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모바일 디바이스를 이용한 환자 맞춤형 이미지 기반 황달 진단
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 선우명훈 | - |
| dc.contributor.author | 최성빈 | - |
| dc.date.accessioned | 2018-11-08T08:28:51Z | - |
| dc.date.available | 2018-11-08T08:28:51Z | - |
| dc.date.issued | 2018-08 | - |
| dc.identifier.other | 27809 | - |
| dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/14187 | - |
| dc.description | 학위논문(석사)--아주대학교 일반대학원 :전자공학과,2018. 8 | - |
| dc.description.tableofcontents | Table of Contents Abstract List of Figures List of Tables List of Abbreviations I. Introduction 1 II. Patch based white balance 2 III. Image based jaundice monitoring 10 IV. Experimental Results 13 V. Conclusion 18 Bibliography 19 | - |
| dc.language.iso | eng | - |
| dc.publisher | The Graduate School, Ajou University | - |
| dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
| dc.title | 모바일 디바이스를 이용한 환자 맞춤형 이미지 기반 황달 진단 | - |
| dc.title.alternative | Image-based patient-personalized diagnosis of jaundice using mobile devices | - |
| dc.type | Thesis | - |
| dc.contributor.affiliation | 아주대학교 일반대학원 | - |
| dc.contributor.alternativeName | Choi Seong Bin | - |
| dc.contributor.department | 일반대학원 전자공학과 | - |
| dc.date.awarded | 2018. 8 | - |
| dc.description.degree | Master | - |
| dc.identifier.localId | 887759 | - |
| dc.identifier.uci | I804:41038-000000027809 | - |
| dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/common/orgView/000000027809 | - |
| dc.subject.keyword | Mobile health | - |
| dc.subject.keyword | Jaundice diagnosis | - |
| dc.subject.keyword | Total bilirubin | - |
| dc.subject.keyword | Smart device | - |
| dc.subject.keyword | Health care application | - |
| dc.description.alternativeAbstract | Jaundice is a yellow discoloration of the skin, mucous membranes, and sclera caused by increased amounts of total bilirubin in the blood. Patients frequently visiting to the hospital to monitor jaundice and measuring the total bilirubin values are uncomfortable. To solve these problems, this paper proposes an image-based diagnostic method of jaundice for mobile devices. The proposed algorithm extracts the scleral region by applying the Otsu method to the patient image captured by mobile devices, performs preprocessing to correct image and removes the light reflection in the scleral region. Then the proposed algorithm based on the HSV color model is used to obtain image feature values that show the progression of jaundice. Simulation results have been obtained by applying the proposed method to image history of jaundice patients, which show that total bilirubin values are well matched with the image feature values. | - |
- Appears in Collections:
- Graduate School of Ajou University > Department of Electronic Engineering > 3. Theses(Master)
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