2020/12: Dr. Quyen Tran Joining the Lab

Dr. Quyen Tran is joining our lab, starting February 1st, 2021. Dr. Tran obtained his Ph.D. in Mathematics from the Vietnam Academy of Science and Technology in 2013. He was an Alexander von Humboldt Fellow at the University of Hamburg, Germany, and a Postdoctoral Fellow at the University of Goettingen, Germany, and received Habilitation in 2019. He has a strong background in differential equations and inverse problems. We are looking forward to working with him together!

2020/11: Liver Imaging Symposium Successfully Held

The virtual 2020 UC Davis Liver Imaging Symposium – Innovations in Liver Imaging: From Byte to Bedside, co-chaired by Dr. Souvik Sarkar and Dr. Guobao Wang, was successfully held on November 17th, 2020. The symposium is jointly sponsored by the Department of Internal Medicine, Department of Radiology, and the UCD Comprehensive Cancer Center. It consisted of ten excellent scientific talks and a panel discussion. The symposium attracted a good attendance (peaked at ~90 participants attending the scientific sessions and ~65 attendees in the last panel discussion session). We thank all the organizers, speakers, and attendees!

2020/07: IEEE MIC abstract acceptance on PET kinetic modeling and deep-learning low-dose CT

Dr. Yang Zuo, Dr. Siqi Li, and graduate student Yiran Wang have three conference submissions accepted by the 2020 IEEE Nuclear Science Symposium & Medical Imaging Conference (NSS&MIC), all for oral presentation. The topics relate to PET kinetic modeling and deep-learning low-dose CT respectively.

  • Y Zuo, RD Badawi, CC Foster, T Smith, JE Lopez, GB Wang. Multiparametric Cardiac 18F-FDG PET in Humans: Kinetic Model Selection and Parametric Imaging. IEEE NSS&MIC, November 2020. accepted for oral presentation.
  • S Li, GB Wang. Parallel-Clone Networks for Deep-Learning Image Denoising in Low-Dose CT. IEEE NSS&MIC, November 2020. accepted for oral presentation.
  • Y Wang, Y Zuo, BA Spencer, J Schmall, RD Badawi, SR Cherry, GB Wang. Effect of Time Delay and Dual Blood Input on Liver Kinetic Quantification Using High-Temporal Resolution Dynamic PET. IEEE NSS&MIC, November 2020. accepted for oral presentation.

Graduate student Elizabeth Li, who is in the Cherry lab and co-supervised by Guobao Wang, also has her work on kinetic modeling accepted for oral presentation.

  • E Li, BA Spencer, JP Schmall, GB Wang, and SR Cherry. Pulse-timing methods for time delay estimation in dynamic total-body PET kinetic modeling. IEEE NSS&MIC, November 2020. accepted for oral presentation.

2020/07: Yiran Wang received Honorable Mention from SNMMI PIDSC Young Investigator Award Symposium

Yiran Wang, a second-year graduate student jointly supervised by Dr. Guobao Wang and Dr. Simon Cherry, received an Honorable Mention from the 2020 SNMMI PIDSC Young Investigator Award Symposium on July 12. His conference abstract “Effect of dual-input function and dispersion on lung FDG-PET kinetic quantification using the EXPLORER total-body PET/CT scanner” is one of the six abstracts selected from a total 129 abstracts from young investigators in the SNMMI Physics, Instrumentation, and Data Sciences Council (PIDSC). Well-done and congratulations, Yiran!

2020/07: SNMMI Press Release – Total-Body Dynamic PET of Metastatic Cancer

The Society of Nuclear Medicine and Molecular Imaging (SNMMI) selected our work on total-body dynamic PET of metastatic cancer that has been recently presented in the 2020 Annual Meeting for a press release:

https://www.snmmi.org/NewsPublications/NewsDetail.aspx?ItemNumber=34153

This work reports the first patient results from our study of total-body 18F-FDG dynamic PET of metastatic cancer. The study is ongoing in the EXPLORER Molecular Imaging Center with support from the UC Davis Cancer Center.

2020/04: Undergraduate Jesse to present deep-learning ultralow-dose CT quantification

Jesse Ahlquist has recently had a conference submission accepted by SNMMI 2020 Annual Meeting for oral presentation.  His work investigates the potential of state-of-the-art deep learning noise reduction for improving ultralow-dose CT imaging. A specific significance of his work is for total-body PET/CT imaging using the EXPLORER scanner in the context of liver quantification (see a figure from his work).

Jesse was an undergraduate student and graduated in December 2019. We wish him all the best for his next adventure!

2020/04: SNMMI 2020 acceptance on total-body PET kinetic modeling

We have four conference submissions accepted by the 2020 Annual Meeting of SNMMI (Society of Nuclear Medicine and Molecular Imaging), all for oral presentation. Three of these submissions are on total-body PET kinetic modeling:

  • Zuo Y, Cherry SR, Badawi RD, Wang GB. Multiphase Patlak Plot Enabled by High Temporal Resolution Total-body Dynamic PET. SNMMI 2020 Annual Meeting, June 2020. accepted for oral presentation.
  • Wang Y, Cherry SR, Badawi RD, Wang GB. Effect of dual-input function and dispersion on lung FDG-PET kinetic quantification using the EXPLORER total-body PET/CT scanner. SNMMI 2020 Annual Meeting, June 2020. accepted for oral presentation.
  • Wang GB, Parikh M, Nardo L, Zuo Y, Abdelhafez YG, Qi J, Jones T, Price PM, Cherry SR, Pan CX, Badawi RD. Total-Body Dynamic PET of Metastatic Cancer: First Patient Results. SNMMI 2020 Annual Meeting, June 2020. accepted for oral presentation.

Another one is on deep-learning low-dose CT:

  • Ahlquist J, Abdelhafez YG, Nardo L, Badawi RD, Qi J, Wang GB. Ultralow-Dose CT Imaging with Deep Learning Noise Reduction on the EXPLORER Total-Body PET/CT Scanner. SNMMI 2020 Annual Meeting, June 2020. accepted for oral presentation.

Thanks to everyone for your hard and smart work!