDVI or 10 m Sentinel-2A/B are considered to be the most efficient, but high-resolution satellite images can be used to estimate detailed physical quantities of individual crops.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1773-1784
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• 2021

In order to minimize damage to oil spill accidents in the ocean, it is essential to collect a spilled area as soon as possible. Thus satellite-based remote sensing is a powerful source to detect oil spills in the ocean. With the recent rapid increase in the number of available satellites, it has become possible to generate a status report of marine oil spills soon after the accident. In this study, the oil spill area was calculated using various satellite images for the Symphony oil spill accident that occurred off the coast of Qingdao Port, China, on April 27, 2021. In particular, improving the accuracy of oil spill area determination was applied using high-resolution commercial satellite images with a spatial resolution of 2m. Sentinel-1, Sentinel-2, LANDSAT-8, GEO-KOMPSAT-2B (GOCI-II) and Skysat satellite images were collected from April 27 to May 13, but five images were available considering the weather conditions. The spilled oil had spread northeastward, bound for coastal region of China. This trend was confirmed in the Skysat image and also similar to the movement prediction of oil particles from the accident location. From this result, the look-alike patch observed in the north area from the Sentinel-1A (2021.05.01) image was discriminated as a false alarm. Through the survey period, the spilled oil area tends to increase linearly after the accident. This study showed that high-resolution optical satellites can be used to calculate more accurately the distribution area of spilled oil and contribute to establishing efficient response strategies for oil spill accidents.