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정지원,서고훈,오아름,진희경,배재성,김구환,유한욱,이범희,Jung, Jiwon,Seo, Go Hun,Oh, Arum,Jin, Hee Kyung,Bae, Jae-Sung,Kim, Gu-Hwan,Yoo, Han-Wook,Lee, Beom Hee 대한유전성대사질환학회 2018 대한유전성대사질환학회지 Vol.18 No.1
C형 Niemann-Pick 병은 NPC1 및 NPC2 유전자의 돌연변이로 인해 발생하며 상염색체 열성으로 유전된다. 신생아 간염 및 간비비대로 발현하며 안구의 수직운동 마비, 조화운동불능, 근육긴장이상, 경련 등의 신경학적 증상이 서서히 발현 하는 것을 특징으로 한다. 저자들은 복부 팽만 및 심한 비장비대로 입원한 3세 남아에서 간 조직 검사 및 유전자 검사, 섬유모세포의 Filipin 염색으로 확진 된 C형 Niemann-Pick 병 1례를 보고하는 바이다. Niemann Pick type C disease (NPC) is an inherited progressive neurodegenerative disorder, due to defects of intracellular lipid trafficking and storage. Hepatosplenomegaly may prevail, while progressive neurodegenerative symptoms such as cerebellar involvement, dystonia, vertical supranuclear ophthalmoplegia, cataplexy, and eventually seizures starting at juvenile or late infantile period may accompany after normal early development. Here we describe a 3-year-old Korean boy with NPC who presented with splenomegaly at age 3. Liver biopsy showed characteristic foamy cell stained by periodic acid-schiff, and molecular analysis for NPC1 identified the compound heterozygous mutations, novel mutation of c.1631G>A (p.Trp544Ter) and c.2662C>T (p. Pro888Ser) as a known mutation. Filipin was strongly stained with unesterified cellular cholesterol in the patient's skin fibroblasts. The patient has received migulstat since age 3 years and his long-term outcome is needed to be observed.
정지원(Jung, Jiwon),김현정(Kim, Hyunjeong) 한국실내디자인학회 2010 한국실내디자인학회논문집 Vol.19 No.1
The objective of this study is to investigate the difference between the standard ‘design guideline’ in barrier free laws for the disabled and disabled’s real experience in public convenient facilities. It is mainly focused on accessibility by the disabled people who use an electric motion wheel chair, a wheel chair and crutches as well as a visual impaired person in the public resident centers. For this purpose, four resident centers in Busan have been selected as the objects of investigation. We observed and video recorded the disabled people with various handicaps to access and use facilities in four resident centers, and interviewed them afterwards. We found out problems from the perspective of the disabled and figured out the difference between barrier free laws and the disabled’s real experience. The research result is as follow. First, it is important to make the arrangement of public convenient facilities according to the flow of the user’s movements. Second, it is necessary to provide better conditions for the disabled to access the public toilet easily and conveniently. Third, it is essential for public convenient facilities to be more strictly controlled by regulations. Fourth, we need to make better standards that could reflect real experiences of various disabled users. Fifth, we need to keep providing the best follow-up service for the disabled in terms of using public convenient facilities safely. This study can contribute for designers to understand specific users through their experiences and suggest improvement ideas for better public convenient Facilities.
Unsupervised Liver Segmentation using Domain Adaptation in MRI
Jiwon Jung(정지원),Ehwa Yang(양이화),Woo Kyoung Jeong(정우경),Kyoung Doo Song(송경두),Jae-Hun Kim(김재훈) 한국통신학회 2022 한국통신학회 학술대회논문집 Vol.2022 No.2
Liver segmentation is an essential procedure in Computer-Aided Diagnosis (CAD), surgery, and volume measurement for radiotherapy. But it is still a challenging task to extract liver tissue parenchyma due to nearby organs with similar intensities. When we segment the liver using supervised deep learning, fully-annotated datasets are needed. However, it is hard to obtain well-annotated labels because of their diverse appearances such as size and shape. Also, it takes expensive costs for labeling. In this paper, we performed unsupervised liver segmentation in unlabeled Magnetic Resonance Imaging (MRI) datasets using deep learning. To generate labels of MRI, the domain adaptation technique is applied with CT images containing well-annotated labels. We trained the segmentation model with the MRI dataset which is transferred from CT images and evaluated the model on real MRI datasets. The performance of our model shows 88% dice similarity coefficient accuracy. This study could be one of the solutions to handle the difficulty to train deep learning models with unlabeled datasets.
영상 및 레이저데이터 융합을 통한 실도로 자율주행 차량 개발
정지원(Jiwon Jung),이웅희(Woonghui Lee),정석우(Seokwoo Jung),오현찬(Hyeonchan Oh),홍준(Jun Hong),유하람(Haram You),심현철(Hyunchul Shim) 한국자동차공학회 2016 한국자동차공학회 부문종합 학술대회 Vol.2016 No.5
자율주행 자동차는 차량에 장착된 센서들을 활용하여 운전자의 개입없이 실도로를 주행하는 차이다. 자율주행 자동차는 자차 위치를 정확히 인식하여 주어진 경로를 추종하는 것이 중요하다. 기존의 연구에서는 복잡한 3차원 지도를 생성하여 자차 위치를 인식하거나 고정밀 GPS를 활용하여 자차 위치를 인식하였다. 본 연구에서는 저가의 GPS와 차량의 센서를 활용하여 자율항법 시스템을 구성하고 GPS의 신호가 약한 도심자율주행을 위해 도로 경계 인식과 차선 인식 시스템을 구성하였고 서울 도심 자율주행을 통해 검증하였다.