• Title/Summary/Keyword: Automated image analysis

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Development of Automatized Quantitative Analysis Method in CT Images Evaluation using AAPM Phantom (AAPM Phantom을 이용한 CT 영상 평가 시 자동화된 정량적 분석 방법 개발)

  • Noh, Sung Sun;Um, Hyo Sik;Kim, Ho Chul
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.12
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    • pp.163-173
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    • 2014
  • When evaluating the spatial resolution images and evaluation of low contrast resolution using CT standard phantom, and might present a automated quantitative evaluation method for minimizing errors by subjective judgment of the evaluator be, and try to evaluate the usefulness. 120kVp and 250mAs, 10mm collimation, SFOV(scan field of view) of 25cm or more than, exposure conditions DFOV(display field of view) of 25cm, and were evaluated the 24 passing images and 20 failing images taken using a standard reconstruction algorithm by using the Nuclear Associates, Inc. AAPM CT Performance Phantom(Model 76-410). Quantitative evaluation of low contrast resolution and spatial resolution was using an evaluation program that was self-developed using the company Mathwork Matlab(Ver. 7.6. (R2008a)) software. In this study, the results were evaluated using the evaluation program that was self-developed in the evaluation of images using CT standard phantom, it was possible to evaluate an objective numerical qualitative evaluation item. First, if the contrast resolution, if EI is 0.50, 0.51, 0.52, 0.53, as a result of evaluating quantitatively the results were evaluated qualitatively match. Second, if CNR is -0.0018~-0.0010, as a result of evaluating quantitatively the results were evaluated qualitatively match. Third, if the spatial resolution, as a result of using a image segmentation technique, and automatically extract the contour boundary of the hole, as a result of evaluating quantitatively the results were evaluated qualitatively match.

Using Numerical Maps to Select Solar Panel Installation Sites no Expressway Slopes (수치지도를 이용한 고속국도 주변 태양광 패널 설치 대상지 선정)

  • Jung, Jaehoon;Kim, Byungil
    • Korean Journal of Construction Engineering and Management
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    • v.17 no.5
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    • pp.71-77
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    • 2016
  • Solar energy is a viable source to replace fossil fuels. However, challenges associated with site selection for solar panel installation inhibit the uptake of solar energy systems. Expressway slopes offer a potentially attractive alternative for solar panel installation for the following reasons: expressway slopes are vacant public sites, they are abundant (about 4,193km in South Korea), and they are linear in nature. Traditoinally when selecting sites for solar systems conventional surveying methods are employed. Unfortunately, these methods can be dangerous, time consuming, and labor intensive. To overcome these limitations of conventional site selection methodologies, we propose an automated approach using numerical maps. First, contour and expressway polylines are extracted separately from numeric maps. The extracted contour lines are then converted into a digital terrain model; this is used to calculate aspect and slope information. Next, the extracted expressway lines are projected onto a binary image and refined to recover the disconnections, and then applied to create a buffer zone to narrow the search space. Finally, all data sets are overlaid to identify candidate sites for solar panel systems and are visually verified through comparisons with aerial photos.

Fully Automated Generation of Cloud-free Imagery Using Landsat-8 (Landsat-8을 이용한 자동화된 구름 제거 영상 생성)

  • Kim, Byeong Hee;Kim, Yong;Han, You Kyung;Choi, Won Seok;Kim, Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.2
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    • pp.133-142
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    • 2014
  • Landsat is one of the popular satellites for observing land surface that is used in various areas including monitoring, detecting and classifying changes in land surface. However, shades, which cloud itself and its shadow, interrupted often clear observation and analysis of ground surface. For this reason, the process of removing shades and restoring original ground surfaces are critical for geospatial users. This study is planned to recommend a methodology for more accurate and clear images of Landsat-8 sensor, which provided two additional bands of costal/aerosol and cirrus. In fact, those bands are known as functioned effectively in detecting and restoring shades. Otsu's thresholding technique to detect clouds, we replaced those detective shades by using experimental and reference images. In accurate assessment, the overall accuracy and kappa coefficients were about 85% and 0.7128, respectively. This indicates that the proposed technique is effective for recovering the original land surface.

Automatic Construction of Deep Learning Training Data for High-Definition Road Maps Using Mobile Mapping System (정밀도로지도 제작을 위한 모바일매핑시스템 기반 딥러닝 학습데이터의 자동 구축)

  • Choi, In Ha;Kim, Eui Myoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.3
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    • pp.133-139
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    • 2021
  • Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.

Automated Data Extraction from Unstructured Geotechnical Report based on AI and Text-mining Techniques (AI 및 텍스트 마이닝 기법을 활용한 지반조사보고서 데이터 추출 자동화)

  • Park, Jimin;Seo, Wanhyuk;Seo, Dong-Hee;Yun, Tae-Sup
    • Journal of the Korean Geotechnical Society
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    • v.40 no.4
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    • pp.69-79
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    • 2024
  • Field geotechnical data are obtained from various field and laboratory tests and are documented in geotechnical investigation reports. For efficient design and construction, digitizing these geotechnical parameters is essential. However, current practices involve manual data entry, which is time-consuming, labor-intensive, and prone to errors. Thus, this study proposes an automatic data extraction method from geotechnical investigation reports using image-based deep learning models and text-mining techniques. A deep-learning-based page classification model and a text-searching algorithm were employed to classify geotechnical investigation report pages with 100% accuracy. Computer vision algorithms were utilized to identify valid data regions within report pages, and text analysis was used to match and extract the corresponding geotechnical data. The proposed model was validated using a dataset of 205 geotechnical investigation reports, achieving an average data extraction accuracy of 93.0%. Finally, a user-interface-based program was developed to enhance the practical application of the extraction model. It allowed users to upload PDF files of geotechnical investigation reports, automatically analyze these reports, and extract and edit data. This approach is expected to improve the efficiency and accuracy of digitizing geotechnical investigation reports and building geotechnical databases.

A Study on the Field Data Applicability of Seismic Data Processing using Open-source Software (Madagascar) (오픈-소스 자료처리 기술개발 소프트웨어(Madagascar)를 이용한 탄성파 현장자료 전산처리 적용성 연구)

  • Son, Woohyun;Kim, Byoung-yeop
    • Geophysics and Geophysical Exploration
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    • v.21 no.3
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    • pp.171-182
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    • 2018
  • We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.

The Comparison of Quantitative Indices by Changing an Angle of LAO View in Multi-Gated Cardiac Blood Pool Scan (게이트 심장 혈액풀 스캔에서 좌전사위상 각도의 변화에 따른 정량적 지표 비교)

  • Yoon, Soon-Sang;Nam, Ki-Pyo;Ryu, Jae-Kwang;Kim, Seong-Hwan
    • The Korean Journal of Nuclear Medicine Technology
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    • v.16 no.1
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    • pp.57-61
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    • 2012
  • Purpose: The multi-gated cardiac blood pool scan is to evaluate the function of left ventricle (LV) and usefully observe a value of ejection fraction (EF) for a patient who is receiving chemotherapy. To calculate LVEF, we should adjust an angle of left anterior oblique (LAO) view to separate both ventricles. And by overlapped ventricles, it is possible to affect LVEF. The purpose of this study is to investigate and compare quantitative indices by changing an angle of LAO view. Materials and methods: We analyzed the 49 patients who were examined by multi-gated cardiac blood pool scan in department of nuclear medicine at Asan Medical Center from June to September 2011. Firstly, we acquired "Best septal" view. And then, we got images by addition and subtraction of angle for LAO view to anterior and lateral. We compared three LAO views for 20 people by 5 degrees and 39 people by 10 degrees. And we analyzed quantitative indices, EF, end diastole and end systole counts, by automated and manual region of interest (ROI) modes. Results: Firstly, we analyzed quantitative indices by automated ROI mode. In case of 5 degrees, the averages of EF are $61.0{\pm}7.5$, $62.1{\pm}7.1$, $60.9{\pm}6.7%$ ($p$=0.841) in LAO, LAO $-5^{\circ}$ and LAO $+5^{\circ}$ respectively. And there is no difference in end diastole and end systole counts ($p$<0.05). In case of 10 degrees, the averages of EF are $62.4{\pm}9.5$, $62.3{\pm}10.8$, $61.6{\pm}.9.3%$ ($p$=0.938) in LAO, LAO $-10^{\circ}$ and LAO $+10^{\circ}$ respectively. And there is no difference in end diastole and end systole counts ($p$<0.05). Secondly, we analyzed quantitative indices by manual ROI mode. In case of 5 degrees, the averages of EF are $62.8{\pm}7.1$, $63.6{\pm}7.5$, $62.7{\pm}7.3%$ ($p$=0.903) in LAO, LAO $-5^{\circ}$ and LAO $+5^{\circ}$ respectively. And there is no difference in end diastole and end systole counts ($p$<0.05). In case of 10 degrees, the averages of EF are $65.5{\pm}9.0$, $66.3{\pm}8.7$, $63.5{\pm}.9.3%$ (p=0.473) in LAO, LAO $-10^{\circ}$ and LAO $+10^{\circ}$ respectively. And there is no difference in end diastole and end systole counts ($p$<0.05). Conclusion: When an image is nearly "Best septal" view, the difference of LAO angle would not affect to change LVEF. Although there was no difference in quantitative analysis, deviations could happen when to interpret wall motion qualitatively by reading physicians.

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Analysis of Optimal Resolution and Number of GCP Chips for Precision Sensor Modeling Efficiency in Satellite Images (농림위성영상 정밀센서모델링 효율성 재고를 위한 최적의 해상도 및 지상기준점 칩 개수 분석)

  • Choi, Hyeon-Gyeong;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1445-1462
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    • 2022
  • Compact Advanced Satellite 500-4 (CAS500-4), which is scheduled to be launched in 2025, is a mid-resolution satellite with a 5 m resolution developed for wide-area agriculture and forest observation. To utilize satellite images, it is important to establish a precision sensor model and establish accurate geometric information. Previous research reported that a precision sensor model could be automatically established through the process of matching ground control point (GCP) chips and satellite images. Therefore, to improve the geometric accuracy of satellite images, it is necessary to improve the GCP chip matching performance. This paper proposes an improved GCP chip matching scheme for improved precision sensor modeling of mid-resolution satellite images. When using high-resolution GCP chips for matching against mid-resolution satellite images, there are two major issues: handling the resolution difference between GCP chips and satellite images and finding the optimal quantity of GCP chips. To solve these issues, this study compared and analyzed chip matching performances according to various satellite image upsampling factors and various number of chips. RapidEye images with a resolution of 5m were used as mid-resolution satellite images. GCP chips were prepared from aerial orthographic images with a resolution of 0.25 m and satellite orthogonal images with a resolution of 0.5 m. Accuracy analysis was performed using manually extracted reference points. Experiment results show that upsampling factor of two and three significantly improved sensor model accuracy. They also show that the accuracy was maintained with reduced number of GCP chips of around 100. The results of the study confirmed the possibility of applying high-resolution GCP chips for automated precision sensor modeling of mid-resolution satellite images with improved accuracy. It is expected that the results of this study can be used to establish a precise sensor model for CAS500-4.

Assessment of Cerebral Hemodynamic Changes in Pediatric Patients with Moyamoya Disease Using Probabilistic Maps on Analysis of Basal/Acetazolamide Stress Brain Perfusion SPECT (소아 모야모야병에서 뇌확률지도를 이용한 수술전후 혈역학적 변화 분석)

  • Lee, Ho-Young;Lee, Jae-Sung;Kim, Seung-Ki;Wang, Kyu-Chang;Cho, Byung-Kyu;Chung, June-Key;Lee, Myung-Chul;Lee, Dong-Soo
    • Nuclear Medicine and Molecular Imaging
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    • v.42 no.3
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    • pp.192-200
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    • 2008
  • To evaluate the hemodynamic changes and the predictive factors of the clinical outcome in pediatric patients with moyamoya disease, we analyzed pre/post basal/acetazolamide stress brain perfusion SPECT with automated volume of interest (VOIs) method. Methods: Total fifty six (M:F = 33:24, age $6.7{\pm}3.2$ years) pediatric patients with moyamoya disease, who underwent basal/acetazolamide stress brain perfusion SPECT within 6 before and after revascularization surgery (encephalo-duro-arterio-synangiosis (EDAS) with frontal encephalo-galeo-synangiosis (EGS) and EDAS only followed on contralateral hemisphere), and followed-up more than 6 months after post-operative SPECT, were included. A mean follow-up period after post-operative SPECT was $33{\pm}21$ months. Each patient's SPECT image was spatially normalized to Korean template with the SPM2. For the regional count normalization, the count of pons was used as a reference region. The basal/acetazolamide-stressed cerebral blood flow (CBF), the cerebral vascular reserve index (CVRI), and the extent of area with significantly decreased basal/acetazolamide- stressed rCBF than age-matched normal control were evaluated on both medial frontal, frontal, parietal, occipital lobes, and whole brain in each patient's images. The post-operative clinical outcome was assigned as good, poor according to the presence of transient ischemic attacks and/or fixed neurological deficits by pediatric neurosurgeon. Results: In a paired t-test, basal/acetazolamide-stressed rCBF and the CVRI were significantly improved after revascularization (p<0.05). The significant difference in the pre-operative basal/acetazolamide-stressed rCBF and the CVRI between the hemispheres where EDAS with frontal EGS was performed and their contralateral counterparts where EDAS only was done disappeared after operation (p<0.05). In an independent student t-test, the pre-operative basal rCBF in the medial frontal gyrus, the post-operative CVRI in the frontal lobe and the parietal lobe of the hemispheres with EDAS and frontal EGS, the post-operative CVRI, and ${\Delta}CVRI$ showed a significant difference between patients with a good and poor clinical outcome (p<0.05). In a multivariate logistic regression analysis, the ${\Delta}CVRI$ and the post-operative CVRI of medial frontal gyrus on the hemispheres where EDAS with frontal EGS was performed were the significant predictive factors for the clinical outcome (p =0.002, p =0.015), Conclusion: With probabilistic map, we could objectively evaluate pre/post-operative hemodynamic changes of pediatric patients with moyamoya disease. Specifically the post-operative CVRI and the post-operative CVRI of medial frontal gyrus where EDAS with frontal EGS was done were the significant predictive factors for further clinical outcomes.