• The Korean Journal of Nuclear Medicine Technology
• /
• v.12 no.3
• /
• pp.222-228
• /
• 2008

Purpose: The objectives of this study were to compare the left ventricle ejection fraction (LVEF) from gated cardiac blood pool scan (GCBP) for analysis auto-drawing region of interest mode (AROI) and manual-drawing region of interest mode (MROI), respectively. To evaluation the relationships between values produced by both ROI modes. Materials and Methods: Gated cardiac blood pool scan using in vivo method Tc-99m Red Blood Cell were performed for 33 patients (mean age: $53.2{\pm}13.2\;y$) with objective of chemotherapy using single head gamma camera (ADAC Laboratories, Milpitas, CA). Left ventricular ejection fraction was automatically and manually measured, respectively. Results: There was significant difference statistically between AROI and MROI ($LVEF^{AROI}$: $71.4{\pm}12.4%$ vs. $LVEF^{MROI}$: $65.8{\pm}5.9%$, p=0.003). Intra-observer agreements in AROI was higher than MROI ($\gamma^{AROI}=0.964$, Cronbach's $\alpha^{AROI}=0.986$ vs. $\gamma^{MROI}=0.793$, Cronbach's $\alpha^{MROI}=0.911$), either. Additionally, there was no significant difference statistically at best septal view (${\Delta}LVEF^{BSV}=0.7{\pm}2.3%$, p=0.233), however statistically significant difference was found at badly separated septal view (${\Delta}LVEF=10.9{\pm}11.4%$, p=0.001). Moreover, Intra-observer agreements in best septal view was higher than badly separated septal view ($\gamma^{BSV}=0.939$, Cronbach's $\alpha^{BSV}=0.978$; $\gamma=0.948$, Cronbach's $\alpha=0.981$ at AROI, $\gamma^{BSV}=0.836$, Cronbach's $\alpha^{BSV}=0.936$; $\gamma=0.748$, Cronbach's $\alpha=0.888$ at MROI). Conclusion: When best septal view was acquired, LVEF by AROI and MROI indicated not different. Comparing Intra-observer agreements with AROI and MROI, the AROI tended to show higher. Therefore, it is considered that the AROI than MROI is valuable in reproducibility and objective when ROI analysis by acquire left ventricular of best septal view.

• Progress in Medical Physics
• /
• v.12 no.1
• /
• pp.41-50
• /
• 2001

The quantification analysis of renal scintigraphy is strongly affected by the location, shape and size of region of interest(ROI). When ROIs are drawn manually, these ROIs are not reproducible due to the operators' subjective point of view, and may lead to inconsistent results even if the same data were analyzed. In this study, the effect of the ROI variation on the analysis of renal scintigraphy when the ROIs are drawn manually was investigated, and in order to obtain more consistent results, methods for automated ROI definition were developed and the results from the application of the developed methods were analyzed. Relative renal function, glomerular filtration rate and mean transit time were selected as clinical parameters for the analysis of the effect of ROI and the analysis tools were designed with the programming language of IDL5.2. To obtain renal scintigraphy, $^{99m}$Tc-DTPA was injected to the 11 adults of normal condition and to study the inter-operator variability, 9 researchers executed the analyses. The calculation of threshold using the gradient value of pixels and border tracing technique were used to define renal ROI and then the background ROI and aorta ROI were defined automatically considering anatomical information and pixel value. The automatic methods to define renal ROI were classified to 4 groups according to the exclusion of operator's subjectiveness. These automatic methods reduced the inter-operator variability remarkably in comparison with manual method and proved the effective tool to obtain reasonable and consistent results in analyzing the renal scintigraphy quantitatively.

• Progress in Medical Physics
• /
• v.14 no.4
• /
• pp.268-278
• /
• 2003

Purpose：The aim of this study was to evaluate the striatal binding ratio, the anterior/posterior ratio and reproducibility using a template based registration method using the standard MR template as a replacement for each patients MR image. Materials and Methods：This study analyzed the 123I IPT SPECT images of 30 patients with IPD, who were subdivided into 17 patients (56.6$\pm$10.8 yr, M/F : 8/9.) with mild IPD, and 13 patients (56.4$\pm$11.1 yr, M/F : 8/5) with severe IPD. In addition, 11 normal controls (57.8$\pm$14.4 yr, M/F : 4/7) were also analyzed. The ROIs were positioned manually in the same slice showing the highest striatal activity using the traditional manual method, whereas those were positioned automatically in a mid striatal slice of the SPECT image coregistered to the standard T1 weighted MR template. Results : The specific binding ratio (SBR) obtained using the template based registration method strongly correlated with those using the manual method in all groups : normal controls (r=0.85, P<0.001), mild IPD (r=0.84, P<0.001) and severe IPD (r=0.7, P=0.01). The SBRs obtained using both methods were significantly different among the three groups (P=0.05) and the SBRs obtained by the template based registration method were higher than those by the manual method (P=0.05) in all three groups. The APRs obtained by the template based registration correlated with those using manual method in only mild IPD (r=0.72, P=0.0). The APRs obtained by the template based registration method were significantly different from the normal controls and those with mild or severe IPD (P<0.05), whereas those obtained using the manual method were not significantly different among the three groups (P＞0.1). The reproducibility (rmsCV) of the template based registration method was 7.2% (normal controls：5.2%, mild IPD：4.2%, severe IPD：10.8%), whereas the reproducibility of the manual method was 31% (normal controls：19.7%, mild IPD：21.7%, severe IPD：46.2%). Conclusion：These results show that the use of $^{123}$ I-IPT SPECT for assessing IPD is affected by the methods used to position the striatal ROI. The template based registration method using the standard MR template can be useful in diagnosing IPD and assessing the disease severity with a high reproducibility. Therefore, the template based registration method appears to be a good replacement for the manual method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.835-836
• /
• 2009

본 연구는 스케치기반의 인터페이슬 통해 큐빅스플라인 곡선을 자동으로 생성하는 방법을 제시한다. 또한 탐색항해에서 많이 발생하는 이동중 관심영역으로의 뷰포인트를 자동으로 변환하기 위한 방법을 제시한다. 스케치기반 인터페이스는 일반인에게 친숙한 종이환경과 유사한 인터페이스를 통해 가상환경의 탐색항해를 위한 투어패스를 설정하고 관심영역을 중심으로 뷰포인트가 자동적으로 변환하는 기법을 제시함으로써 가상환경에 전문적인 지식이 없거나 전문개발자에게도 시간과 노력을 절약할 수 있는 방법을 제시한다.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.16 no.1
• /
• pp.27-33
• /
• 2012

Purpose: Most of diagnosis in the pediatric hydronephrosis patients have been performed $^{99m}Tc$-DMSA renal scan. Then the region of interest (ROI) is set for comparative analysis of uptake ratio in left-right kidney after acquiring the image. But if the equipment set an automatic ROI, the ROI could include expanded renal pelvis due to hydronephrosis and the uptake ratio of left-right kidney will be incorrect result. Therefore this study compared both ROIs including expanded renal pelvis and excluding renal pelvis through experiment using normal kidney phantom and expanded renal pelvis phantom and suggested setting method of improved ROI. In addition, this study have been helped by readout doctor for investigate distinction radiopharmaceutical uptake between renal cortex and remained urine by expanded renal pelvis. Materials and Methods: The both of renal phantoms were filled with water and shacked with $^{99m}TcO_4$ 111 MBq. In order to describe the expanded renal pelvis, the five latex balloon were all filled with 10 mL water and each of balloon was mixed with $^{99m}TcO_4$ 18.5, 37, 55.5, 74, 92.5 MBq. And we made phantom with fixed $^{99m}TcO_4$activity of 37 MBq and mixed water 5, 10, 15, 20, 25 mL in each balloon. The left kidney was fixed its shape and the right kidney was modified like as hydronephrosis kidney by attached the latex balloons. And the acquiring counts were 2 million. After acquisition, we compared the image of ROI with Expanded renal pelvis and the image of ROI without renal pelvis for analyzing difference in the uptake ratio of left-right kidney and for reproducibility, set the ROI 5 times in the same images. Patients were injected $^{99m}Tc$-DMSA 1.5~1.9 MBq/kg and scanned 3 to 4 hours after injection. The each of 3 skillful radio technologists performed the comparing estimation by setting ROI. To determine statistical significance between two data, SPSS (ver. 17) Wilcoxon Signed Ranks Test was used. Results: As a result of renal phantom's experiment, we compared with average of counts Background (BKG) ratios in the setting of ROI including expanded renal pelvis and setting of excluding expanded renal pelvis. Therefore, they can obtain changed counts and changed ratios. Patient also can obtain same results. In addition, the radiopharmaceutical uptake in expanded renal pelvis was come out the remained urine that couldn't descend to ureter by the help of readout doctor. Conclusion: As above results, the case of setting ROI including expanded renal pelvis was more abnormally increasing uptake ratio than the case of setting ROI excluding expanded renal pelvis in analysis the uptake ratio in left-right kidney of hydronephrosis. Because of the work convenience and prompted analysis, the automatic ROI is generally used. But in case of the hydronephrosis study, we should set the manual ROI without expanded renal pelvis for an accurate observation of the uptake ratio of left-right kidney since the radiopharmaceutical uptake in expanded renal pelvis is the remained urine.

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.06c
• /
• pp.458-462
• /
• 2010

본 논문은 X-선 혈관조영영상에서 기울기 정보 및 최대 빈도수를 이용한 카테터 자동 분할 방법을 제안한다. 제안방법은 세 단계로 이루어진다. 첫째, 분할하고자 하는 카테터 관심영역을 설정하고, 영상의 대조대비를 높이기 위한 밝기값 스트레칭을 수행한다. 둘째, 카테터 후보 경계점을 추출하기 위하여 카테터 방향을 고려한 경계 강조 마스크를 영상에 적용한다. 셋째, 카테터 후보 경계점에서 기울기가 크고 최대 빈도수 직경을 갖는 카테터 경계점을 추출하고 이들을 선형 보간하여 최종 카테터 경계를 분할한다. 제안 방법의 평가를 위하여 육안 평가 및 전문가가 수동 분할한 결과와 본 제안방법을 적용하여 얻은 중복 영역 비율과 평균 거리 차이를 측정한 정확성 평가를 수행하였고, 수행시간을 측정하였다. 실험결과 중복 영역 비율은 93.9%${\pm}$2.7%, 평균 거리 차이는 0.116-픽셀, 수행시간은 평균 0.011초로 측정되었다.

• Journal of Biomedical Engineering Research
• /
• v.24 no.2
• /
• pp.91-97
• /
• 2003

The Propose of this paper is hierarchical detection method for the optic disc in fundus image. We detected the optic disc boundary by using the Prior information. It is based on the anatomical knowledge of fundus which are the vessel information. the image complexity. and etc. The whole method can be divided into three stages . First, we selected the region of interest(ROI) which included optic disc region. This is used to calculate location and size of the optic disc which are prior knowledge to simplify image preprocessing. And then. we divided the fundus image into numberous regions with watershed algorithm and detected intial boundary of the optic disc by reducing the number of the separated regions in ROI. Finally, we have searching the defective parts of boundary as a result of serious vessel interference in order to detect the accurate boundary of optic disc and we have removing and interpolating them.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.1
• /
• pp.153-158
• /
• 2016

A detection algorithm of fallen pear bags caused by natural disaster like heavy rain, typhoon, hurricane, etc. is presented in this paper. The algorithm is developed for the gray pear bags with printed characters which are widely used at pear farms at Sangju and Naju producing large quantity of pears for export. It sets a region of interest (ROI) at first and then eliminates the regions having chromatic color in ROI. Morphological operation and prior information are used to eliminate small noises and several unusual regions and finally the regions of fallen pear bags are remained. The remained regions are analyzed and counted to estimate the scale of damage. Test images are consisted of the images taken at pear farms of Sangju and Naju at 2014. Experimental result shows that the detection rate of pear bags is more than 90% and also the proposed system can be implemented in real-time using hand-held devices because of its simple and parallel architecture.

• The KIPS Transactions:PartB
• /
• v.10B no.2
• /
• pp.127-134
• /
• 2003

This paper is intended to develop an algorithm for automatic detection of traffic accidents using image sequences. This algorithm is designed for detecting stopped vehicles traffic accidents, break down, illegal stop in the road shoulder - on the range of camera view. Virtual traps are set on accident-prone spots. We analyze the changes in gray levels of pixels on the virtual traps which represent the motion of vehicles on the corresponding spots. We verify the proposed algorithm by simulating some situations and checking if it detect them correctly.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.2
• /
• pp.260-267
• /
• 2011

This paper proposes a method for segmenting objects from the background in IR(Infrared) images based on GrabCut algorithm. The GrabCut algorithm needs the window encompassing the interesting known object. This procedure is processed by user. However, to apply it for object recognition problems in image sequences. the location of window should be determined automatically. For this, we adopted the Otsu' algorithm for segmenting the interesting but unknown objects in an image coarsely. After applying the Otsu' algorithm, the window is located automatically by blob analysis. The GrabCut algorithm needs the probability distributions of both the candidate object region and the background region surrounding closely the object for estimating the Gaussian mixture models(GMMs) of the object and the background. The probability distribution of the background is computed from the background window, which has the same number of pixels within the candidate object region. Experiments for various IR images show that the proposed method is proper to segment out the interesting object in IR image sequences. To evaluate performance of proposed segmentation method, we compare other segmentation methods.