• Title/Summary/Keyword: image analysis algorithm

Search Result 1,484, Processing Time 0.025 seconds

Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis

  • Chenggong Yan;Jie Lin;Haixia Li;Jun Xu;Tianjing Zhang;Hao Chen;Henry C. Woodruff;Guangyao Wu;Siqi Zhang;Yikai Xu;Philippe Lambin
    • Korean Journal of Radiology
    • /
    • v.22 no.6
    • /
    • pp.983-993
    • /
    • 2021
  • Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

Motion Recognitions Based on Local Basis Images Using Independent Component Analysis (독립성분분석을 이용한 국부기저영상 기반 동작인식)

  • Cho, Yong-Hyun
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • v.18 no.5
    • /
    • pp.617-623
    • /
    • 2008
  • This paper presents a human motion recognition method using both centroid shift and local basis images. The centroid shift based on 1st moment balance technique is applied to get the robust motion images against position or size changes, the extraction of local basis images based on independent component analysis(ICA) is also applied to find a set of statistically independent motion features, which is included in each motions. Especially, ICA of fixed-point(FP) algorithm based on Newton method is used for being quick to extract a local basis images of motions. The proposed method has been applied to the problem for recognizing the 160(1 person * 10 animals * 16 motions) sign language motion images of 240*215 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate) than the method using local eigen images and the method using local basis images without centroid shift respectively.

Applying CBR algorithm for cyber infringement profiling system (사례기반추론기법을 적용한 침해사고 프로파일링 시스템)

  • Han, Mee Lan;Kim, Deok Jin;Kim, Huy Kang
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.23 no.6
    • /
    • pp.1069-1086
    • /
    • 2013
  • Nowadays, web defacement becomes the utmost threat which can harm the target organization's image and reputation. These defacement activities reflect the hacker's political motivation or his tendency. Therefore, the analysis of the hacker's activities can give the decisive clue to pursue criminals. A specific message or photo or music on the defaced web site and the outcome of analysis will be supplying some decisive clues to track down criminals. The encoding method or used fonts of the remained hacker's messages, and hacker's SNS ID such as Twitter or Facebook ID also can help for tracking hackers information. In this paper, we implemented the web defacement analysis system by applying CBR algorithm. The implemented system extracts the features from the web defacement cases on zone-h.org. This paper will be useful to understand the hacker's purpose and to plan countermeasures as a IDSS(Investigation Detection Support System).

Development of Experience System for Sasang Constitution Analysis (사상체질 분석 체험 시스템 개발)

  • So, Ji-Ho;Jeon, Young-Ju
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.20 no.5
    • /
    • pp.9-13
    • /
    • 2020
  • Sasang Constitutional Medicine is a traditional Korean medicine optimized for personalized medicine, and despite its effective clinical efficacy, the inaccuracy of constitutional diagnosis has been pointed out as a limitation. To improve the accuracy, a constitutional analysis algorithm based on quantitative data was developed. In this study, a constitutional analysis experience system applied with the algorithm was developed and repeatability was evaluated. The system analyzes the constitution of the experiencer by collecting front and side facial images, audio, and questionnaire and calculating the integrated constitution probability value. To evaluate the repeatability of the probability values of the system was performed five times each for three people, and the coefficient of variation was 4.778%, indicating that the repeatability was sufficient. The system could contribute to the promotion of the awareness of Sasang medicine.

2D-MELPP: A two dimensional matrix exponential based extension of locality preserving projections for dimensional reduction

  • Xiong, Zixun;Wan, Minghua;Xue, Rui;Yang, Guowei
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.16 no.9
    • /
    • pp.2991-3007
    • /
    • 2022
  • Two dimensional locality preserving projections (2D-LPP) is an improved algorithm of 2D image to solve the small sample size (SSS) problems which locality preserving projections (LPP) meets. It's able to find the low dimension manifold mapping that not only preserves local information but also detects manifold embedded in original data spaces. However, 2D-LPP is simple and elegant. So, inspired by the comparison experiments between two dimensional linear discriminant analysis (2D-LDA) and linear discriminant analysis (LDA) which indicated that matrix based methods don't always perform better even when training samples are limited, we surmise 2D-LPP may meet the same limitation as 2D-LDA and propose a novel matrix exponential method to enhance the performance of 2D-LPP. 2D-MELPP is equivalent to employing distance diffusion mapping to transform original images into a new space, and margins between labels are broadened, which is beneficial for solving classification problems. Nonetheless, the computational time complexity of 2D-MELPP is extremely high. In this paper, we replace some of matrix multiplications with multiple multiplications to save the memory cost and provide an efficient way for solving 2D-MELPP. We test it on public databases: random 3D data set, ORL, AR face database and Polyu Palmprint database and compare it with other 2D methods like 2D-LDA, 2D-LPP and 1D methods like LPP and exponential locality preserving projections (ELPP), finding it outperforms than others in recognition accuracy. We also compare different dimensions of projection vector and record the cost time on the ORL, AR face database and Polyu Palmprint database. The experiment results above proves that our advanced algorithm has a better performance on 3 independent public databases.

A Study on the Quantitative Analysis for the Forest Landscape (삼림경관에 관한 계량적 분석에 관한 연구)

  • 서주환
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.15 no.1
    • /
    • pp.39-67
    • /
    • 1987
  • The purpose of this thesis is to suggest objective basic data for the environmental design through the quantitative analysis of the visual quality included in the physical environment of forest landscape. For this, landscape values of forest landscape have been evaluated by using the Iverson method, the images structure of forest landscape's main utilizing space have been analysed by the factor analysis algorithm, degree of visual preferences have been pleasured mainly by questionnaries and SBE method, and finally these thesis can be summarized as fallow LCP with high values of Iverson factors I and IV yield high landscape value. Specifically, Iverson factor IV has been found to play the dominant. For all experimental points, significant seasonal variations in S.D. scale values have been observed. In natural parks, where artificial structures are complementary to the natural landscape, main factors of image are S.D. scales such as the visual sequence, the formal simplicity of structures, the emphasis, the unification of heterogeneous factors and the assimilation. Factors covering the spatial image of natural parks have been found to be the overall evaluation, the individual characteristics, the tidiness, the potentiality, the dignity, the intimacy and the space volume. For all seasons, factors such as the individual characteristics, the dignity, the tidiness, the potentiality, yield high factor scores. As for factors determining the degree of visual preference, variables such as the summit, the skyline, rocks, the water and the degree of natural destruction by artificial structures yield high values for all seasons.

  • PDF

Software Development for Dynamic Positron Emission Tomography : Dynamic Image Analysis (DIA) Tool (동적 양전자방출단층 영상 분석을 위한 소프트웨어 개발: DIA Tool)

  • Pyeon, Do-Yeong;Kim, Jung-Su;Jung, Young-Jin
    • Journal of radiological science and technology
    • /
    • v.39 no.3
    • /
    • pp.369-376
    • /
    • 2016
  • Positron Emission Tomography(PET) is nuclear medical tests which is a combination of several compounds with a radioactive isotope that can be injected into body to quantitatively measure the metabolic rate (in the body). Especially, Phenomena that increase (sing) glucose metabolism in cancer tissue using the $^{18}F$-FDG (Fluorodeoxyglucose) is utilized widely in cancer diagnosis. And then, Numerous studies have been reported that incidence seems high availability even in the modern diagnosis of dementia and Parkinson's (disease) in brain disease. When using a dynamic PET iamge including the time information in the static information that is provided for the diagnosis many can increase the accuracy of diagnosis. For this reason, clinical researchers getting great attention but, it is the lack of tools to conduct research. And, it interfered complex mathematical algorithm and programming skills for activation of research. In this study, in order to easy to use and enable research dPET, we developed the software based graphic user interface(GUI). In the future, by many clinical researcher using DIA-Tool is expected to be of great help to dPET research.

Landscape Value Analysis of Hallyǒ Haesang Sea National Park (한려해상국립공원(閑麗海上國立公園)의 경관자원(景觀資源) 가치분석(價値分析))

  • Kim, Sei-Cheon
    • Journal of Korean Society of Forest Science
    • /
    • v.89 no.2
    • /
    • pp.145-160
    • /
    • 2000
  • This study is focused to the national park of Korean typical Sea Hally$\check{o}$ Haesang, and its visual resources and practiced inspect course by the way of suppositions and tests, to show the visual resource management objectively, and that of qualitative basic data. Accordingly by measuring the physical amount spatial structure with the visual amount originated from the Mesh Analyzing Method and the Visual Preference from the Scenic Beauty Estimation(S.B.E.) method and analyzed the valuation of the visual resource by Iverson method. Spatial image structure measured by Semantic Differential(S.D.) Scale was shown through the factor analysis algorithm for the analyzing psychological amount and examined the flowing out of decisive factor and the objective importance related to the mutual factors by appling the measurement of the visual quality. As a national Park, the visual factors that have natural landscape harmonized with forest, sky, surface of the water, curious stones and rocks, and temples should be escalated their values affirmatively so as to be the scenery of pointed direction and enjoyable, and it is of more needed for visual resource and its' controlling technique to make artificial structures more intentional planning and systemical setting. When we are viewing the improvement for the national park along with the visual resource management, reasonable level of development is needed, because when men interference surpass plantations and leasts will be damaged and the quality of natural landscape can be lowered, so it is needed to set up a management end, tangibly or clearly; and it is permitted limit coming and going ablably by accounting the suitable number for availing. But the controling end should be set in every level, positive management, very actively within the permissive varcability. It is the main business for the national park to prevent the damage from human for their gay life or to prevent the damage of a land carpet, and to restorate for the visual resource management.

  • PDF

A Study on Segmentation and Volume Calculation of the White Matter and Gray Matter for Brain Image Processing (뇌 영상처리를 위한 백질과 회백질의 추출 및 체적 산출에 관한 연구)

  • Kim, Shin-Hong
    • 전자공학회논문지 IE
    • /
    • v.43 no.4
    • /
    • pp.21-27
    • /
    • 2006
  • This paper is for the segmentation and volume calculation of the white matter and gray matter from brain MRI. We segment white matter, gray matter and CSF from the Brain image in the normal and abnormal person, and calculate the volume of segmented tissue. In this paper, we present a new method of extracting white matter, gray matter and CSF and calculation its volume from MR images for brain. And we have developed the determining method of threshold that can extract white matter and gray matter from MR image for brain through the analysis of gray values represented by ratio of each component. We proposed the calculation method of volume for white matter and gray matter by using number of extracted pixels in each slice. This algorithm input CSF/Head volume ratio and age of patient and calculates discriminant value through discriminant expression, classifies normal and abnormal using calculated discriminant value. As a result, we could blow that white matter and gray matter volume decrease and CSF volume increase as we grow gold.

Analysis on Optimal Threshold Value for Infrared Video Flame Detection (적외선 영상의 화염 검출을 위한 최적 문턱치 분석)

  • Jeong, Soo-Young;Kim, Won-Ho
    • Journal of Satellite, Information and Communications
    • /
    • v.8 no.4
    • /
    • pp.100-104
    • /
    • 2013
  • In this paper, we present an optimal threshold setting method for flame detection of infrared thermal image. Conventional infrared flame detection methods used fixed intensity threshold to segment candidate flame regions and further processing is performed to decide correct flame detection. So flame region segmentation step using the threshold is important processing for fire detection algorithm. The threshold should be change in input image depends on camera types and operation conditions. We have analyzed the conventional thresholds composed of fixed-intensity, average, standard deviation, maximum value. Finally, we extracted that the optimal threshold value is more than summation of average and standard deviation, and less than maximum value. it will be enhance flame detection rate than conventional fixed-threshold method.