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PRODID:-//Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系 - ECPv6.15.20//NONSGML v1.0//EN
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X-WR-CALNAME:Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
X-ORIGINAL-URL:https://ece.hku.hk
X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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BEGIN:VTIMEZONE
TZID:Asia/Hong_Kong
BEGIN:STANDARD
TZOFFSETFROM:+0800
TZOFFSETTO:+0800
TZNAME:HKT
DTSTART:20240101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20250827T140000
DTEND;TZID=Asia/Hong_Kong:20250827T150000
DTSTAMP:20260511T191732
CREATED:20250822T025105Z
LAST-MODIFIED:20250822T025217Z
UID:113079-1756303200-1756306800@ece.hku.hk
SUMMARY:RPG Seminar – Calibrationless Reconstruction of Uniformly Undersampled Multi-Channel MR Data with Deep Learning Estimated ESPIRiT Maps
DESCRIPTION:Zoom Link: https://us05web.zoom.us/j/82334736966?pwd=rKsbc5OlbKDaftQ5NbrkvvoohDw5ct.1 \nAbstract\nESPIRiT\, one commonly used parallel imaging reconstruction technique\, forms the images from undersampled MR data using ESPIRiT data using ESPIRiT maps that closely represent coil sensitivity information. Accurate estimation of ESPIRiT maps requires the acquisition of coil sensitivity calibration or autocalibration signals. We develop a U-Net based deep learning model to directly estimate the multi-channel ESPIRiT maps from uniformly undersampled multi-channel multi-slice 2D MR data. The model incorporates coil-subject geometry prior information. It is trained using fully sampled data from the same MR receiving coil system by minimizing a hybrid loss on ESPIRiT maps derived from each dataset with and without spatial alignment to the coil system. The performance of the approach was evaluated using publicly available gradient-echo T1-weighed brain data. \nSpeaker\nSpeaker: Junhao Zhang\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nJunhao Zhang obtained his Bachelor degree in Biomedical Engineering from Xi’an Jiaotong University in 2019. In 2021\, he obtained his Master degree in Biomedical Engineering from Columbia University in the City of New York. He is now pursuing a PhD degree with Prof Ed X Wu in the Department of Electrical and Electronic Engineering. His research focuses on the application of deep learning techniques to MRI reconstruction and dynamic MRI. \nOrganiser\nProf. Ed X Wu \nAll are welcome.
URL:https://ece.hku.hk/events/20250827-2/
LOCATION:Online via Zoom
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/11/rpg-seminar.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20250827T150000
DTEND;TZID=Asia/Hong_Kong:20250827T160000
DTSTAMP:20260511T191732
CREATED:20250822T024243Z
LAST-MODIFIED:20250822T024728Z
UID:113076-1756306800-1756310400@ece.hku.hk
SUMMARY:RPG Seminar – Ultra-low-field magnetization transfer imaging with low specific absorption rate
DESCRIPTION:Zoom Link: https://hku.zoom.us/j/93345117865?pwd=f9VJJMOyiUlAkwOwAe4E5rboouDJIP.1 \n  \nAbstract\nThe recent resurgence of ultra-low-field (ULF) magnetic resonance imaging (MRI) (i.e.\, below 0.1 T) is showing great promise for future clinical applications due to its low cost\, portability\, and accessibility. One significant advantage of ULF MRI is its extremely low specific absorption rate (SAR)\, which makes it possible to use highly flexible frequency (RF) pulses for strong magnetization transfer (MT) saturation and achieve tissue/lesion contrast enhancement. MT imaging provides insights into dipolar coupling and chemical exchange processes between the “bound pool” (i.e.\, macromolecular) and the “free pool” (i.e.\, bulk water)\, and has proven valuable in the diagnosis of demyelinating disease and the evaluation of articular cartilage degeneration and repair. In this seminar\, we present novel techniques for efficient MT imaging with strong MT saturation and extremely low SAR on ULF MRI scanners. \nSpeaker\nSpeaker: Shi Su\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nShi Su received his BEng and MEng degrees in Electrical and Electronic Engineering from Beihang University in 2011 and 2014\, respectively. He is now pursuing a PhD degree with Prof Ed X. Wu in the Department of Electrical and Electronic Engineering. His research focuses on the technical development and application of MRI. \nOrganiser\nProf. Ed X Wu \nAll are welcome.
URL:https://ece.hku.hk/events/20250827-1/
LOCATION:Online via Zoom
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/11/rpg-seminar.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20250827T160000
DTEND;TZID=Asia/Hong_Kong:20250827T170000
DTSTAMP:20260511T191732
CREATED:20250822T031939Z
LAST-MODIFIED:20250822T031939Z
UID:113084-1756310400-1756314000@ece.hku.hk
SUMMARY:RPG Seminar – Ultra-low-field Balanced Steady-state Free Precession MRI at 0.05 Tesla
DESCRIPTION:Zoom Link: https://hku.zoom.us/j/94172535993?pwd=oTH8kZ6eiLvp9a61FDZ21omj70WVaA.1 \n  \nAbstract\nThe high cost and limited accessibility of MRI scanners remain significant barriers to their broader use in clinical settings. This study aims to demonstrate the feasibility of balanced steady-state free precession (bSSFP) imaging at ultra-low-field (ULF) on a highly simplified and low-cost 0.05 Tesla whole-body MRI scanner. The bSSFP protocols demonstrated reasonable image quality at 0.05 Tesla\, allowing visualization of various anatomical structures. The protocols provided a spatial resolution of 2×2×6 mm3 with approximately 5 minutes of scan time per protocol. Good soft tissue contrasts were shown\, facilitating the identification of major tissue types within each structure. This study demonstrates that imaging various anatomical structures with bSSFP at 0.05 Tesla is efficient and feasible. \nSpeaker\nSpeaker: Mr Ding Ye\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nDing Ye received his BEng in Electrical and Electronic Engineering from Liaoning University in 2018 and received his MEng degrees in Electrical and Electronic Engineering from Chongqing University in 2021\, respectively. He is now pursuing a PhD degree with Prof Ed X Wu in the Department of Electrical and Electronic Engineering. His research focuses on the technical development and application of ULF MRI. \nOrganiser\nProf. Ed X Wu \nAll are welcome.
URL:https://ece.hku.hk/events/20250827-3/
LOCATION:Online via Zoom
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/11/rpg-seminar.jpg
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