Research Summary
The scope of Dr. Lee’s research includes: medical image processing and analysis, inverse problems, computer vision, machine learning, and image-guided surgery and radiation therapy.
Lab
The Medical Image Computing and Analysis (MICA) lab is a collaborative research lab led by professor Junghoon Lee based in the Department of Radiation Oncology and Molecular Radiation Sciences at the Johns Hopkins University. Research focuses on signal and image processing with applications to medical imaging problems. Specific areas of research interest include computed tomography, magnetic resonance imaging, novel image reconstruction, multi-modal image registration, segmentation, computer vision, machine learning, and image-guided interventions and radiotherapy.
Lab Website: Medical Image Computing and Analysis (MICA)
Technology Expertise Keywords
Medical imaging, image processing, computer vision, machine learning, image-guided surgery and radiotherapy
Selected Publications
J. Lee, R. F. Hobbs, M. Zahurak, S. K. Ng, Z. Zhang, E. C. Burdette, T. L. DeWeese, D. Y. Song, Phase II study of intraoperative dosimetry for prostate brachytherapy using Registered Ultrasound and Fluoroscopy (iRUF), Brachytherapy, Vol. 17, Issue 6, pp. 858-865, 2018
S. Park, R. Farah, S. M Shea, E. Tryggestad, R. Hales, J. Lee, Simultaneous tumor and surrogate motion tracking with dynamic MRI for radiation therapy planning, Physics in Medicine and Biology, Vol. 63, pp. 025015, 2018
J. Lee, O. Y. Mian, Y. Le, H. J. Bae, E. C. Burdette, T. L. DeWeese, J. L. Prince, D. Y. Song, Intraoperative Registered Ultrasound and Fluoroscopy (iRUF) for dose calculation during prostate brachytherapy: improved accuracy compared to standard ultrasound-based dosimetry, Radiotherapy and Oncology, Vol. 124, Issue 1, pp. 61-67, 2017
S. Park, W. Plishker, H. Quon, J. Wong, R. Shekhar, J. Lee, Deformable registration of CT and cone-beam CT with local intensity matching, Physics in Medicine and Biology, Vol. 62, Num. 3, pp. 927-947, 2017
S. Park, T. McNutt, W. Plishker, G. Zaki, H. Quon, J. Wong, R. Shekhar, J. Lee, Technical Note: SCUDA: A software platform for cumulative dose assessment, Medical Physics, Vol. 43, No. 10, pp. 5339-5346, 2016
Patient Ratings & Comments
The Patient Rating score is an average of all responses to physician related questions on the national CG-CAHPS Medical Practice patient experience survey through Press Ganey. Responses are measured on a scale of 1 to 5, with 5 being the best score. Comments are also gathered from our CG-CAHPS Medical Practice Survey through Press Ganey and displayed in their entirety. Patients are de-identified for confidentiality and patient privacy.