• Title/Summary/Keyword: Image Sets

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Features Extraction of Remote Sensed Multispectral Image Data Using Rough Sets Theory (Rough 집합 이론을 이용한 원격 탐사 다중 분광 이미지 데이터의 특징 추출)

  • 원성현;정환묵
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.3
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    • pp.16-25
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    • 1998
  • In this paper, we propose features extraction method using Rough sets theory for efficient data classifications in hyperspectral environment. First, analyze the properties of multispectral image data, then select the most efficient bands using discemibility of Rough sets theory based on analysis results. The proposed method is applied Landsat TM image data, from this, we verify the equivalence of traditional bands selection method by band features and bands selection method using Rough sets theory that pmposed in this paper. Finally, we present theoretical basis to features extraction in hyperspectral environment.

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Quantitative Evaluation of Setup Error for Whole Body Stereotactic Radiosurgery by Image Registration Technique

  • Kim, Young-Seok;Yi, Byong-Yong;Kim, Jong-Hoon;Ahn, Seung-Do;Lee, Sang-wook;Im, Ki-Chun;Park, Eun-Kyung
    • Proceedings of the Korean Society of Medical Physics Conference
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    • 2002.09a
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    • pp.103-105
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    • 2002
  • Whole body stereotactic radiosurgery (WBSRS) technique is believed to be useful for the metastatic lesions as well as relatively small primary tumors in the trunk. Unlike stereotactic radiosurgery to intracranial lesion, inherent limitation on immobilization of whole body makes it difficult to achieve the reliable setup reproducibility. For this reason, it is essential to develop an objective and quantitative method of evaluating setup error for WBSRS. An evaluation technique using image registration has been developed for this purpose. Point pair image registrations with WBSRS frame coordinates were performed between two sets of CT images acquired before each treatment. Positional displacements could be determined by means of volumetric planning target volume (PTV) comparison between the reference and the registered image sets. Twenty eight sets of CT images from 19 WBSRS patients treated in Asan Medical Center have been analyzed by this method for determination of setup random error of each treatment. It is objective and clinically useful to analyze setup error quantitatively by image registration technique with WBSRS frame coordinates.

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ERS-1 AND CCRS C-SAR Data Integration For Look Direction Bias Correction Using Wavelet Transform

  • Won, J.S.;Moon, Woo-Il M.;Singhroy, Vern;Lowman, Paul-D.Jr.
    • Korean Journal of Remote Sensing
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    • v.10 no.2
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    • pp.49-62
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    • 1994
  • Look direction bias in a single look SAR image can often be misinterpreted in the geological application of radar data. This paper investigates digital processing techniques for SAR image data integration and compensation of the SAR data look direction bias. The two important approaches for reducing look direction bias and integration of multiple SAR data sets are (1) principal component analysis (PCA), and (2) wavelet transform(WT) integration techniques. These two methods were investigated and tested with the ERS-1 (VV-polarization) and CCRS*s airborne (HH-polarization) C-SAR image data sets recorded over the Sudbury test site, Canada. The PCA technique has been very effective for integration of more than two layers of digital image data. When there only two sets of SAR data are available, the PCA thchnique requires at least one more set of auxiliary data for proper rendition of the fine surface features. The WT processing approach of SAR data integration utilizes the property which decomposes images into approximated image ( low frequencies) characterizing the spatially large and relatively distinct structures, and detailed image (high frequencies) in which the information on detailed fine structures are preserved. The test results with the ERS-1and CCRS*s C-SAR data indicate that the new WT approach is more efficient and robust in enhancibng the fine details of the multiple SAR images than the PCA approach.

Comparison of the Quality of Various Polychromatic and Monochromatic Dual-Energy CT Images with or without a Metal Artifact Reduction Algorithm to Evaluate Total Knee Arthroplasty

  • Hye Jung Choo;Sun Joo Lee;Dong Wook Kim;Yoo Jin Lee;Jin Wook Baek;Ji-yeon Han;Young Jin Heo
    • Korean Journal of Radiology
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    • v.22 no.8
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    • pp.1341-1351
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    • 2021
  • Objective: To compare the quality of various polychromatic and monochromatic images with or without using an iterative metal artifact reduction algorithm (iMAR) obtained from a dual-energy computed tomography (CT) to evaluate total knee arthroplasty. Materials and Methods: We included 58 patients (28 male and 30 female; mean age [range], 71.4 [61-83] years) who underwent 74 knee examinations after total knee arthroplasty using dual-energy CT. CT image sets consisted of polychromatic image sets that linearly blended 80 kVp and tin-filtered 140 kVp using weighting factors of 0.4, 0, and -0.3, and monochromatic images at 130, 150, 170, and 190 keV. These image sets were obtained with and without applying iMAR, creating a total of 14 image sets. Two readers qualitatively ranked the image quality (1 [lowest quality] through 14 [highest quality]). Volumes of high- and low-density artifacts and contrast-to-noise ratios (CNRs) between the bone and fat tissue were quantitatively measured in a subset of 25 knees unaffected by metal artifacts. Results: iMAR-applied, polychromatic images using weighting factors of -0.3 and 0.0 (P-0.3i and P0.0i, respectively) showed the highest image-quality rank scores (median of 14 for both by one reader and 13 and 14, respectively, by the other reader; p < 0.001). All iMAR-applied image series showed higher rank scores than the iMAR-unapplied ones. The smallest volumes of low-density artifacts were found in P-0.3i, P0.0i, and iMAR-applied monochromatic images at 130 keV. The smallest volumes of high-density artifacts were noted in P-0.3i. The CNRs were best in polychromatic images using a weighting factor of 0.4 with or without iMAR application, followed by polychromatic images using a weighting factor of 0.0 with or without iMAR application. Conclusion: Polychromatic images combined with iMAR application, P-0.3i and P0.0i, provided better image qualities and substantial metal artifact reduction compared with other image sets.

Design of Image Retrieval System using Color and Morphological Informations based on Binary Sets (이진집합기반에서 칼라와 형태정보를 이용한 영상 검색시스템 설계)

  • 김성동;최기호
    • Journal of Korea Multimedia Society
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    • v.3 no.6
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    • pp.575-584
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    • 2000
  • This paper presents a new image retrieval system with color and morphological informations based on binary sets. Each of them can be obtained from color binary sets and regional segmentation separately. For retrieval processes, the candidate images are decided by comparing color and their image binary sets of the database with query images. Particularly, it is possible that the retrieval of similar-measurements has a weight of color spatial distribution and its objective morphological features. We proposed a new idea for performing simply the complicated similar-measurement of candidated images to improve queried processes. The retrieval method using spatial and morphological features is shown with the effectiveness on the result of implementation on database with 3,000 images.

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On Generalized Quasi-preclosed Sets and Quasi Preseparation Axioms

  • Park, Jin Han;Pyo, Yong Soo
    • Honam Mathematical Journal
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    • v.25 no.1
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    • pp.141-152
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    • 2003
  • In this paper, we define generalized quasi-preclosed sets and gqp-closed functions and obtain some new characterizations of quasi P-normal spaces and quasi P-regular spaces due to Tapi et al. [9,11]. It is shown that the pairwise continuous pre gqp-closed (resp. pairwise preopen pre gqp-closed) surjective image of quasi P-normal (resp. quasi P-regular) space is quasi P-normal (resp. quasi P-regular).

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THE κ-QUOTIENT IMAGES OF METRIC SPACES

  • Lin, Shou;Zheng, Chunyan
    • Communications of the Korean Mathematical Society
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    • v.27 no.2
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    • pp.377-384
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    • 2012
  • In this paper some properties of sequentially closed sets and $k$-closed sets in a topological space are discussed, it is shown that a space is a $k$-quotient image of a metric space if and only if its each sequentially closed set is $k$-closed, and some related examples about connectedness are obtained.

MODELING SATELLITE IMAGE STRIPS WITH COLLINEARITY-BASED AND ORBIT-BASED SENSOR MODELS

  • Kim, Hyun-Suk;Kim, Tae-Jung
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.578-581
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    • 2006
  • Usually to achieve precise geolocation of satellite images, we need to get GCPs (Ground control points) from individual scenes. This requirement greatly increases the cost and processing time for satellite mapping. In this article, we focus on finding appropriate sensor models for entire image strips composing of several adjacent scenes. We tested the feasibility of modelling whole satellite image strips by establishing sensor models of one scene with GCPs and by applying the models to neighboring scenes without GCPs. For this, we developed two types of sensor models: collinearity-based type and orbit-based type and tested them using different sets of unknowns. Results indicated that although the performance of two types was very similar, for modelling individual scenes, it was not for modelling the whole strips. Moreover, the performance of sensor models was remarkably sensitive to different sets of unknowns. It was found that the orbit-based model using attitude biases as unknowns can be used to model SPOT image strips of 420 Km in length.

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Multimodal Medical Image Fusion Based on Sugeno's Intuitionistic Fuzzy Sets

  • Tirupal, Talari;Mohan, Bhuma Chandra;Kumar, Samayamantula Srinivas
    • ETRI Journal
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    • v.39 no.2
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    • pp.173-180
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    • 2017
  • Multimodal medical image fusion is the process of retrieving valuable information from medical images. The primary goal of medical image fusion is to combine several images obtained from various sources into a distinct image suitable for improved diagnosis. Complexity in medical images is higher, and many soft computing methods are applied by researchers to process them. Intuitionistic fuzzy sets are more appropriate for medical images because the images have many uncertainties. In this paper, a new method, based on Sugeno's intuitionistic fuzzy set (SIFS), is proposed. First, medical images are converted into Sugeno's intuitionistic fuzzy image (SIFI). An exponential intuitionistic fuzzy entropy calculates the optimum values of membership, non-membership, and hesitation degree functions. Then, the two SIFIs are disintegrated into image blocks for calculating the count of blackness and whiteness of the blocks. Finally, the fused image is rebuilt from the recombination of SIFI image blocks. The efficiency of the use of SIFS in multimodal medical image fusion is demonstrated on several pairs of images and the results are compared with existing studies in recent literature.

The Dosimetric Effect on Real PTV and OARs at Various Image Fusion Protocol for Pituitary Adenomas (뇌하수체 종양의 방사선 수술 시 영상 융합 프로토콜이 실제 PTV와 OAR 선량에 미치는 영향)

  • Lee, Kyung-Nam;Lee, Dong-Joon;Suh, Tae-Suk
    • Progress in Medical Physics
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    • v.21 no.4
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    • pp.354-359
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    • 2010
  • The purpose of this study is to verify the dosimetric effect on real PTV (planning target volume) coverage and safety of OARs (organs at risk) at various image fusion protocol-based radiosurgery plan for pituitary adenomas. Real PTV coverage and its variation was acquired and maximum dose and the volume absorbing above threshold dose were also measured for verifying the safety of optic pathway and brainstem. The protocol that can reduce superior-inferior uncertainty by using both axial and coronal MR (magnetic resonance) image sets shows relatively lower values than that of case using only axial image sets. As a result, the image fusion protocol with both axial and coronal image sets can be beneficial to generate OAR-weighted radiosurgery plan.