Dr. Donghoon Kim is a postdoctoral scholar at Stanford's Center for Advanced Functional Neuroimaging. Before joining Stanford, he earned his Ph.D. in Biomedical Engineering from University of California, Davis, supervised by Dr. Youngkyoo Jung. His Ph.D. thesis was titled "Deep Learning-Driven Technical Developments and Clinical Applications of Arterial Spin Labeling MRI". During his Ph.D. studies, he focused on the development of advanced deep learning techniques for ASL MRI, and its clinical applications. During his master's degree in Biomedical Engineering at Virginia Tech-Wake Forest University, he studied the functional connectivity of the default mode network using resting state BOLD fMRI among youth football players, supervised by Dr. Christopher Whitlow and Dr. Youngkyoo Jung.

Professional Education

  • Master of Science, Wake Forest University (2019)
  • Bachelor of Science, Ohio State University (2017)
  • Doctor of Philosophy, University of California Davis (2023)
  • Ph.D., University of California, Davis, Biomedical Engineering (2023)
  • M.S., Virginia Tech - Wake Forest University, Biomedical Engineering (2019)
  • B.S., Ohio State University, Electrical and Computer Engineering (2017)

Stanford Advisors

All Publications

  • Parametric cerebral blood flow and arterial transit time mapping using a 3D convolutional neural network MAGNETIC RESONANCE IN MEDICINE Kim, D., Lipford, M. E., He, H., Ding, Q., Ivanovic, V., Lockhart, S. N., Craft, S., Whitlow, C. T., Jung, Y. 2023; 90 (2): 583-595


    To reduce the total scan time of multiple postlabeling delay (multi-PLD) pseudo-continuous arterial spin labeling (pCASL) by developing a hierarchically structured 3D convolutional neural network (H-CNN) that estimates the arterial transit time (ATT) and cerebral blow flow (CBF) maps from the reduced number of PLDs as well as averages.A total of 48 subjects (38 females and 10 males), aged 56-80 years, compromising a training group (n = 45) and a validation group (n = 3) underwent MRI including multi-PLD pCASL. We proposed an H-CNN to estimate the ATT and CBF maps using a reduced number of PLDs and a separately reduced number of averages. The proposed method was compared with a conventional nonlinear model fitting method using the mean absolute error (MAE).The H-CNN provided the MAEs of 32.69 ms for ATT and 3.32 mL/100 g/min for CBF estimations using a full data set that contains six PLDs and six averages in the 3 test subjects. The H-CNN also showed that the smaller number of PLDs can be used to estimate both ATT and CBF without significant discrepancy from the reference (MAEs of 231.45 ms for ATT and 9.80 mL/100 g/min for CBF using three of six PLDs).The proposed machine learning-based ATT and CBF mapping offers substantially reduced scan time of multi-PLD pCASL.

    View details for DOI 10.1002/mrm.29674

    View details for Web of Science ID 000974719400001

    View details for PubMedID 37092852

  • Relationship Between Cerebrovascular Reactivity and Cognition Among People With Risk of Cognitive Decline. Frontiers in physiology Kim, D., Hughes, T. M., Lipford, M. E., Craft, S., Baker, L. D., Lockhart, S. N., Whitlow, C. T., Okonmah-Obazee, S. E., Hugenschmidt, C. E., Bobinski, M., Jung, Y. 2021; 12: 645342


    Vascular risk factors (e.g., obesity and hypertension) are associated with cerebral small vessel disease, Alzheimer's disease (AD) pathology, and dementia. Reduced perfusion may reflect the impaired ability of blood vessels to regulate blood flow in reaction to varying circumstances such as hypercapnia (increased end-tidal partial pressures of CO2). It has been shown that cerebrovascular reactivity (CVR) measured with blood-oxygen-level-dependent (BOLD) MRI is correlated with cognitive performance and alterations of CVR may be an indicator of vascular disfunction leading to cognitive decline. However, the underlying mechanism of CVR alterations in BOLD signal may not be straight-forward because BOLD signal is affected by multiple physiological parameters, such as cerebral blood flow (CBF), cerebral blood volume, and oxygen metabolism. Arterial spin labeling (ASL) MRI quantitatively measures blood flow in the brain providing images of local CBF. Therefore, in this study, we measured CBF and its changes using a dynamic ASL technique during a hypercapnia challenge and tested if CBF or CVR was related to cognitive performance using the Mini-mental state examination (MMSE) score. Seventy-eight participants underwent cognitive testing and MRI including ASL during a hypercapnia challenge with a RespirAct computer-controlled gas blender, targeting 10 mmHg higher end-tidal CO2 level than the baseline while end-tidal O2 level was maintained. Pseudo-continuous ASL (PCASL) was collected during a 2-min baseline and a 2-min hypercapnic period. CVR was obtained by calculating a percent change of CBF per the end-tidal CO2 elevation in mmHg between the baseline and the hypercapnic challenge. Multivariate regression analyses demonstrated that baseline resting CBF has no significant relationship with MMSE, while lower CVR in the whole brain gray matter (β = 0.689, p = 0.005) and white matter (β = 0.578, p = 0.016) are related to lower MMSE score. In addition, region of interest (ROI) based analysis showed positive relationships between MMSE score and CVR in 26 out of 122 gray matter ROIs.

    View details for DOI 10.3389/fphys.2021.645342

    View details for PubMedID 34135768

    View details for PubMedCentralID PMC8201407

  • Preliminary Study for Designing a Novel Vein-Visualizing Device. Sensors (Basel, Switzerland) Kim, D., Kim, Y., Yoon, S., Lee, D. 2017; 17 (2)


    Venipuncture is an important health diagnosis process. Although venipuncture is one of the most commonly performed procedures in medical environments, locating the veins of infants, obese, anemic, or colored patients is still an arduous task even for skilled practitioners. To solve this problem, several devices using infrared light have recently become commercially available. However, such devices for venipuncture share a common drawback, especially when visualizing deep veins or veins of a thick part of the body like the cubital fossa. This paper proposes a new vein-visualizing device applying a new penetration method using near-infrared (NIR) light. The light module is attached directly on to the declared area of the skin. Then, NIR beam is rayed from two sides of the light module to the vein with a specific angle. This gives a penetration effect. In addition, through an image processing procedure, the vein structure is enhanced to show it more accurately. Through a phantom study, the most effective penetration angle of the NIR module is decided. Additionally, the feasibility of the device is verified through experiments in vivo. The prototype allows us to visualize the vein patterns of thicker body parts, such as arms.

    View details for DOI 10.3390/s17020304

    View details for PubMedID 28178227

    View details for PubMedCentralID PMC5336071