Dr. Siqi Li presented his recent work on a deep kernel method for PET image reconstruction at the SPIE Medical Imaging 2022 held in San Diego. This is his first time presenting in person at an international conference in the pandemic, though he already presented three other talks virtually at IEEE-MIC 2021, SPIE Medical Imaging 2021, and Fully 3D 2021. Well done, Siqi!

Our Liver Parametric PET work for imaging fatty liver disease (in close collaboration with Souvik Sarkar MD and other colleagues at UC Davis Medical Center) was recently highlighted by UC Davis Health and also featured as Top Story on SNMMI SmartBrief newsletters.

UC Davis Health Newsroom: New PET imaging-based tool detects liver inflammation from fatty liver disease

SNMMI SmartBrief: PET-based tool detects liver inflammation in NAFLD

Yiran Wang, a Ph.D. student of Dr. Guobao Wang and Dr. Simon Cherry, won the IEEE NPSS Christopher J Thompson Student Awards “2nd Best Oral Paper” at the 2021 IEEE Medical Imaging Conference. His paper

Y Wang, E Berg, Y Zuo, E Li, BA Spencer, RD Badawi, SR Cherry, GB Wang. Voxel-wise kinetic model selection using single-subject deep learning for total-body PET parametric imaging. 2021 Virtual IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS&MIC), October 16-23, 2021.

is one of the two Best Oral Papers that were selected from 141 student applicants.

Yiran has been working on total-body PET kinetic modeling and parametric imaging and exploring deep learning approaches in this area. In this work, Yiran developed a single-subject deep learning approach to address the voxel-wise model selection problem for total-body PET parametric imaging on EXPLORER. His approach uses a small fraction of voxels from a subject to build a temporal neural network model and then applies the learned model to fast predict the appropriate kinetic model type of a vast amount of voxels of the same subject. As compared to a standard solution, the deep-learning approach leads to improved total-body PET parametric images with reduced artifacts without a significant increase in computational time.

This work is supported in part by NIH grants R01 CA206187, R01DK124803.

Congratulations, Yiran!

Yiran, Siqi, and Yansong have three conference submissions accepted by the 2021 IEEE Nuclear Science Symposium & Medical Imaging Conference (NSS&MIC):

• Y Wang, E Berg, Y Zuo, E Li, BA Spencer, RD Badawi, SR Cherry, G Wang. Voxel-Wise Kinetic Model Selection Using Single-Subject Deep Learning for Total-Body PET Parametric Imaging, IEEE NSS&MIC, Oct 2021, accepted for oral presentation.
• S Li, K Gong, J Qi, G Wang. Neural KEM for PET Image Reconstruction, IEEE NSS&MIC, Oct 2021, accepted for oral presentation.
• Y Zhu, G Wang. Statistical CT sinogram generation from time-of-flight PET data using kernel methods in the projection space, IEEE NSS&MIC, Oct 2021, accepted for mini-oral presentation.

Elizabeth (of the Cherry Lab) also has a paper accepted:

• EJ Li, E Berg, Y Wang, BA Spencer, RD Badawi, AF Tarantal, G Wang, SR Cherry, CNN-based time delay estimation in dynamic total-body PET kinetic modeling, IEEE NSS&MIC, Oct 2021, accepted for poster presentation.

Graduate student Yiran Wang successfully passed his Qualifying Exam. He is now a Ph.D. candidate! Congratulations, Yiran.

Dr. Yansong Zhu is joining our lab starting from February 1st. He received his Ph.D. in Electrical and Computer Engineering from Johns Hopkins University in 2020. During his PhD research in the lab of Quantitative Radiomolecular Imaging and Therapy, Yansong developed improved physical modeling and image reconstruction algorithms for fluorescence molecular tomography and partial volume correction algorithms for brain PET/MR imaging. We are looking forward to working together on exciting projects.

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!

Dr. Yang Zuo, a postdoctoral scholar in our lab, is joining the University of Science and Technology of China (USTC) as a new faculty member there, starting in December 2020. During her time in our lab, Yang made significant contributions to several different projects, including the multiparametric cardiac PET, liver parametric PET, and relative Patlak plot. Thank Yang for all the contributions and wish her all the best in her faculty career!

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!

Our Liver Parametric PET project has been formally funded by an R01 grant from NIH/NIDDK.

Co-investigators include Souvik Sarkar MD (hepatology), Michael Corwin MD (Radiology), Ramsey D. Badawi PhD (Radiology), Karen Matsukuma MD (Pathology), Jinyi Qi PhD (Biomedical Engineering), and Shuai Chen PhD (Biostatistics).