본문
| 교실(과) | 영상의학 |
|---|---|
| 연구(전공)분야 | 자기공명영상학, 의료영상인공지능, 대사영상학 |
| 이메일 | ipark@jnu.ac.kr |
| 홈페이지 | sites.google.com/view/ilwoopark |
학력
- 2004 미국 UC Berkeley 대학 졸업 (BS in Bioengineering, University of California Berkeley)
- 2010 미국 UC Berkeley 박사 졸업 (PhD in Bioengineering, University of California Berkeley/San Francisco Joint Graduate Group)
경력 및 해외 연수
- 2017-현재 전남대학교 의과대학 영상의학과 조교수 (Assistant Professor, Chonnam National University)
- 2015-2017 미국 UCSF 연구교수 (Assistant Professional Researcher, Department of Radiology and Biomedical Imaging, University of California San Francisco)
- 2011-2015 미국 UCSF 박사후 연구원 (Postdoctoral Scholar, Department of Radiology and Biomedical Imaging, University of California San Francisco)
연구소개
■ 지도교수 : 박일우■ https://sites.google.com/view/ilwoopark
■ LABMI (Laboratory for Advanced BioMedical Imaging) 연구실은 최첨단 의료영상과 인공지능 기술의 융합 연구를 수행하고 있습니다. 기계학습 및 딥러닝 알고리즘을 이용하여 헬스케어 분야에서 환자 진료에 사용할 수 있는 인공지능 의료 보조 시스템 개발을 수행하고 있습니다. 전남대학교병원의 환자 빅데이터를 이용하여 영상의학과, 신경과, 신장내과, 순환기내과 등 전남대학교병원 교수진들과 활발한 공동연구를 진행하고 있습니다.
■ The goal of our research is to advance our understanding of diseases using advanced imaging methods combined with artificial intelligence technology. Our laboratory has two main research focus: 1) Development of machine learning/deep learning-based methods for application to clinical data, including medical imaging and EMR (electronic medical record), 2) Development of new imaging techniques and imaging biomarkers using magnetic resonance imaging (MRI)
프로젝트 현황
Recurrent Residual Convolutional Neural Network을 이용한 뇌졸중 환자 치료법 자동 진단법 개발 (Development of automatic ASPECTS scoring system for stroke patients using Recurrent Residual Convolutional Neural Network) |
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2단개 딥러닝 알고리즘을 이용해 유방암 환자의 자기공명영상에서 invasive vs non-invasive 유방암 감별 (Classification of invasive vs noninvasive breast cancer using MRI of breast cancer patients using 2 types of Deep learning algorithms) |
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Radiomics와 기계학습을 이용한 대장암 환자의 흉부 CT 영상에서 폐전이암과 폐원발암 구별 (Classification of solitary lung metastasis vs primary lung cancer in chest CT of colon cancer patients using a combination of Radiomics and Machine learning approach) |
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유방암 환자의 자기공명영상(MRI)에서 추가로 발견된 병변을 Radiomics와 기계학습을 이용하여 악성종양(malignancy)와 양성병변(benign lesion) 구별 (Utility of radiomics analysis for classification of additional MR-detected lesions in patients with breast cancer) |
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딥러닝을 이용한 134개 피부암 진단법 개발 (Development of deep learning system for the classification of 134 skin lesions) |
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과분극화 탄소-13 이미징 방법을 이용한 뇌종양 방사선 괴사와 뇌종양 재발 조직 구별 (Differentiating Radiation Necrosis from Brain Tumor Using Hyperpolarized Carbon-13 MR Metabolic Imaging) |
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수상경력
- 2015 Magna Cum Laude Merit Award, International Society for Magnetic Resonance in Medicine
- 2014 Bruce Hasegawa Excellence in Biomedical Research Award
- 2013-2015 NIH T32 Training Grant in UCSF Translational Brain Tumor Research
- 2013 Junior Fellow, International Society for Magnetic Resonance in Medicine
- 2013 Magna Cum Laude Merit Award, International Society for Magnetic Resonance in Medicine
- 2012 Surbeck Scholar Award from Margaret Hart Surbeck Foundation: 1st place
- 2011-2013 American Brain Tumor Association Basic Research Fellowship
- 2010 World Molecular Imaging Congress Annual Meeting Poster Award
- 2008-2009 University of California Cancer Research Coordinating Committee Fellowship
- 2009 Surbeck Scholar Award from Margaret Hart Surbeck Foundation: 3rd place
- 2008 Young Investigator Award Finalist, World Molecular Imaging Congress Annual Meeting
- 2008 University of California Discovery Grant Travel Award
- 2006-2007 Graduate Dean's Health Science Fellowship, University of California San Francisco
- 2005 ISMRM Poster Award - Spectroscopy category
- 2001-2002 Dean's Honors List, University of California Berkeley
연구업적 및 저서
- <최근 3년간 연구논문>
- 1. Gordon JW, Chen HY, Autry A, Park I, Van Criekinge M, Mammoli D, Milshteyn E, Bok R, Xu D, Li Y, Aggarwal R, Chang S, Slater JB, Ferrone M, Nelson S, Kurhanewicz J, Larson PEZ, Vigneron DB. Translation of Carbon-13 EPI for hyperpolarized MR molecular imaging of prostate and brain cancer patients. Magn Reson Med. 2018 Oct 30. doi: 10.1002/mrm.27549. [Epub ahead of print]
- 2. Park I, Lupo JM, Nelson SJ. Correlation of Tumor Perfusion Between Carbon-13 Imaging with Hyperpolarized Pyruvate and Dynamic Susceptibility Contrast MRI in Pre-Clinical Model of Glioblastoma. Mol Imaging Biol. 2018 Sep 17. doi: 10.1007/s11307-018-1275-y. [Epub ahead of print]
- 3. Chen HY, Larson PEZ, Gordon JW, Bok RA, Ferrone M, van Criekinge M, Carvajal L, Cao P, Pauly JM, Kerr AB, Park I, Slater JB, Nelson SJ, Munster PN, Aggarwal R, Kurhanewicz J, Vigneron DB. Technique development of 3D dynamic CS-EPSI for hyperpolarized 13 C pyruvate MR molecular imaging of human prostate cancer. Magn Reson Med. Magn Reson Med. 2018 Nov;80(5):2062-2072.
- 4. Han SS, Lim W, Kim MS, Park I, Park GH, Chang SE. Interpretation of the Outputs of Deep Learning Model trained with Skin Cancer Dataset. J Invest Dermatol. J Invest Dermatol. 2018 Oct;138(10):2275-2277.
- 5. Park I, Larson PEZ, Gordon JW, Carvajal L, Chen HY, Bok R, Van Criekinge M, Ferrone M, Slater JB, Xu D, Kurhanewicz J, Vigneron DB, Chang S, Nelson SJ. Development of Methods and Feasibility of Using Hyperpolarized Carbon-13 Imaging Data for Evaluating Brain Metabolism in Patient Studies. Magn Reson Med. 2018 Sep;80(3):864-873.
- 6. Autry AW, Hashizume R, James CD, Larson PEZ, Vigneron DB, Park I. Measuring Tumor Metabolism in Pediatric Diffuse Intrinsic Pontine Glioma Using Hyperpolarized Carbon-13 MR Metabolic Imaging. Contrast Media Mol Imaging. 2018 Jul 30;2018:3215658. doi: 10.1155/2018/3215658. eCollection 2018.
- 7. Han SS, Kim MS, Lim W, Park GH, Park I, Chang SE. Classification of the clinical images for benign and malignant cutaneous tumors using a deep learning algorithm. J Invest Dermatol. J Invest Dermatol. 2018 Jul;138(7):1529-1538
- 8. Han SS, Lim W, Park GH, Kim MS, Na JI, Park I, Chang SE. Deep neural networks show an equivalent and often superior performance to dermatologists in onychomycosis diagnosis: Automatic construction of onychomycosis datasets by region-based convolutional deep neural network. PloS One. 2018 Jan 19;13(1):e0191493
- 9. Nelson SJ, Kadambi AK, Park I, Li Y, Crane J, Olson M, Molinaro A, Roy R, Butowski N, Cha S, Chang S. Association of early changes in 1H MRSI parameters with survival for patients with newly diagnosed glioblastoma receiving a multimodality treatment regimen. Neuro Oncol. 2017 Mar 1;19(3):430-439.
- 10. Park I, von Morze C, Lupo JM, Ardenkjaer-Larsen JH, Kadambi A, Vigneron DB, Nelson SJ. Investigating Tumor Perfusion by Hyperpolarized 13C MRI with Comparison to Conventional Gadolinium Contrast-Enhanced MRI and Pathology in Orthotopic Human GBM Xenografts. Magn Reson Med. 2017 Feb;77(2):841-847.
- 11. ParkI, Nelson SJ, Talbott JF. In Vivo Monitoring of Rat Spinal Cord Metabolism Using Hyperpolarized Carbon-13 MR Spectroscopic Imaging. AJNR Am J Neuroradiol. 2016 Dec;37(12):2407-2409.
- 12. Cao P, Shin P, Park I, Najac C, Marco-Rius I, Vigneron DB, Nelson SJ, Ronen SM, Larson PEZ. Accelerated High Bandwidth MR Spectroscopic Imaging Using Compressed Sensing. Magn Reson Med. 2016 Aug;76(2):369-79.
- 13. Cao P, Zhang X, Park I, Najac C, Nelson SJ, Ronen S, Larson PEZ. 1H-13C Independently Tuned RF Surface Coil Applied for In vivo Hyperpolarized MRI. Magn Reson Med. 2016 Nov;76(5):1612-1620.
- 14. Li Y, Park I, Nelson SJ. Imaging tumor metabolism using in vivo magnetic resonance spectroscopy. Cancer J. 2015 Mar-Apr;21(2):123-8.
- 15. Park I, Mukherjee J, Ito M, Chaumeil MM, Jalbert LE, Gaensler K, Ronen SM, Nelson SJ, Pieper RO. Changes in pyruvate metabolism detected by magnetic resonance imaging are linked to DNA damage and serve as a sensor of temozolomide response in glioblastoma cells. Cancer Res. 2014 Dec 1;74(23):7115-24.
- 16. Park I, Larson PEZ, Tropp JL, Carvajal L, Reed G, Bok R, Robb F, Bringas J, Kells A, Pivirotto P, Bankiewicz K, Vigneron DB, Nelson1 SJ. Dynamic Hyperpolarized Carbon-13 Metabolic MR Imaging of Non-Human Primate Brain. Magn Reson Med. 2014 Jan;71(1):19-25.
- <연구비 수주>
- 2017-20 Basic Science-Engineering Grant, Korean Ministry of Science, and ICT (Role: PI)
- 2018-20 Biomedical Academic Research Grant, Chonnam National University Hospital Biomedical Research Institute (Role: PI)
- 2017-18 American Brain Tumor Association Discovery Grant
- 2017 The Research Evaluation and Allocation Committee grant (Role: PI)
- 2015-17 Kure It Cancer Research & Helen Diller Cancer Center (Role: Co-PI)
- 2013-15 NIH T32 Training Grant in Translational Brain Tumor Research (Role: PI)
- 2011-13 UCSF Radiology Departmental Seed Grant Award (Role: PI)
- 2011-13 American Brain Tumor Association Basic Research Fellowship (Role: PI)
학회활동
- 국제자기공명의과학회 (International Society for Magnetic Resonance in Medicine) 회원, Junior Fellow
- 한국자기공명의과학회 (Korean Society for Magnetic Resonance in Medicine) 회원, 국제협력이사
- 세계분자영상학회 (Society of Molecular Imaging) 회원