• 제목/요약/키워드: Flash method

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정적 영상에서 Noise Reduction Software의 이해와 적용 (The Understanding and Application of Noise Reduction Software in Static Images)

  • 이형진;송호준;승종민;최진욱;김진의;김현주
    • 핵의학기술
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    • 제14권1호
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    • pp.54-60
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    • 2010
  • 본원에 도입된 새로운 소프트웨어는 SPECT나 전신 뼈 영상에만 국한되어 사용되어 지고 있지만 보다 효과적으로 다른 검사에 적용하기 위해 팬텀을 통한 실험과 영상의 비교를 통하여 그 유용성을 찾아보고자 하였다. 실험을 위하여 Body IEC phantom과 Jaszczak ECT phantom, Capillary를 이용한 실린더 팬텀을 이용하였고, 영상의 처리 전후의 계수, statistics를 비교해 보고 contrast ratio나 BKG의 변화들을 정량적으로 분석해 보았다. Capillary source를 이용한 FWHM 비교에서는 PIXON의 경우 처리 전후의 영상에서 차이가 거의 없었고, ASTONISH의 경우 처리 후의 영상이 우수해짐을 확인할 수 있었다. 반면 Standard deviation과 그에 따른 Variance는 PIXON은 다소 감소한 반면 ASTONISH는 큰 폭으로 증가함을 보였다. IEC phantom을 이용한 BKG variability 비교에서는 PIXON의 경우 전체적으로 감소한 반면 ASTONISH는 다소 증가하는 경향을 보였고, 각각의 sphere에 대한 contrast ratio도 두 가지 방법 모두 향상됨을 확인하였다. 영상의 스케일 면에서도 PIXON의 경우 처리 후에는 window width가 약 4-5배 증가하였지만 ASTONISH에서는 큰 차이가 없었다. 팬텀 실험 분석 후 ASTONISH는 정량적 분석을 위해 ROI를 그려야 하는 기타 검사와 대조도를 강조하는 검사에 적용 가능성을 보였고, PIXON은 획득계수가 부족하거나 SNR이 낮은 핵의학 검사에 유용하게 사용될 것으로 생각되었다. 영상의 분석 인자로 많이 사용되는 정량적인 수치들은 소프트웨어의 적용 후 대체로 향상되었지만 감마카메라의 차이보다 소프트웨어간의 알고리즘 특성으로 인한 결과영상의 차이가 많아 모든 핵의학 검사의 적용에 있어서 일관성을 유지하기는 어려울 것으로 사료된다. 또한 전신 뼈 영상과 같이 검사시간의 획기적 단축과 같은 수단으로는 우수한 영상의 질을 기대하기 어렵다. 새로운 소프트웨어의 도입 시 병원의 특성에 맞는 protocol과 임상 적용 전에 많은 연구가 필요할 것으로 사료된다.

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Information Privacy Concern in Context-Aware Personalized Services: Results of a Delphi Study

  • Lee, Yon-Nim;Kwon, Oh-Byung
    • Asia pacific journal of information systems
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    • 제20권2호
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    • pp.63-86
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    • 2010
  • Personalized services directly and indirectly acquire personal data, in part, to provide customers with higher-value services that are specifically context-relevant (such as place and time). Information technologies continue to mature and develop, providing greatly improved performance. Sensory networks and intelligent software can now obtain context data, and that is the cornerstone for providing personalized, context-specific services. Yet, the danger of overflowing personal information is increasing because the data retrieved by the sensors usually contains privacy information. Various technical characteristics of context-aware applications have more troubling implications for information privacy. In parallel with increasing use of context for service personalization, information privacy concerns have also increased such as an unrestricted availability of context information. Those privacy concerns are consistently regarded as a critical issue facing context-aware personalized service success. The entire field of information privacy is growing as an important area of research, with many new definitions and terminologies, because of a need for a better understanding of information privacy concepts. Especially, it requires that the factors of information privacy should be revised according to the characteristics of new technologies. However, previous information privacy factors of context-aware applications have at least two shortcomings. First, there has been little overview of the technology characteristics of context-aware computing. Existing studies have only focused on a small subset of the technical characteristics of context-aware computing. Therefore, there has not been a mutually exclusive set of factors that uniquely and completely describe information privacy on context-aware applications. Second, user survey has been widely used to identify factors of information privacy in most studies despite the limitation of users' knowledge and experiences about context-aware computing technology. To date, since context-aware services have not been widely deployed on a commercial scale yet, only very few people have prior experiences with context-aware personalized services. It is difficult to build users' knowledge about context-aware technology even by increasing their understanding in various ways: scenarios, pictures, flash animation, etc. Nevertheless, conducting a survey, assuming that the participants have sufficient experience or understanding about the technologies shown in the survey, may not be absolutely valid. Moreover, some surveys are based solely on simplifying and hence unrealistic assumptions (e.g., they only consider location information as a context data). A better understanding of information privacy concern in context-aware personalized services is highly needed. Hence, the purpose of this paper is to identify a generic set of factors for elemental information privacy concern in context-aware personalized services and to develop a rank-order list of information privacy concern factors. We consider overall technology characteristics to establish a mutually exclusive set of factors. A Delphi survey, a rigorous data collection method, was deployed to obtain a reliable opinion from the experts and to produce a rank-order list. It, therefore, lends itself well to obtaining a set of universal factors of information privacy concern and its priority. An international panel of researchers and practitioners who have the expertise in privacy and context-aware system fields were involved in our research. Delphi rounds formatting will faithfully follow the procedure for the Delphi study proposed by Okoli and Pawlowski. This will involve three general rounds: (1) brainstorming for important factors; (2) narrowing down the original list to the most important ones; and (3) ranking the list of important factors. For this round only, experts were treated as individuals, not panels. Adapted from Okoli and Pawlowski, we outlined the process of administrating the study. We performed three rounds. In the first and second rounds of the Delphi questionnaire, we gathered a set of exclusive factors for information privacy concern in context-aware personalized services. The respondents were asked to provide at least five main factors for the most appropriate understanding of the information privacy concern in the first round. To do so, some of the main factors found in the literature were presented to the participants. The second round of the questionnaire discussed the main factor provided in the first round, fleshed out with relevant sub-factors. Respondents were then requested to evaluate each sub factor's suitability against the corresponding main factors to determine the final sub-factors from the candidate factors. The sub-factors were found from the literature survey. Final factors selected by over 50% of experts. In the third round, a list of factors with corresponding questions was provided, and the respondents were requested to assess the importance of each main factor and its corresponding sub factors. Finally, we calculated the mean rank of each item to make a final result. While analyzing the data, we focused on group consensus rather than individual insistence. To do so, a concordance analysis, which measures the consistency of the experts' responses over successive rounds of the Delphi, was adopted during the survey process. As a result, experts reported that context data collection and high identifiable level of identical data are the most important factor in the main factors and sub factors, respectively. Additional important sub-factors included diverse types of context data collected, tracking and recording functionalities, and embedded and disappeared sensor devices. The average score of each factor is very useful for future context-aware personalized service development in the view of the information privacy. The final factors have the following differences comparing to those proposed in other studies. First, the concern factors differ from existing studies, which are based on privacy issues that may occur during the lifecycle of acquired user information. However, our study helped to clarify these sometimes vague issues by determining which privacy concern issues are viable based on specific technical characteristics in context-aware personalized services. Since a context-aware service differs in its technical characteristics compared to other services, we selected specific characteristics that had a higher potential to increase user's privacy concerns. Secondly, this study considered privacy issues in terms of service delivery and display that were almost overlooked in existing studies by introducing IPOS as the factor division. Lastly, in each factor, it correlated the level of importance with professionals' opinions as to what extent users have privacy concerns. The reason that it did not select the traditional method questionnaire at that time is that context-aware personalized service considered the absolute lack in understanding and experience of users with new technology. For understanding users' privacy concerns, professionals in the Delphi questionnaire process selected context data collection, tracking and recording, and sensory network as the most important factors among technological characteristics of context-aware personalized services. In the creation of a context-aware personalized services, this study demonstrates the importance and relevance of determining an optimal methodology, and which technologies and in what sequence are needed, to acquire what types of users' context information. Most studies focus on which services and systems should be provided and developed by utilizing context information on the supposition, along with the development of context-aware technology. However, the results in this study show that, in terms of users' privacy, it is necessary to pay greater attention to the activities that acquire context information. To inspect the results in the evaluation of sub factor, additional studies would be necessary for approaches on reducing users' privacy concerns toward technological characteristics such as highly identifiable level of identical data, diverse types of context data collected, tracking and recording functionality, embedded and disappearing sensor devices. The factor ranked the next highest level of importance after input is a context-aware service delivery that is related to output. The results show that delivery and display showing services to users in a context-aware personalized services toward the anywhere-anytime-any device concept have been regarded as even more important than in previous computing environment. Considering the concern factors to develop context aware personalized services will help to increase service success rate and hopefully user acceptance for those services. Our future work will be to adopt these factors for qualifying context aware service development projects such as u-city development projects in terms of service quality and hence user acceptance.