Laboratory for Advanced BioMedical Imaging

Center for AI in Medical Imaging Research

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)

Ilwoo Park, PhD

Associate Professor, Chonnam National University

Department of Artificial Intelligence Convergence, College of Engineering

Department of Radiology, College of Medicine

Education

  • BA, University of California Berkeley

  • PhD, University of California Berkeley

Email: ipark@chonnam.edu, ipark@jnu.ac.kr


Read more about Ilwoo Park's Profile in English or Korean

Selected Publications

  1. Lee HJ, Nguyen AT, Ki SY, Lee JE, Do LN, Park MH, Lee JS, Kim HJ, Park I, Lim HS. Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning. Front Oncol. 2021;11:744460. doi: 10.3389/fonc.2021.744460.

  2. Lee SJ, Park I, Talbott JF, Gordon J. Investigating the Feasibility of In Vivo Perfusion Imaging Methods for Spinal Cord Using Hyperpolarized [13C]t-Butanol and [13C,15N2]Urea. Mol Imaging Biol. 2021 Nov 15;. doi: 10.1007/s11307-021-01682-1. [Epub ahead of print]

  3. Park I, Kim S, Pucciarelli D, Song J, Choi JM, Lee KH, Kim YH, Jung S, Yoon W, Nakamura JL. Differentiating Radiation Necrosis from Brain Tumor Using Hyperpolarized Carbon-13 MR Metabolic Imaging. Mol Imaging Biol. 2021 Jun;23(3):417-426. doi: 10.1007/s11307-020-01574-w.

  4. Do LN, Baek BH, Kim SK, Yang HJ, Park I, Yoon W. Automatic Assessment of ASPECTS Using Diffusion-Weighted Imaging in Acute Ischemic Stroke Using Recurrent Residual Convolutional Neural Network. Diagnostics (Basel). 2020 Oct 9;10(10). doi: 10.3390/diagnostics10100803.

  5. Han SS, Park I, Eun Chang S, Lim W, Kim MS, Park GH, Chae JB, Huh CH, Na JI. Augmented Intelligence Dermatology: Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders. J Invest Dermatol. 2020 Sep;140(9):1753-1761. doi: 10.1016/j.jid.2020.01.019.

  6. 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. doi: 10.1002/mrm.27077.

  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. 2018 Jul;138(7):1529-1538. doi: 10.1016/j.jid.2018.01.028.

Learn more >

Career Opportunities

We are seeking highly motivated research associates, mater and phD students, who are interested in machine/deep learning applications to medical imaging as well as developing new metabolic MRI techniques for probing disease metabolism. If you are interested, please contact Dr. Park at ipark@chonnam.edu