publications

2024

1. Skeletal Rad.

   Improved Resolution and Image Quality of Musculoskeletal Magnetic Resonance Imaging using Deep Learning-based Denoising Reconstruction: A Prospective Clinical Study.

   Do Hung P., Lockard Carly A., Berkeley Dawn, Tymkiw Brian, Dulude Nathan, Tashman Scott, Gold Garry, Gross Jordan, Kelly Erin, and Ho Charles P.

   Skeletal Radiology 2024

   Abstract HTML PDF

   Objective: To prospectively evaluate a deep learning-based denoising reconstruction (DLR) for improved resolution and image quality in musculoskeletal (MSK) magnetic resonance imaging (MRI). Methods: Images from 137 contrast-weighted sequences in 40 MSK patients were evaluated. Each sequence was performed twice, first with the routine parameters and reconstructed with a routine reconstruction filter (REF), then with higher resolution and reconstructed with DLR, and with three conventional reconstruction filters (NL2, GA43, GA53). The five reconstructions (REF, DLR, NL2, GA43, and GA53) were de-identified, randomized, and blindly reviewed by three MSK radiologists using eight scoring criteria and a forced ranking. Quantitative SNR, CNR, and structure’s full width at half maximum (FWHM) for resolution assessment were measured and compared. To account for repeated measures, Generalized Estimating Equations (GEE) with Bonferroni adjustment was used to compare the reader’s scores, SNR, CNR, and FWHM between DLR vs. NL2, GA43, GA53, and REF. Results: Compared to the routine REF images, the resolution was improved by 47.61% with DLR from 0.39±0.15 mm2 to 0.20±0.06 mm2 (p<0.001). Per-sequence average scan time was shortened by 7.93% with DLR from 165.58±21.86 s to 152.45±25.65 s (p<0.001). Based on the average scores, DLR images were rated significantly higher in all image quality criteria and the forced ranking (p<0.001). Conclusion: This prospective clinical evaluation demonstrated that DLR allows approximately two times finer resolution and improved image quality compared to the standard-of-care images.

2022

1. Neu.Trau.Rep.

   Magnetic Resonance Imaging Findings in High School Football Players: Brain and Cervical Spine

   Yu H., Wardi L., Say I., Paganini-Hill A., Chow D., Jafari A., Farhan S., Sol S., Mobayed O., Alvarez A., Hasso A., Li S., Do Hung P., Berkeley D., Lee Y., Su L., Rosen C., and Fisher M.

   Neurotrauma Reports 2022

   Abstract HTML PDF

   Football exposes its players to traumatic brain, neck, and spinal injury. It is unknown whether the adolescent football player develops imaging abnormalities of the brain and spine that are detectable on magnetic resonance imaging (MRI). The objective of this observational study was to identify potential MRI signatures of early brain and cervical spine (c-spine) injury in high school football players. Eighteen football players (mean age, 17.0 ± 1.5 years; mean career length, 6.3 ± 4.0 years) had a baseline brain MRI, and 7 had a follow-up scan 9–42 months later. C-spine MRIs were performed on 11 of the 18 subjects, and 5 had a follow-up scan. C-spine MRIs from 12 age-matched hospital controls were also retrospectively retrieved. Brain MRIs were reviewed by a neuroradiologist, and no cerebral microbleeds were detected. Three readers (a neuroradiologist, a neurosurgeon, and an orthopedic spine surgeon) studied the cervical intervertebral discs at six different cervical levels and graded degeneration using an established five-grade scoring system. We observed no statistically significant difference in disc degeneration or any trend toward increased disc degeneration in the c-spine of football players as compared with age-matched controls. Further research is needed to validate our findings and better understand the true impact of contact sports on young athletes.

2020

1. MRM

   Accuracy, uncertainty, and adaptability of automatic myocardial ASL segmentation using deep CNN

   Do Hung P., Guo Yi, Yoon Andrew J., and Nayak Krishna S.

   Magnetic Resonance in Medicine 2020

   Abstract arXiv HTML PDF

   Purpose To apply deep convolution neural network to the segmentation task in myocardial arterial spin labeled perfusion imaging and to develop methods that measure uncertainty and that adapt the convolution neural network model to a specific false-positive versus false-negative tradeoff. Methods The Monte Carlo dropout U-Net was trained on data from 22 subjects and tested on data from 6 heart transplant recipients. Manual segmentation and regional myocardial blood flow were available for comparison. We consider 2 global uncertainty measures, named “Dice uncertainty” and “Monte Carlo dropout uncertainty,” which were calculated with and without the use of manual segmentation, respectively. Tversky loss function with a hyperparameter β was used to adapt the model to a specific false-positive versus false-negative tradeoff. Results The Monte Carlo dropout U-Net achieved a Dice coefficient of 0.91 ± 0.04 on the test set. Myocardial blood flow measured using automatic segmentations was highly correlated to that measured using the manual segmentation (R2 = 0.96). Dice uncertainty and Monte Carlo dropout uncertainty were in good agreement (R2 = 0.64). As β increased, the false-positive rate systematically decreased and false-negative rate systematically increased. Conclusion We demonstrate the feasibility of deep convolution neural network for automatic segmentation of myocardial arterial spin labeling, with good accuracy. We also introduce 2 simple methods for assessing model uncertainty. Finally, we demonstrate the ability to adapt the convolution neural network model to a specific false-positive versus false-negative tradeoff. These findings are directly relevant to automatic segmentation in quantitative cardiac MRI and are broadly applicable to automatic segmentation problems in diagnostic imaging.

2018

1. JCMR

   Non-contrast assessment of microvascular integrity using arterial spin labeled cardiovascular magnetic resonance in a porcine model of acute myocardial infarction

   Do Hung P., Ramanan Venkat, Qi Xiuling, Barry Jennifer, Wright Graham A., Ghugre Nilesh R., and Nayak Krishna S.

   Journal of Cardiovascular Magnetic Resonance Jul 2018

   Abstract HTML PDF

   Following acute myocardial infarction (AMI), microvascular integrity and function may be compromised as a result of microvascular obstruction (MVO) and vasodilator dysfunction. It has been observed that both infarcted and remote myocardial territories may exhibit impaired myocardial blood flow (MBF) patterns associated with an abnormal vasodilator response. Arterial spin labeled (ASL) CMR is a novel non-contrast technique that can quantitatively measure MBF. This study investigates the feasibility of ASL-CMR to assess MVO and vasodilator response in swine.

2017

1. MRM

   Double-gated myocardial ASL perfusion imaging is robust to heart rate variation

   Do Hung P., Yoon Andrew J., Fong Michael W., Saremi Farhood, Barr Mark L., and Nayak Krishna S.

   Magnetic Resonance in Medicine 2017

   Abstract HTML PDF

   Purpose Cardiac motion is a dominant source of physiological noise (PN) in myocardial arterial spin labeled (ASL) perfusion imaging. This study investigates the sensitivity to heart rate variation (HRV) of double-gated myocardial ASL compared with the more widely used single-gated method. Methods Double-gating and single-gating were performed on 10 healthy volunteers (n = 10, 3F/7M; age, 23–34 years) and eight heart transplant recipients (n = 8, 1F/7M; age, 26–76 years) at rest in the randomized order. Myocardial blood flow (MBF), PN, temporal signal-to-noise ratio (SNR), and HRV were measured. Results HRV ranged from 0.2 to 7.8 bpm. Double-gating PN did not depend on HRV, while single-gating PN increased with HRV. Over all subjects, double-gating provided a significant reduction in global PN (from 0.20 ± 0.15 to 0.11 ± 0.03 mL/g/min; P = 0.01) and per-segment PN (from 0.33 ± 0.23 to 0.21 ± 0.12 mL/g/min; P < 0.001), with significant increases in global temporal SNR (from 11 ± 8 to 18 ± 8; P = 0.02) and per-segment temporal SNR (from 7 ± 4 to 11 ± 12; P < 0.001) without significant difference in measured MBF. Conclusion Single-gated myocardial ASL suffers from reduced temporal SNR, while double-gated myocardial ASL provides consistent temporal SNR independent of HRV. Magn Reson Med 77:1975–1980, 2017. © 2016 International Society for Magnetic Resonance in Medicine

2. JMRI

   Assessment of segmental myocardial blood flow and myocardial perfusion reserve by adenosine-stress myocardial arterial spin labeling perfusion imaging

   Yoon Andrew J., Do Hung P., Cen Steven, Fong Michael W., Saremi Farhood, Barr Mark L., and Nayak Krishna S.

   Journal of Magnetic Resonance Imaging 2017

   Abstract HTML PDF

   Purpose To determine the feasibility of measuring increases in myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) on a per-segment basis using arterial spin labeled (ASL) magnetic resonance imaging (MRI) with adenosine vasodilator stress in normal human myocardium. Materials and Methods Myocardial ASL scans at rest and during adenosine infusion were incorporated into a routine 3T MR adenosine-induced vasodilator stress protocol and were performed in 10 healthy human volunteers. Myocardial ASL was performed using single-gated flow-sensitive alternating inversion recovery (FAIR) tagging and balanced steady-state free precession (bSSFP) imaging at 3T. A T2-prep blood oxygen level-dependent (BOLD) SSFP sequence was used to concurrently assess segmental myocardial oxygenation with BOLD signal intensity (SI) percent change in the same subjects. Results There was a statistically significant difference between MBF measured by ASL at rest (1.75 ± 0.86 ml/g/min) compared to adenosine stress (4.58 ± 2.14 ml/g/min) for all wall segments (P < 0.0001), yielding a per-segment MPR of 3.02 ± 1.51. When wall segments were divided into specific segmental myocardial perfusion territories (ie, anteroseptal, anterior, anterolateral, inferolateral, inferior, and inferoseptal), the differences between rest and stress regional MBF for each territory remained consistently statistically significant (P < 0.001) after correcting for multiple comparisons. Conclusion This study demonstrates the feasibility of measuring MBF and MPR on a segmental basis by single-gated cardiac ASL in normal volunteers. Second, this study demonstrates the feasibility of performing the ASL sequence and T2-prepared SSFP BOLD imaging during a single adenosine infusion. Level of Evidence: 2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:413–420

2014

1. JCMR

   Myocardial arterial spin labeling perfusion imaging with improved sensitivity

   Do Hung P., Jao Terrence R., and Nayak Krishna S.

   Journal of Cardiovascular Magnetic Resonance Jan 2014

   Abstract HTML PDF

   Myocardial arterial spin labeling (ASL) is a noninvasive MRI based technique that is capable of measuring myocardial blood flow (MBF) in humans. It suffers from poor sensitivity to MBF due to high physiological noise (PN). This study aims to determine if the sensitivity of myocardial ASL to MBF can be improved by reducing image acquisition time, via parallel imaging.

2008

1. CIP

   On the new type of optical bio-sensor from DNA-wrapped carbon nanotubes

   Do Hung P., Dao Le Hien, Do Nga T., Ngo Van Thanh, and Nguyen Ai Viet

   Communications in Physics Sep 2008

   Abstract PDF

   Recently, Daniel A. Heller et al. (Science 311, 508 (2006)) demonstrated that carbon nanotubes wrapped with DNA can be placed inside living cells and detect trace amounts of harmful contaminants using near infrared light. This discovery could lead to new types of optical sensor and biomarkers at the subcellular level. We study a simple model of this new optical bio-sensor by wrapping a piece of double-stranded DNA around the surface of single-walled carbon nanotube in much the same fashion as a ribbon wraps around a cylinder. The DNA starts out wrapping around the nanotube with a certain shape that is defined by the negative charges along its backbone. Based on a theory of exciton in carbon nanotubes and we investigated transition of DNA secondary structure from the native, right-handed B form to the alternate, left-handed Z form. We’ve shown that our simple model can explain the working principle of this optical bio-sensor from DNA and carbon nanotubes.

2016

1. WIPO

   SYNCHRONIZED MULTI-MODULE PULSED ARTERIAL SPIN LABELED MAGNETIC RESONANCE IMAGING

   Do Hung P., Jao Terrence R., and Nayak Krishna S.

   International Patent Application No. WO/2016/089895 Jun 2016

   HTML PDF

2023

1. Canon USA

   Prospective Clinical Evaluation of Novel Deep Learning Denoising Reconstruction for Improved Image Quality in Musculoskeletal Magnetic Resonance Imaging

   Do Hung P., and Berkeley D.

   Canon Medical Systems USA, Inc., Tustin, CA, Dec 2023
2. Canon USA

   MSK Imaging using Advanced intelligent Clear-IQ Engine (AiCE) Deep Learning Reconstruction

   Do Hung P., and Berkeley D.

   Canon Medical Systems USA, Inc., Tustin, CA, Dec 2023

   PDF

2022

1. Canon Global

   Good to Know: Multi-echo Ultrashort Echo Time (UTE)

   Do Hung P.

   Canon Medical Systems Corporation, Japan, Mar 2022

   HTML PDF

2021

1. Canon Global

   Good to Know: Advanced intelligent Clear-IQ Engine (AiCE) Deep Learning Reconstruction - Page #53 VISION MAGAZINE SPECIAL EDITION NO.1

   Do Hung P.

   Canon Medical Systems Corporation, Japan, Jul 2021

   HTML PDF
2. Canon USA

   Advanced intelligent Clear-IQ Engine (AiCE) Interpretable Model with Robust and Generalized Performance: Beyond Brain and Knee

   Do Hung P., and Berkeley D.

   Canon Medical Systems USA, Inc., Tustin, CA, May 2021

   HTML PDF

2020

1. Canon USA

   Advanced intelligent Clear-IQ Engine (AiCE) Deep Learning Reconstruction: Effectively Removes Noise while Maintaining MR Signal

   Do Hung P.

   Canon Medical Systems USA, Inc., Tustin, CA, Jul 2020

   HTML PDF
2. Canon USA

   Advanced intelligent Clear-IQ Engine (AiCE) Deep Learning Reconstruction (DLR): Translating the Power of Deep Learning to MR Image Reconstruction

   Do Hung P.

   Canon Medical Systems USA, Inc., Tustin, CA, Mar 2020

   HTML PDF

2019

1. Canon USA

   k-t SPEEDER: A reference-free parallel imaging method for fast dynamic MRI

   Do Hung P.

   Canon Medical Systems USA, Inc., Tustin, CA, Jan 2019

   HTML PDF

2024

1. RSNA

   Reliability, Agreement, and Biases of Deep Learning-based Reconstructions for Quantitative Susceptibility Mapping (QSM)

   Do Hung P., Yu H., Berkeley D., Lin W., Tymkiw B., AlGhuraibawi W., Soun J., Chang P., Kadbi M., Su L., Fisher M., and Pakbaz Z.

   Proceedings of the Radiological Society of North America Scientific Sessions, Chicago, Dec 2024
2. RSNA

   Improved Precision and Resolution of Cartilage T2 Mapping using Deep Learning Reconstruction

   Do Hung P., Berkeley D., Tymkiw B., AlGhuraibawi W., and Kadbi M.

   Proceedings of the Radiological Society of North America Scientific Sessions, Chicago, Dec 2024
3. ISMRM

   Test-Retest Reliability, Agreement, and Bias of Deep Learning-based Reconstructions for PDFF and R2* Quantification

   Do Hung P., Starekova J., Malis V., Bae W., Berkeley D., Tymkiw B., AlGhuraibawi W., Reeder S. B., Brittain J. H., Kadbi M., and Hernando D.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2024
4. ISMRM

   Accelerated 3D isotropic multi-echo UTE using CG-SENSE and Deep Learning Reconstruction for CT-like Imaging and Ultrashort T2* Mapping

   Do Hung P., Bekku M., Berkeley D., Tymkiw B., AlGhuraibawi W., and Kadbi M.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2024
5. ISMRM

   Multi-center, multi-vendor validation of PDFF and T1 mapping in an Optimized PDFF-T1 Phantom

   Starekova J., Rutkowski D., Bae W., Do Hung P., Madhuranthakam A., Malis V., Mukherjee S., Lin S. Q., Serai S., Yokoo T., Reeder S. B., Brittain J. H., and Hernando D.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2024
6. ASNR Late Breaking Oral

   Deep Learning Reconstruction Using Convolution Neural Networks Enables up to 3X High-Resolution Imaging, Improved Sharpness, and Reduced Ringing Artifacts for Neuroimaging at 1.5T and 3T.

   AlGhuraibawi W., Caruthers S., Do Hung P., Berkeley D., Tymkiw B., and Kadbi M.

   Proceedings of the American Society of Neuroradiology Scientific Sessions, May 2024

2023

1. RSNA Oral Presentation

   Accelerated 2-3-Minute Multi-echo Ultra-short Echo Time (mecho UTE) using Conjugate Gradient SENSE (CG-SENSE) Reconstruction

   Do Hung P., Berkeley D., Tymkiw B., AlGhuraibawi W., and Kadbi M.

   Proceedings of the Radiological Society of North America Scientific Sessions, Chicago, Nov 2023

   VIDEO Slides
2. RSNA

   Artificial Intelligent and MRI Artifacts: A Pictorial Review of MRI Artifacts and AI Techniques for Reduction

   Carbone J., Chow D., Soun J., Kadbi M., and Do Hung P.

   Proceedings of the Radiological Society of North America Education Exhibits, Chicago, Nov 2023
3. ISMRM Oral Presentation

   Multi-center, multi-vendor validation of PDFF-R2* mapping in an Optimized Fat-Iron Phantom

   Starekova J., Rutkowski D., Bae W., Do Hung P., Madhuranthakam A., Malis V., Mukherjee S., Lin S. Q., Serai S., Yokoo T., Reeder S. B., Brittain J. H., and Hernando D.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, Jun 2023
4. ISMRM

   Deep Learning Denoising Reconstruction Enables up to 2X Scan Time Reduction while Maintaining Image Quality for Musculoskeletal MRI

   Do Hung P., Berkeley D., Tymkiw B., AlGhuraibawi W., and Kadbi M.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, Jun 2023
5. ISMRM

   Increased Resolution and Shortened Scan Time of T2 weighted Prostate MRI using Deep Learning Denoising Reconstruction at 1.5T

   Do Hung P., Berkeley D., Tymkiw B., AlGhuraibawi W., and Kadbi M.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, Jun 2023

2022

1. RSNA Oral Presentation

   Eleven-minute Comprehensive MSK Imaging Using Deep Learning Reconstruction (DLR) and Multi-echo Ultrashort Echo-Time (UTE)

   Do Hung P., Berkeley D., Tymkiw B., AlGhuraibawi W., and Kadbi M.

   Proceedings of the Radiological Society of North America Scientific Sessions, Chicago, Nov 2022

   Slides
2. ISMRM

   Visualizing Short T2* Tissues, Generating Associated T2* Map, and Producing CT-like Images of Bony Structures using Multi-echo UTE

   Do Hung P., Berkeley D., Tymkiw B., and Kadbi M.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2022
3. ISMRM

   Deep Learning Denoising Reconstruction (DLR) Preserves Quantitative DWI and DCE Signal Intensity Measures in Prostate MRI

   Do Hung P., Tymkiw B., Berkeley D., and Kadbi M.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2022

2021

1. RSNA

   Developing a Framework for Prospective Evaluation of MRI Deep Learning Reconstruction: A Case Study of Higher Resolution and Higher Image Quality in Shorter Scan Time

   Do Hung P., Lockard C., Berkeley D., Tymkiw B., Dulude N., Tashman S., Gold G., Kelly E., and Ho C.

   Proceedings of the Radiological Society of North America Scientific Sessions, Chicago, Dec 2021
2. RSNA Oral Presentation

   Blinded Reader Validation Study for Generalizable Deep Learning Denoising Reconstruction (DLR) Throughout Multiple Anatomies at 1.5T And 3T

   Caruthers S., Falls Y., Do Hung P., Kadbi M., Ishimoto T., Shinoda K., Taguchi A., and Kelly E.

   Proceedings of the Radiological Society of North America Scientific Sessions, Chicago, Dec 2021
3. RSNA

   Application of Deep Learning Reconstruction in MR: Higher Resolution MR Imaging in Shorter Scan Time

   Kadbi M., Berkeley D., Tymkiw B., Do Hung P., and Kelly E.

   Proceedings of the Radiological Society of North America Scientific Sessions, Chicago, Dec 2021
4. RSNA Oral Presentation

   Evaluation of Image Quality and Artifact in Deep Learning Reconstruction Method Using an ACR Phantom

   Kadbi M., Trent J., Do Hung P., and Kelly E.

   Proceedings of the Radiological Society of North America Scientific Sessions, Chicago, Dec 2021
5. ASTRO

   Deep Learning Reconstruction Helps to Achieve Diagnostic-like Image Quality in MR Radiation Therapy of Brain

   Kadbi M., Berkeley D., Tymkiw B., Do Hung P., and Kelly E.

   Proceedings of the American Society for Radiation Oncology Scientific Sessions, Oct 2021
6. ISMRM

   Higher Resolution with Improved Image Quality without Increased Scan Time: Is It Possible with MRI Deep Learning Reconstruction?

   Do Hung P., Lockard C., Berkeley D., Tymkiw B., Dulude N., Tashman S., Gold G., Kelly E., and Ho C.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2021
7. ISMRM

   Prospective Performance Evaluation of the Deep Learning Reconstruction Method at 1.5T: A Multi-Anatomy and Multi-Reader Study

   Do Hung P., Kadbi M., Berkeley D., Tymkiw B., and Kelly E.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2021
8. ISMRM

   A Paradigm Shift in MR Physics with Deep Learning Reconstruction: Higher Image Quality and Spatial Resolution in Shorter Scan Time

   Kadbi M., Berkeley D., Tymkiw B., Do Hung P., and Kelly E.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2021
9. ISMRM

   Initial Results of a Novel High-Resolution 3D-FSE Based Protocol for Silicone Breast Implant Screening

   Zaidi T., Mugler J., Hood M., Garra B., Do Hung P., Kadbi M., and Rajan S.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2021
10. JSRT

    Evaluation of the Versatility of the Advanced intelligent Clear-IQ Engine (AiCE) in MR for Various Sites and Contrast Types

    Taguchi A., Ishimoto T., Do Hung P., Mo K., and Shinoda K.

    Proceedings of the Japan Society of Radiological Technology Scientific Sessions, Apr 2021

2020

1. ISMRM

   Clinical Image Quality Evaluation for Field Strength and Contrast Independence of Deep Learning Reconstruction

   Kelly E., Do Hung P., Berkeley D., and Furuyama J.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, Aug 2020

2019

1. RSNA

   Ultrashort Echo Time (UTE) Imaging: Review of Technique and Musculoskeletal Applications with Examples of Utility in the Knee

   Matcuk G., Gholamrezanezhad A., Do Hung P., Franco M., and Desai B.

   Proceedings of the Radiological Society of North America Education Exhibits, Chicago, Nov 2019
2. SCMR Oral Presentation

   DnoiseNET: Deep Convolutional Neural Network for Image Denoising

   Do Hung P., Yoon A., and Nayak K.

   The Proceedings of the ISMRM & SCMR Co-Provided Workshop on the Emerging Role of Machine Learning in Cardiovascular Magnetic Resonance Imaging, Feb 2019

   Slides
3. ISMRM Oral Presentation

   Deep Convolutional Neural Network for Segmentation of Myocardial ASL Short-Axis Data: Accuracy, Uncertainty, and Adaptability

   Do Hung P., Guo Y., Yoon A., and Nayak K.

   The Proceedings of the ISMRM Workshop on Machine Learning Part 2, Oct 2019

   HTML VIDEO Slides
4. ISMRM

   Optimization of Steady-Pulsed Arterial Spin Labeling for Myocardial Perfusion Imaging

   Javed A., Lee N., Do Hung P., Ghugre N., Wright G., Wong E., and Nayak K.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2019

2018

1. RSNA

   Compressed Sensing Magnetic Resonance Imaging (CS-MRI) for Accelerated Knee MR Imaging

   Matcuk G., Do Hung P., Gross J., Fields B., Franco M., and Desai B.

   Proceedings of the Radiological Society of North America Education Exhibits, Chicago, Nov 2018
2. SCMR

   Optimal Flip Angle for Steady Pulsed Arterial Spin Labeled CMR

   Do Hung P., Jao T., Ramanan V., Wright G., Ghugre N., and Nayak K.

   The Proceedings of the ISMRM & SCMR Co-provided Workshop on CMR in Ischemic Heart Disease, Feb 2018
3. SCMR

   Coronary Endothelial Function Testing using Continuous Cardiac ASL-CMR

   Javed A., Do Hung P., Yoon A., Nayak K., and Garg P.

   The Proceedings of the ISMRM & SCMR Co-provided Workshop on CMR in Ischemic Heart Disease, Feb 2018

2017

1. ISMRM

   Physiologically Synchronized Multi-Module Pulsed Arterial Spin Labeled (SymPASL) MRI

   Do Hung P., and Nayak K.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, Apr 2017
2. ISMRM Power Pitch (top 2%)

   Non-contrast Assessment of Vasodilator Response using Native Myocardial T1 and T2 Mapping and Arterial Spin Labeled CMR

   Ghugre N., Do Hung P., Chu K., Ramanan V., Nayak K., and Wright G.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, Apr 2017
3. ISMRM

   Comparison of Renal Blood Flow Measurements Obtained using ASL-MRI and CT Perfusion

   Landes V., Ferguson C., Do Hung P., Woollard J., Krier J., Lerman L., and Nayak K.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, Apr 2017
4. SCMR Oral Presentation

   Vasodilator Response in Heart Transplant Recipients using T1-based Myocardial Blood Volume Mapping

   Do Hung P., Yoon A., Fong M., Grazette L., Saremi F., Barr M., and Nayak K.

   The Proceedings of the ISMRM & SCMR Co-provided Workshop, Feb 2017
5. SCMR Moderated Poster

   Contrast Free Assessment of Vasodilator Response using Myocardial T2 BOLD and Arterial Spin Labeled CMR

   Ghugre N., Do Hung P., Ramanan V., Nayak K., and Wright G.

   Proceedings of the Society for Cardiovascular Magnetic Resonance Scientific Sessions, Feb 2017

2016

1. ISMRM Oral Presentation

   Non-contrast Vasodilator Response Assessment in a porcine model of Acute Myocardial Infarction using Arterial Spin Labeled CMR

   Do Hung P., Ramanan V., Wright G., Ghugre N., and Nayak K.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2016
2. ISMRM

   Double-gated Myocardial Arterial Spin Labeled Perfusion Imaging provides Insensitivity to Heart Rate Variation

   Do Hung P., Yoon A., Fong M., Saremi F., Barr M., and Nayak K.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2016
3. ISMRM

   Myocardial Arterial Spin Labeled Perfusion Imaging using Modified Look-Locker Inversion Recovery (MOLLI)

   Do Hung P., and Nayak K.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2016
4. SCMR Oral Presentation

   Non-contrast Myocardial Perfusion Assessment in Porcine Acute Myocardial Infarction using Arterial Spin Labeled CMR

   Do Hung P., Ramanan V., Jao T., Wright G., Nayak K., and Ghugre N.

   Proceedings of the Society for Cardiovascular Magnetic Resonance Scientific Sessions, Feb 2016
5. SCMR

   Myocardial ASL-CMR Perfusion Imaging with Improved Sensitivity using GRAPPA

   Jao T., Do Hung P., and Nayak K.

   Proceedings of the Society for Cardiovascular Magnetic Resonance Scientific Sessions, Feb 2016

2015

1. SCMR

   Arterial Spin Labeling CMR Perfusion Imaging is Capable of Continuously Monitoring Myocardial Blood Flow during Stress

   Do Hung P., Javed A., Jao T., Kim H., Yoon A., and Nayak K.

   Proceedings of the Society for Cardiovascular Magnetic Resonance Scientific Sessions, Feb 2015

2014

1. BMES

   Temporal SNR of Myocardial ASL does not Increase with Improved Spatial Consistency of Background Suppression

   Jao T., Do Hung P., and Nayak K.

   Proceedings of the Biomedical Engineering Society Scientific Sessions, Oct 2014
2. ISMRM

   Myocardial Arterial Spin Labeling with Improved Sensitivity to Myocardial Blood Flow using Parallel Imaging

   Do Hung P., Jao T., and Nayak K.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2014

2013

1. ISMRM

   In Vivo Performance of Myocardial Background Suppression

   Jao T., Do Hung P., and Nayak K.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, Apr 2013

2011

1. ISMRM

   Magnetization Transfer Effects in Wideband Steady State Free Precession (wb-SSFP)

   Do Hung P., Lebel M., and Nayak K.

   Proceedings of the International Society for Magnetic Resonance in Medicine Scientific Sessions, May 2011

2007

1. NCTP Oral Presentation

   On the New Type of Optical Bio-sensor from DNA-wrapped Carbon Nanotubes

   Do Hung P., Dao H., Do N., Ngo T., and Nguyen V.

   Proceedings of the Vietnam National Conference on Theoretical Physics Scientific Sessions, Aug 2007