Projects in Progress

Photon-counting CT and Optical Molecular Tomography

The goal is to develop a preclinical x-ray and optical prototype for High-dimensional Optical Tomography (HOT) Guided-by Energy-resolved Micro-CT (GEM), visualize breast tumor heterogeneity, HER2 expression and dimerization, and therapeutic response in mice.

  • Grant: NIH/NCI R01CA237267
  • Multi-PIs: Ge Wang*, Xavier Intes, Barroso, Margarida (Albany Medical Center)
  • Project schedule: 09/01/2019 – 08/31/2024
  • For more details, visit website

Constrained Disentanglement for CT Metal Artifact Reduction

The goal is to develop deep learning algorithms for CT metal artifact reduction in the context of proton therapy.

  • Grant: NIH/NIBIB R01EB031102
  • Multi-PIs: Ge Wang*, Bruno De Man (GE), Harald Paganetti (Harvard)
  • Project schedule: 09/01/2021 – 08/31/2024
  • For more details, visit website

Adversarially Based Virtual CT Workflow for Evaluation of AI Imaging

The goal is to develop an FDA workflow evaluating, approving, and monitoring AI imaging software. This project would be a key element in the future healthcare metaverse.

  • Grant: NIH/NIBIB R01EB032716
  • Multi-PIs: Ge Wang*, Klaus Mueller (Stony Brook), Xun Jia (JHU), Rongping Zeng (FDA)
  • Project schedule: 04/01/2022 – 03/31/2026
  • For more details, visit website

Cardiac CT Deblooming

The goal is to use deep learning to eliminate blooming artifacts in cardiac CT images without costly redesign of the CT hardware. This will be based on a dual-domain workflow from sinogram processing through image reconstruction to image analysis.

  • Grant: NIH/NIBIB R01HL151561
  • Multi-PIs: Bruno De Man* (GE), Ge Wang, James Min (Cleerly/Cornell)
  • Project schedule: 04/01/2020 – 06/30/2024

SPECT with a Compton Camera for Thyroid Cancer Imaging

This goal is to design a high-efficiency and high-quality Compton camera based tomographic imaging system.

  • Grant: NIH/NCI R21CA264772
  • MPIs: Hengyong Yu*, Ge Wang
  • Project schedule: 05/01/2021 – 04/30/2023

Bio-tissue Oxygenation Nanophosphor Enabled Sensing (BONES)

The goal is to develop radiomics/rawdiomics for personalized treatment of colorectal liver metastases.

  • Grant: NIH/NIGMS R42GM142394
  • Sub-PI: Wang
  • Project schedule: 06/01/2021 – 11/30/2023

Focused X-ray Luminescence Tomography

The goal is to develop the first-of-its-kind focused x-ray luminescence tomography (FXLT) scanner to “slice” deep cancers/tissues sensitively and longitudinally at 150μm resolution at a radiation dose comparable to that of a regular micro-CT scan.

  • Grant: NIH/NIBIB R01EB026646
  • Sub-PI: Wang
  • Project schedule: 07/01/2018 – 03/31/2022

Radiomic Markers of Response and Recurrence for Cancer Patients

The goal is to develop and validate robust imaging features by standardizing image acquisition, improve automated tools for clinical trial use, and validate the predictive power of imaging features with external data.

  • Grant: NIH/NCI R01CA233888
  • Sub-PI: Wang
  • Project schedule: 03/01/2019 – 08/31/2024

Deep Learning for Medical CT

The goal is to develop medical CT algorithms.

  • Industrial grant: General Electric (USA)
  • PI: Wang
  • Project schedule: 01/01/2021– 12/31/2022

Preclinical Micro-CT

The goal is to develop preclinical micro-CT algorithms.

  • Industrial grant: FirstImaging (Shanghai, China)
  • PI: Wang
  • Project schedule: 01/01/2021– 12/31/2021

Projects in Preparation

Temporal Bone CT With Interior, Deep and Robotic Imaging

The goal is to develop a robotic clinical micro-CT system with cutting-edge x-ray source and photon-counting detector technologies for temporal bone imaging.

Auto-driving Vehicle for Affordable Tomo-Analytic Robots (AVATAR)

For more details, please click the following links: