• Title/Summary/Keyword: classification skin

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Hyperspectral Image Fusion for Tumor Detection (초분광 영상 융합을 이용한 종양인식)

  • Xu Cheng-Zhe;Kim In-Taek
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.43 no.4 s.310
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    • pp.11-20
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    • 2006
  • This paper presents a method for detecting tumors on chicken carcasses by fusion of hyperspectral fluorescence and reflectance images. Classification of normal skin and tumor is performed by the image obtain 어 from optimal band ratio which minimizes the overlapping area of PDFs for normal skin and tumor. This method yields four feature images, each of them represents the ratio of two intensity values from a pixel. Classification is achieved by applying ISODATA to each pixel from the feature images. For the analysis of reflectance image, band selection method is proposed based on the information quantity, many effective features are acquired for the classification by defining the linear transformation selecting the projection axis, accordingly, accurate interpretation of images is possible in the reflectance image and automatic feature selection method is realized. Feature images from reflectance images are also classified by ISODATA and combined with the result from fluorescence images. Experimental result indicates that improved performance in term of reducing false detection rate is observed.

A Review on Patterns and Classification Criteria of Psoriasis by analyzing Chinese Theses (중국 논문에 나타난 건선의 변증 분석 및 변증체계에 대한 고찰)

  • Cho, Eun-Chai;Kim, Kyu-Seok
    • The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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    • v.33 no.2
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    • pp.112-129
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    • 2020
  • Objectives : The aim of this study is to explore the types of pattern identification (PI, 辨證) and the differential points of PI used for the treatment of psoriasis in Traditional Chinese Medicine (TCM) based on the Chinese references and to provide the evidences applying PI for the treatment of psoriasis in clinical practice. Methods : This study extracted patterns of psoriasis through database CNKI (China National Knowledge Infrastructure) and analysis the patterns and classification criteria of the patterns. Those examined in the study are dermal symptoms, general symptoms, formula and herbs which are different depending on the patterns. Results : Total 60 studies were selected and 44 pattern types were extracted from them. We categorized the main pattern types on psoriasis used in TCM as 'blood-heat syndrome(BHS, 血熱證)', blood-stasis syndrome(BSS, 血瘀證), and 'blood-dryness syndrome(BDS, 血燥證)', 'dampness-heat syndrome(DHS, 濕熱證)' and 'yang-deficiency syndrome(YDS, 陽虛證)'. Among these patterns, BHS was the most common. In TCM, the pattern of BHS tended to have skin symptoms and signs related to inflammatory erythema and heat. Both BSS and BDS were characterized by long disease duration and poor healing. In addition, DHS tended to have the skin symptoms and signs such as oozing and severe itching. The symptoms and signs related to coldness mainly showed in YDS. For PI criteria, 'qi-blood-essence criteria(氣血津液辨證)' and 'eight-doctrine criteria(八鋼辨證) are commonly used. Conclusions : Our findings show that each PI on psoriasis in TCM has different characteristics related to dermal and general symptoms or signs. Further studies are needed to develop the diagnostic tool of PI on psoriasis reflecting on clinical practices in Korean Medicine by referring to the findings of this study about PI on psoriasis in TCM.

A Study on Nursing Diagnoses and Nursing Intervention Classification -focused on Home Health Care Clients- (간호진단과 중재분류에 관한 조사연구 -가정 간호 대상자를 중심으로-)

  • 김조자;최애규;김기란;송희영
    • Journal of Korean Academy of Nursing
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    • v.29 no.1
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    • pp.72-83
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    • 1999
  • The purpose of this study was to classify, from collected home health care records data, nursing diagnoses according to the NANDA system and nursing interventions according to the NIC system, and to link nursing interventions to nursing diagnoses. For this study, 101 home health care records of clients seen between September, 1994 and November, 1996 at Yonsei Medical Center, Seoul, were analyzed. The results of this study are summarized as follows : 1. The most frequent nursing diagnoses were ‘Risk for infection’ and ‘Altered nutrition : Less than body requirements’, then ‘Impaired skin intergrity’ and ‘Ineffective airway clearance’ in the Exchange pattern of NANDA nine human response patterns. 2. The most frequent nursing interventions were the interventions in the Physiological : Complex domain, there were 690(50.7%) interventions among a total 1347 interventions. This results corresponds to Yom, Young Hee(1995)’s research, both Korean and U.S. nurses used the interventions in the Physiological : Complex do main most often on a daily basis. And respiratory nursing interventions were most frequent because 32.7% of the subjects were respiratory patients. 3. The next step was to link the nursing interventions to nursing diagnoses. The most frequent nursing diagnosis was ‘Risk for infection’ and 19 interventions for ‘Risk for infection’ were used 267 times. Then 14 interventions for ‘Impaired skin integrity’ were used 258 times, 12 interventions for ‘Ineffrective airway clearance’ were used 193 times, 12 interventions for ‘Altered nutrition : Less than body requirements’ were used 122 times, 10 interventions for ‘Activity intolerance’ were used 75 times, and 11 interventions for ‘Knowledge deficit’ were used 52 times. 4. The use of standardized classification in the areas of nursing diagnoses and nursing interventions facilitates clinical decision making and prompt nursing activity, and so enhances the effectiveness of nursing care.

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Skin Disease Classification Technique Based on Convolutional Neural Network Using Deep Metric Learning (Deep Metric Learning을 활용한 합성곱 신경망 기반의 피부질환 분류 기술)

  • Kim, Kang Min;Kim, Pan-Koo;Chun, Chanjun
    • Smart Media Journal
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    • v.10 no.4
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    • pp.45-54
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    • 2021
  • The skin is the body's first line of defense against external infection. When a skin disease strikes, the skin's protective role is compromised, necessitating quick diagnosis and treatment. Recently, as artificial intelligence has advanced, research for technical applications has been done in a variety of sectors, including dermatology, to reduce the rate of misdiagnosis and obtain quick treatment using artificial intelligence. Although previous studies have diagnosed skin diseases with low incidence, this paper proposes a method to classify common illnesses such as warts and corns using a convolutional neural network. The data set used consists of 3 classes and 2,515 images, but there is a problem of lack of training data and class imbalance. We analyzed the performance using a deep metric loss function and a cross-entropy loss function to train the model. When comparing that in terms of accuracy, recall, F1 score, and accuracy, the former performed better.

Classification of Sasang Constitution Taeumin by Comparative of Speech Signals Analysis (음성 분석 정보값 비교를 통한 사상체질 태음인의 분류)

  • Kim, Bong-Hyun;Lee, Se-Hwan;Cho, Dong-Uk
    • The KIPS Transactions:PartB
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    • v.15B no.1
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    • pp.17-24
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    • 2008
  • This paper proposes Sasang constitution classification through speech signals analysis values and comparison. For this, this paper wishes to propose Taeumin classification method of output values signals that comes out speech signal analysis to connect with process classification of Soeumin through skin diagnosis by first step in the whole system configuration to provide for objective index of Sasang constitution. First of all, these characteristic of voices wish to extract phonetic elements that each Sasang constitution groups' clear features. Also, we wish to classify Taeumin through constitution groups' difference and similarity on the basis of results value. Finally, the effectiveness of this method is verified through the experiments.

Review of Acupuncture and Related Treatments and Classification of Hyperpigmentation Disorders in Traditional Medicine (과색소침착질환에 대한 침구의학적 처치 및 분류체계에 대한 고찰)

  • Kang, Ki Wan;Kim, Eui Byeol;Kim, Min Ji;Jang, In Soo
    • Journal of Acupuncture Research
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    • v.33 no.1
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    • pp.69-77
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    • 2016
  • Objectives : The objective of this study is to review external approaches using acupuncture and related treatments of hyperpigmentation disorders and their classification in traditional medicine. Methods and Results : Hyperpigmentation was recorded for the first time in Treatise on the Pathogenesis and Manifestations of All Diseases published in 610 A.D. This suggests that the symptom has already been recognized as an independent disease in East Asia for more than 1,400 years. Over the course of several centuries, there has been a significant evolution in the traditional treatments for hyperpigmentation. There are many different types of therapy, including body acupuncture, intradermal acupuncture, ear acupuncture, ear acupressure, blood-letting treatment, pharmacopuncture, plum-blossom needle therapy, burning acupuncture therapy, moxibustion, and guasha. In addition, the traditional classification of hyperpigmentation has been changing shape. However, no attempts have been made to establish the academic linkage between the modern classification of hyperpigmentation disorders and the traditional one, on account of different concepts and names of the ailment. This study was designed in an attempt to identify the linkage of the categorization of the Korean Standard Classification of Disease (KCD) and the traditional classification. Conclusions : Through this literature review, we found that there has been a significant evolution in the treatment of hyperpigmentation disorders in East Asia. Traditional medical treatment for skin disease, including hyperpigmentation, is expected to be further developed with the advancement of science and technology.

Elliptical Clustering with Incremental Growth and its Application to Skin Color Region Segmentation (점증적으로 증가하는 타원형 군집화 : 피부색 영역 검출에의 적용)

  • Lee Kyoung-Mi
    • Journal of KIISE:Software and Applications
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    • v.31 no.9
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    • pp.1161-1170
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    • 2004
  • This paper proposes to segment skin color areas using a clustering algorithm. Most of previously proposed clustering algorithms have some difficulties, since they generally detect hyperspherical clusters, run in a batch mode, and predefine a number of clusters. In this paper, we use a well-known elliptical clustering algorithm, an EM algorithm, and modify it to learn on-line and find automatically the number of clusters, called to an EAM algorithm. The effectiveness of the EAM algorithm is demonstrated on a task of skin color region segmentation. Experimental results present the EAM algorithm automatically finds a right number of clusters in a given image without any information on the number. Comparing with the EM algorithm, we achieved better segmentation results with the EAM algorithm. Successful results were achieved to detect and segment skin color regions using a conditional probability on a region. Also, we applied to classify images with persons and got good classification results.

A Class and Cosmetics of Make-up in Make-up Deisgn (메이크업 디자인에서 메이크업 종류)

  • Shin, Seong-Yoon;Shin, Kwang-Sung;Lee, Hyun-Chang;Jin, Chan-Yong;Rhee, Yang-Won
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.144-145
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    • 2012
  • Make-up is the act of protecting the body and face, or a beautifully decorating by covering the shortcomings. In this paper, classification and type of makeup was newly organized to suit the present day. And the meaning of the new make-up were evaluated. Makeup helps protect skin from external changes. It gives the beauty function to hide defects of the skin and make it beautiful. Thus, it allows to have a social life actively and aggressively given the confidence to look.

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Relationship between Nurse Staffing and Changes in Pain Level, Infection Severity, and Tissue Integrity: Skin and Mucous Membranes

  • Moon, Mi-Kyung
    • The Korean Journal of Rehabilitation Nursing
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    • v.14 no.1
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    • pp.62-69
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    • 2011
  • Purpose: The study assessed whether nurse staffing was associated with 3 nursing sensitive outcomes used in intensive care unit (ICU) nursing care plans. Methods: This study was a retrospective and descriptive study using clinical data extracted from the data warehouse of a large acute care hospital in the Midwest. One-way analysis of variance was used to analyze the records of 578 ICU patients admitted from March 25 to May 31, 2010. Results: 79 Nursing Outcomes Classification (NOC) outcomes were used in the nursing care plans. The 3 most commonly used NOC outcomes (Pain Level, Infection Severity, and Tissue Integrity: Skin and Mucous Membranes) were analyzed to determine their relationship to nurse staffing. As a nurse staffing ratio, the skill mix of nursing caregivers ranged from 0.74 to 1 with an average of 0.90. This skill mix of nursing caregivers significantly differed among the changes in Infection Severity scores. However, the mean difference was only 0.02. Conclusion: The results did not support that greater nurse staffing was associated with better outcomes. More research is still needed to determine the usefulness of Pain Level, Infection Severity, and Tissue Integrity: Skin and Mucous Membranes in evaluating the impact of nurse staffing.

Automatic Face Identification System Using Adaptive Face Region Detection and Facial Feature Vector Classification

  • Kim, Jung-Hoon;Do, Kyeong-Hoon;Lee, Eung-Joo
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.1252-1255
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    • 2002
  • In this paper, face recognition algorithm, by using skin color information of HSI color coordinate collected from face images, elliptical mask, fratures of face including eyes, nose and mouth, and geometrical feature vectors of face and facial angles, is proposed. The proposed algorithm improved face region extraction efficacy by using HSI information relatively similar to human's visual system along with color tone information about skin colors of face, elliptical mask and intensity information. Moreover, it improved face recognition efficacy with using feature information of eyes, nose and mouth, and Θ1(ACRED), Θ2(AMRED) and Θ 3(ANRED), which are geometrical face angles of face. In the proposed algorithm, it enables exact face reading by using color tone information, elliptical mask, brightness information and structural characteristic angle together, not like using only brightness information in existing algorithm. Moreover, it uses structural related value of characteristics and certain vectors together for the recognition method.

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