• 제목/요약/키워드: Medical image analysis

검색결과 917건 처리시간 0.043초

An Identification of the Image Retrieval Domain from the Perspective of Library and Information Science with Author Co-citation and Author Bibliographic Coupling Analyses

  • 윤정원;정은경;변지혜
    • 한국문헌정보학회지
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    • 제49권4호
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    • pp.99-124
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    • 2015
  • As the improvement of digital technologies increases the use of images from various fields, the domain of image retrieval has evolved and become a growing topic of research in the Library and Information Science field. The purpose of this study is to identify the knowledge structure of the image retrieval domain by using the author co-citation analysis and author bibliographic coupling as analytical tools in order to understand the domain's past and present. The data set for this study is 245 articles with 8,031 cited articles in the field of image retrieval from 1998 to 2013, from the Web of Science citation database. According to the results of author co-citation analysis for the past of the image retrieval domain, our findings demonstrate that the intellectual structure of image retrieval in the LIS field consists of predominantly user-oriented approaches, but also includes some areas influenced by the CBIR area. More specifically, the user-oriented approach contains six specific areas which include image needs, information seeking, image needs and search behavior, image indexing and access, indexing of image collection, and web image search. On the other hand, for CBIR approaches, it contains feature-based image indexing, shape-based indexing, and IR & CBIR. The recent trends of image retrieval based on the results from author bibliographic coupling analysis show that the domain is expanding to emerging areas of medical images, multimedia, ontology- and tag-based indexing which thus reflects a new paradigm of information environment.

갑상샘 유두암종의 세포진단에서 형태학적 계측의 분석 (Morphometric Analysis for Cytological Diagnosis of Thyroid Papillary Carcinoma)

  • 김종옥;양보성;김혜수;이종민;이동호;신소영;강창석;이혜경
    • 대한세포병리학회지
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    • 제17권2호
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    • pp.116-119
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    • 2006
  • The diagnosis of papillary thyroid cancer is generally based on the findings of intranuclear cytoplasmic inclusions and nuclear grooves. Although anisokaryosis and poikilokaryosis, in papillary thyroid cancer, are not distinct when compared to other cancers, cytological examination can provide useful preoperative information. Our study evaluated the diagnostic role of computer-assisted image analysis for the pre-surgical assessment of papillary thyroid carcinoma. Thyroid aspirates from twenty female patients who were histologically confirmed to have both papillary carcinoma and benign nodules were studied. Different populations of 50 benign cells and 50 malignant cells were analyzed. Five morphometric parameters were selected for analysis: nuclear area, perimeter, maximum length, maximum width and intensity standard variation. The values obtained for papillary carcinomas were higher than the surrounding benign nodules as follows: nuclear area 63.5 vs. 36.1 (p=0.000), nuclear perimeter were 29.4 vs. 22.0 (p=0.000), maximum length 9.6 vs. 7.1 (p=0.000), maximum width 8.2 vs. 6.3 (p=0.000), the ratio between maximal length and maximal width 1.16 vs. 1.13 (p=0.000), the standard variation of intensity 14.9 vs. 15.9 (p=0.101) respectively. Therefore, morphometric information can be helpful for the differential cytological diagnosis of papillary thyroid carcinoma.

현미경 영상 기반 암세포 생존력 관련 표현형 추출 (Microscopic Image-based Cancer Cell Viability-related Phenotype Extraction)

  • 강미선
    • 대한의용생체공학회:의공학회지
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    • 제44권3호
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    • pp.176-181
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    • 2023
  • During cancer treatment, the patient's response to drugs appears differently at the cellular level. In this paper, an image-based cell phenotypic feature quantification and key feature selection method are presented to predict the response of patient-derived cancer cells to a specific drug. In order to analyze the viability characteristics of cancer cells, high-definition microscope images in which cell nuclei are fluorescently stained are used, and individual-level cell analysis is performed. To this end, first, image stitching is performed for analysis of the same environment in units of the well plates, and uneven brightness due to the effects of illumination is adjusted based on the histogram. In order to automatically segment only the cell nucleus region, which is the region of interest, from the improved image, a superpixel-based segmentation technique is applied using the fluorescence expression level and morphological information. After extracting 242 types of features from the image through the segmented cell region information, only the features related to cell viability are selected through the ReliefF algorithm. The proposed method can be applied to cell image-based phenotypic screening to determine a patient's response to a drug.

A Comparison of Deep Reinforcement Learning and Deep learning for Complex Image Analysis

  • Khajuria, Rishi;Quyoom, Abdul;Sarwar, Abid
    • Journal of Multimedia Information System
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    • 제7권1호
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    • pp.1-10
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    • 2020
  • The image analysis is an important and predominant task for classifying the different parts of the image. The analysis of complex image analysis like histopathological define a crucial factor in oncology due to its ability to help pathologists for interpretation of images and therefore various feature extraction techniques have been evolved from time to time for such analysis. Although deep reinforcement learning is a new and emerging technique but very less effort has been made to compare the deep learning and deep reinforcement learning for image analysis. The paper highlights how both techniques differ in feature extraction from complex images and discusses the potential pros and cons. The use of Convolution Neural Network (CNN) in image segmentation, detection and diagnosis of tumour, feature extraction is important but there are several challenges that need to be overcome before Deep Learning can be applied to digital pathology. The one being is the availability of sufficient training examples for medical image datasets, feature extraction from whole area of the image, ground truth localized annotations, adversarial effects of input representations and extremely large size of the digital pathological slides (in gigabytes).Even though formulating Histopathological Image Analysis (HIA) as Multi Instance Learning (MIL) problem is a remarkable step where histopathological image is divided into high resolution patches to make predictions for the patch and then combining them for overall slide predictions but it suffers from loss of contextual and spatial information. In such cases the deep reinforcement learning techniques can be used to learn feature from the limited data without losing contextual and spatial information.

신원 은닉을 위한 두뇌 영상의 무손실 변경 (Lossless Deformation of Brain Images for Concealing Identification)

  • 이효종
    • 정보처리학회논문지B
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    • 제18B권6호
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    • pp.385-388
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    • 2011
  • 디지털 형태로 저장된 의료정보가 네트워크를 통하여 제약 없이 전송될 수 있게 되면서, 환자의 개인정보 관리는 의료 업계에서 중요한 주제로 부각되었다. 현재 두뇌 영상의 의료정보를 보호하는 방법은 환자의 신원을 은닉시키기 위하여 얼굴을 절삭하는 것이다. 그러나 절삭 과정에서 간혹 중요한 두뇌 조직부가 함께 절단되어 탈면 두뇌 영상은 의료 용도로 활용될 수 없게 손상을 입게 된다. 실린더 모양의 마스크를 덧붙임으로써 두뇌 영상의 중요한 모든 정보를 유지하면서 환자의 신원 정보를 은닉시키는 직접적인 방법을 제안하였다. 제안하는 두뇌 영상의 무손실 변경 방법은 중요한 영상정보가 손상되지 않음을 확인하였다. 또한 마스크로 입혀진 두뇌영상의 신원을 확인할 수 없는 사실도 증명되었다.

유방 초음파 영상의 CAD 적용을 위한 Segmentation 알고리즘 제안 (The Proposal of Segmentation Algorithm for the Applying Breast Ultrasound Image to CAD)

  • 구락조;정인성;배재호;최성욱;박희붕;왕지남
    • 산업공학
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    • 제21권4호
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    • pp.394-402
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    • 2008
  • The objective of this paper is to design segmentation algorithm for applying the breast ultrasound image to CAD(Computer Aided Diagnosis). This study is conducted after understanding limits, used algorithm and demands of CAD system by interviewing with a medical doctor and analyzing related works based on a general CAD framework that is consisted of five step-establishment of plan, analysis of needs, design, implementation and test & maintenance. Detection function of CAD is accomplished by Canny algorithm and arithmetic operations for segmentation. In addition to, long computing time is solved by extracting ROI (Region Of Interests) and applying segmentation technical methods based morphology algorithm. Overall course of study is conducted by verification of medical doctor. And validity and verification are satisfied by medical doctor's confirmation. Moreover, manual segmentation of related works, restrictions on the number of tumor and dependency of image resolution etc. was solved. This study is utilized as a support system aided doctors' subjective diagnosis even though a lot of future studies is needed for entire application of CAD system.

MR 영상을 이용한 뇌경색 시기판단과 전이방향에 관한 연구 (A Study on Prediction of the brain infarction period and transition direction using MR image)

  • 하광;정필수;박병래;예수영;김학진;전계록
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1998년도 추계학술대회
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    • pp.267-268
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    • 1998
  • In this paper, we analysis 3 types of magnetic resonance image for determining whether brain infarction period is hyperacute or not. If its peirod is hyperacute, we can predict brain infarction transition direction. We use EPI(Echo Planar Image) for prediction of brain infarction transition direction. EPI is a good image for detecting brain infarction because EPI can detect the moving of water in brain which play an important role in deciding method of medical treatment. We utilize characteristics of 3 type of MRI and their relation in brain infarction patient for determining brain infarction period. By this method, we obtain each period characteristics and predict brain infarction transition direction more accurately comparing past method.

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다산(茶山)의 주역(周易) 해석에 대한 연구 (Study on Dasan's apprehension for I Ching)

  • 임명진;강정수
    • 혜화의학회지
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    • 제13권2호
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    • pp.87-95
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    • 2004
  • The medicine through I-Ching(The Book of Changes, 易經) is a field of the medical science, which studies physiology, pathology and Yin-Yang philosophy. From ancient times so many scholars have studied I Ching and they are divided into two different school. one is the school of Image and Number(象數學派), the other is the school of reason(義理學派). Da-San Jung Yak-Yong(茶山 丁若鏞) is a distinguished scholar in the I-Ching study, and he had a unique opinion in the analysis about sentences of I Ching. He has done his best to make 'Image and Number(象數)' harmonize with reason(義理). I Ching is the book about changes, which includes everything like natural phenomena, human body and mind. So we can understand human physiology and pathology through I Ching. But it's important to understand it was organized by symbols. The main symbols are Ba-Gua(八卦), 12 Bi-Gua, Zai-Ruo-zhi-Gua(再閏之卦), 50 Yan-Gua(50衍卦) and these symbols originated from the imagess of the four seasons. The image of 12 Bi-Gua coincide with 12 jing-lao(經絡), the images of Zai-Ruo-zhi-Gua(再閏之卦) coinside with Ren-mai(任脈), Du-mai(督脈). 12 Bi-Gua and Zai-Ruo-zhi-Gua(再閏之卦) are fundamental stuffs, on the other hand 50 Yan-Gua(50衍卦) is an application of every phenomenon.

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2017년 이후 스포츠매장의 브랜드이미지와 VMD 전략 (Brand Image and VMD Strategy of Sports Stores in Korea)

  • 서정화;김화경;김종진;윤명길
    • 유통과학연구
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    • 제15권11호
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    • pp.83-93
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    • 2017
  • Purpose - The study aims to analyze the VMD(Visual Merchandising) perception factors in recent sporting goods store and clarify the effect of each VMD perception factors on brand image, satisfaction, and customer revisit intention. The VMD perception factors play an important role in attracting and actually inducing sales to the visiting customers. It has investigated the effect of VMD perception on customer satisfaction and revisit intention. It is expected that the company's marketing strategy with VMD will be differentiated and competitive in sports item stores, brand image enhancement, customer retention, and acquisition. Research design, data, and methodology - In order to verify the hypotheses of this study, a total of 380 questionnaires had been distributed. 360 respondents were used in the final analysis excluding 20 respondents' incomplete answers. The SPSS 18.0 program was used and the data analysis was conducted for the demographic characteristics and distribution behavior. Principal Components Analysis was used for the common factor extraction for validity analysis, and factor analysis was conducted to verify such as validity in brand image or brand attitude. As for Multiple regression analysis, was performed to verify and in the research model, and in and , the mediation was defined through the Sobel Test in order to verify the brand image mediating effects on VMD, store satisfaction, and revisit inquiry of sports store. Results - Qualitative research shows that VMD sub-variables such as aesthetic, fitness, and functional convenience influence store satisfaction and revisit intention. As a result of analyzing the mediating effect of the brand image, the more VMD is strengthened, the more brand image is improved and store satisfaction is also increased. Conclusions - VMD enhancement requires a VMD strategy aligned with the company's management policies and objectives, a visual directing and consistent concept that delivers a strong message to customers. The customer actual purchasing behavior is a combination of various factors such as sports item stores' interior design, display, advertisement promotion like POP(Point of Purchase), salespersons and their service quality, so that the VMD image and the brand image must be consistent and a unique strategic plan is required.