M.Sc. Hong Phuc Vo

Institut für Medizintechnik
Universität zu Lübeck
Ratzeburger Allee 160
23562 Lübeck
Gebäude 64, Raum 024

Email:	h.vo(at)uni-luebeck.de
Phone:	+49 451 3101 5443

Roles

Research Assistant

Research

Research Interests

Image Reconstruction
Monte-Carlo Simulation
Nuclear Imaging

Involved Projects

Curriculum Vitae

HONG PHUC VO was born in Ben Tre, Vietnam in 1998. He received his Master of Sciences in Biomedical Engineering in 2023 from the University of Lübeck, Germany. In 2023, he wrote his master’s thesis on “Statistical Image Reconstruction and Evaluation of a dedicated prostate PET scanner” at the Institute of Medical Engineering, Universität zu Lübeck in collaboration with Picotech SAS, France. During his studies, he developed a keen interest in nuclear imaging, especially in PET image reconstruction and Monte-Carlo simulation. Since February 2023, he works as a research assistant at the Institute of Medical Engineering.

Publications

[ 2024 ]
[ 2023 ]
[ 2022 ]

2024[ to top ]

Seeger, S., Vo, H., Elmoujarkach, E., Schmidt, C. and Rafecas, M.: EP-0704 The MERMAID Project : Pioneering PET Imaging for Small Aquatics Animals, European Journal of Nuclear Medicine and Molecular Imaging, EANM’24 Abstract Book Congress Oct 19-23, 2024, 2024, DOI: 10.1007/s00259-024-06838-z.
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@article{seeger2024ep0704, author = {Seeger, Steven and Vo, Hong and Elmoujarkach, Ezzat and Schmidt, Christian and Rafecas, Magdalena}, journal = {European Journal of Nuclear Medicine and Molecular Imaging}, keywords = {SeegerSteven}, title = {EP-0704 The MERMAID Project : Pioneering PET Imaging for Small Aquatics Animals}, volume = {EANM’24 Abstract Book Congress Oct 19-23, 2024}, year = 2024 }
Karakatsanis, N., Atkinson, D., Buscaron, C., Cheng, J.-C. K., Coussat, A., Deidda, D., Efthimiou, N., Elmoujarkach, E., Goncharov, F., Han, F., Hansen, M., Jehl, M., Jurjew, N., Kesner, A., Lennie, E., McFarland, A., Nuyts, J., Polson, L., Rahmim, A., Reimers, E., Schramm, G., Singh, I., Soultanidis, G., Spangler-Bickell, M., Stairs, J., Stute, S., Toussaint, M., Twyman, R., Vo, H. P., Wells, R. G. and Thielemans, K.: Usability of PETSIRD, the PET Raw Data open format of the Emission Tomography Standardization Initiative (ETSI): results from ETSIs first hackathon, Journal of Nuclear Medicine, 65(supplement 2), 241285–241285, 2024.
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@article{Karakatsanis241285, abstract = {241285 Introduction: With the advent of Positron Emission Tomography (PET) scanners of increasingly higher sensitivity alongside the evolving capacity of Artificial Intelligence (AI) to support Nuclear Medicine, the opportunity for accessing high fidelity information through standardized PET raw data has become apparent. The Emission Tomography Standardization Initiative (ETSI) was founded in 2022 from an international consortium of nuclear medicine experts to define open, extendable, standardized and vendor-agnostic formats of emission tomography raw data. Currently, the initiative focuses on developing the PET ETSI Raw Data (PETSIRD) list-mode format comprised of (i) data elements (e.g. coincidence events, geometry, correction factors, etc.), (ii) a container describing the element{\textquoteright}s structure and the protocols for access, storage and transfer using Microsoft Research YARDL meta-language, and (iii) a use-cases software library. We report on the progress of developing use-case applications for generating, accessing and processing PETSIRD data.Methods: On November 13-14th 2023, ETSI organized its in Vancouver, BC, Canada, aiming at the development of proof-of-concept open-source software for PETSIRD use-cases to demonstrate its usability. A group of 30 international participants from industry and academia worked together to produce software tools showcasing how to create, access and process PETSIRD data for well-defined user tasks in quantitative PET imaging. Specifically, four subgroups were formed to work on the following tasks: (1) apply split/merge, gating and sub-sampling operations on PETSIRD data according to a user-defined or physiological signal (e.g. ECG) input, (2) build a convertor from GATE Monte Carlo simulations output data in ROOT format to PETSIRD and subsequently generate simulated demo PETSIRD data from realistic Monte Carlo simulations, (3) add a PETSIRD read/write/processing interface within existing open-source reconstruction software, and (4) analytically simulate PETSIRD data from images as well as independently reconstruct PET images from PETSIRD data alone. In all use-cases, the highly versatile YARDL container model of PETSIRD was exploited.Results: All four subgroups were able to make substantial progress during the 2-day hackathon and delivered useful and practical software tools demonstrating PETSIRD{\textquoteright}s high usability and functionality. Specifically, subgroup 1 implemented tools for both sub-sampling and gating operations on PETSIRD data guided by external inputs. Subgroup 2 built a ROOT-to-PETSIRD converter, to be used as a possible roadmap for future converters from vendor proprietary formats to PETSIRD and generated realistic demo PETSIRD data of a simplified NEMA IEC phantom. Subgroup 3 added basic PETSIRD input/output interfaces to STIR, CASToR and PyTomography open-source libraries. Subgroup 4 used PARALLELPROJ{\textquoteright}s open-source projectors to analytically generate synthetic PETSIRD data from images. Finally, subgroup 4 successfully reconstructed an estimate of the NEMA phantom PET image from the PETSIRD demo data of subgroup 2, thus independently validating the respective software of the two subgroups and the format{\textquoteright}s capability to contain sufficient information for standalone reconstruction. The role of PETSIRD{\textquoteright}s YARDL container was pivotal in all developments, as its automatic code generation capabilities in both C++ and Python enabled rapid software prototyping. Prototype PETSIRD definitions are available on . All code will be made available there.Conclusions: The successful implementation of several practical and functional use cases during ETSI{\textquoteright}s first hackathon demonstrated PETSIRD{\textquoteright}s usability as a standalone, open-source, standardized PET list-mode data format. Moreover, it highlighted its value as a vendor- and scanner-agnostic standard to aid the development of novel and high-impact PET applications and analysis tools especially of those relying on data sharing and harmonization principles such as AI models.}, author = {Karakatsanis, Nicolas and Atkinson, David and Buscaron, Camilo and Cheng, Ju-Chieh Kevin and Coussat, Aur{\'e}lien and Deidda, Daniel and Efthimiou, Nikos and Elmoujarkach, Ezzat and Goncharov, Fedor and Han, Fang and Hansen, Michael and Jehl, Markus and Jurjew, Nicole and Kesner, Adam and Lennie, Eve and McFarland, Aaron and Nuyts, Johan and Polson, Luke and Rahmim, Arman and Reimers, Erik and Schramm, Georg and Singh, Imraj and Soultanidis, Georgios and Spangler-Bickell, Matthew and Stairs, John and Stute, Simon and Toussaint, Maxime and Twyman, Robert and Vo, Hong Phuc and Wells, R. Glenn and Thielemans, Kris}, journal = {Journal of Nuclear Medicine}, keywords = {imt}, number = {supplement 2}, pages = {241285–241285}, publisher = {Society of Nuclear Medicine}, title = {Usability of PETSIRD, the PET Raw Data open format of the Emission Tomography Standardization Initiative (ETSI): results from ETSIs first hackathon}, volume = 65, year = 2024 }
Seeger, S., Elmoujarkach, E., Vo, H., Schmidt, C. and Rafecas, M.: Feasibility of Zirconium-89 Imaging with MERMAID, a small-fish PET scanner prototype, 1–2, 2024, DOI: 10.1109/NSS/MIC/RTSD57108.2024.10656767.
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@inproceedings{10656767, author = {Seeger, Steven and Elmoujarkach, Ezzat and Vo, Hong and Schmidt, Christian and Rafecas, Magdalena}, booktitle = {2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)}, keywords = {SeegerSteven}, pages = {1-2}, title = {Feasibility of Zirconium-89 Imaging with MERMAID, a small-fish PET scanner prototype}, year = 2024 }
Vo, H. P., Williams, T., Doroud, K., Williams, C. and Rafecas, M.: EP-0793 Development of dedicated prostate TOF-PET based on ProVision detection concept: Initial image performance study, European Journal of Nuclear Medicine and Molecular Imaging, EANM’24 Abstract Book Congress Oct 19-23, 2024, 2024, DOI: 10.1007/s00259-024-06838-z.
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@article{vo2024ep0793, author = {Vo, Hong Phuc and Williams, Themistoklis and Doroud, Katayoun and Williams, Crispin and Rafecas, Magdalena}, journal = {European Journal of Nuclear Medicine and Molecular Imaging}, keywords = {nuci}, month = {09}, title = {EP-0793 Development of dedicated prostate TOF-PET based on ProVision detection concept: Initial image performance study}, volume = {EANM’24 Abstract Book Congress Oct 19-23, 2024}, year = 2024 }
Lan, W., Vo, H. P., Pommranz, C., Elmoujarkach, E., Cabello, J., Birge, N., Schleyer, P., Rafecas, M., Lafougère, C. and Schmidt, F.: A Simulation Framework to Establish Ground Truth for Motion Correction in Total-Body PET: Initial Evaluation for Complex Respiratory Motion, 1–2, 2024, DOI: 10.1109/NSS/MIC/RTSD57108.2024.10656116.
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@inproceedings{10656116, abstract = {The enhanced sensitivity of total-body PET/CT scanners substantially decreases noise, however the full potential for spatio-temporal resolution is still hampered by artefacts and quantification degradation due to patient motion. To compensate for this, a variety of different motion correction methods were developed, but lack a motion free reference. To this end, our group developed a framework enabling Monte Carlo simulations of patient-like phantoms with motion modelling that accurately resembles event processing and image reconstruction of the Biograph Vision Quadra total-body PET/CT scanner. Simulations were performed with the XCAT phantom to mimic a clinical 5 min $\left[{ }^{18} \mathrm{ F}-\mathrm{FDG}\right]$ scan, with modelling of breathing motion with various breathing frequency/amplitude. To evaluate the impact of motion correction, an elastic motion deblurring approach, OncoFreeze AI, was used. Image quality, quantification of 5-20 mm lesions in lung and liver, and lesion line profiles were compared for a static (no motion) reference and for modelled motion with and without correction. Motion induced blurring in the images and could be compensated by the motion correction. The respiratory curve could be recovered by OncoFreeze AI with high precision (difference $\mathrm{Hz} \pm 0.5 \%$ over all motion segments). The motion correction helped to increase the recovery of the static activity concentration, e.g. for a 10 mm lung lesion: $9.4 \mathrm{kBq} / \mathrm{ml}$ (static no motion), $7 \mathrm{kBq} / \mathrm{ml}$ (motion) and $8.3 \mathrm{kBq} / \mathrm{ml}$ (motion corrected) and recovery of the lesion size 8.0 mm FWHM (static no motion) to 13.4 mm (motion) and 8.6 mm (motion corrected). This work underlines the need for motion correction and confirms the suitability of our framework to provide ground truth information on patient motion for total-body PET scans. Future work will extend this initial evaluation to more motion correction methods and a larger, more diverse data set with different scan durations, activities, and lesions.}, author = {Lan, W. and Vo, H. P. and Pommranz, C. and Elmoujarkach, E. and Cabello, J. and Birge, N. and Schleyer, P. and Rafecas, M. and Lafougère, C. and Schmidt, F.}, booktitle = {2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)}, keywords = {nuci}, month = 10, pages = {1-2}, title = {A Simulation Framework to Establish Ground Truth for Motion Correction in Total-Body PET: Initial Evaluation for Complex Respiratory Motion}, year = 2024 }
Vo, H., Pommranz, C., Schmidt, F. P. and Rafecas, M.: Towards Enhancing Auxiliary Lymph Node Detection Using a Breast Insert with a Whole-Body PET/MRI Scanner, 1–2, 2024, DOI: 10.1109/NSS/MIC/RTSD57108.2024.10657626.
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@inproceedings{10657626, abstract = {In general, breast PET inserts are designed to improve the detection capability for small lesions and early metastases. Expanding on prior research, the insert our group is developing aims to enhance the spatial resolution of axillary lymph nodes beyond the insert’s field-of-view (FOV) via the combination with a clinical whole-body (WB) PET scanner. To explore this potential, Monte Carlo simulations were conducted using Na-22 point sources positioned outside of the insert’s FOV to mimic real lymph node locations. A dedicated reconstruction was developed to accommodate different types of coincidences in this hybrid setup, and the system model was partially validated using a phantom of uniformly distributed activity. Results indicate that, while the WB-PET’s spatial resolution may degrade due to insert attenuation, the combination of conventional WB-PET coincidences and mixed coincidences from both systems enhances spatial resolution in terms of full-width at half-maximum in x-direction, and also helps to mitigate the negative effects of the insert in y-direction. Future steps include a comprehensive assessment of image quality, refinement of the reconstruction algorithm to include the solid angle effect, and evaluation of image performance with realistic phantoms.}, author = {Vo, H.P. and Pommranz, C. and Schmidt, F. P. and Rafecas, M.}, booktitle = {2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)}, keywords = {nuci}, month = 10, pages = {1-2}, title = {Towards Enhancing Auxiliary Lymph Node Detection Using a Breast Insert with a Whole-Body PET/MRI Scanner}, year = 2024 }

2023[ to top ]

Seeger, S., Vo, H., Florack, C., Werner, J., Schmidt, C. and Rafecas, M.: First Images from MERMAID, a Small Aquatic Animal PET Scanner Prototype, 1–1, 2023, DOI: 10.1109/NSSMICRTSD49126.2023.10338697.
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@inproceedings{seeger2023first, author = {Seeger, S. and Vo, H.P. and Florack, C. and Werner, J. and Schmidt, C. and Rafecas, M.}, booktitle = {2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)}, keywords = {MERMAID}, pages = {1-1}, title = {First Images from MERMAID, a Small Aquatic Animal PET Scanner Prototype}, year = 2023 }
Vo, H., Seeger, S., Werner, J. and Rafecas, M.: Towards Full-body Small Aquatic Animal PET: a Simulation Study of MERMAID-v2, 1–1, 2023, DOI: 10.1109/NSSMICRTSD49126.2023.10338525.
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@inproceedings{vo2023towards, author = {Vo, H.P. and Seeger, S. and Werner, J. and Rafecas, M.}, booktitle = {2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)}, keywords = {SeegerSteven}, pages = {1-1}, title = {Towards Full-body Small Aquatic Animal PET: a Simulation Study of MERMAID-v2}, year = 2023 }

2022[ to top ]

Seeger, S., Vo, H. P., Bolke, A. and Rafecas, M.: Characterisation of the Upgraded MERMAID Prototype, a PET/CT Device for Small Aquatic Animals, 1–2, 2022, DOI: 10.1109/NSS/MIC44845.2022.10399085.
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@inproceedings{10399085, author = {Seeger, Steven and Vo, Hong Phuc and Bolke, Andreas and Rafecas, Magdalena}, booktitle = {2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)}, keywords = {MERMAID}, pages = {1-2}, title = {Characterisation of the Upgraded MERMAID Prototype, a PET/CT Device for Small Aquatic Animals}, year = 2022 }

Theses

Hong Phuc Vo, Automatic Health Pattern Recognition based on Vital Body Signals with Deep Learning Approach, Bachelor thesis, Frankfurt University of Applied Sciences, 2020

Hong Phuc Vo, Statistical Image Reconstruction and Evaluation of a dedicated prostate PET scanner, Master thesis, Institute of Medical Engineering, University of Lübeck, 2023