Skip to content Skip to search Skip to footer
Washington University in St. Louis

Computational Medical Imaging and Therapy (CMIT) Lab

Menu
  • Research
    • Ultra-low-count imaging for treatment of cancers
    • Task-specific design of imaging algorithms
    • List-mode SPECT systems
    • No-gold-standard evaluation (NGSE)
    • Using deep learning to advance quantitative PET
    • Physics and deep-learning-based CT-less SPECT
    • Deep-learning-based methods for brain SPECT
    • Other projects
      • Detectors for nuclear-medicine imaging
      • Diffusion MRI
        • PI Biography
      • Computational methods for optical tomography
  • People
  • Open positions
  • Publications
  • News and Fun!
  • Software
    • A Bayesian approach to tissue-fraction estimation for oncological PET segmentation
    • A fully automated modular framework for PET segmentation
    • Simulating SiPM response
    • Image reconstruction in FMT
    • Computational methods for diffuse optical imaging
    • Segmentation and quantification in diffusion MR images
  • Press/media
  • Journal Club
  • Teaching
  • Contact Us

Other projects

In previous studies, we have made contributions to nuclear medicine and other imaging modalities. Two major research projects listed below:

  1. Computational methods for optical tomography
  2. Quantitative diffusion MRI to monitor therapy response in patients with liver metastasis

 

 

  • Research
    • Ultra-low-count imaging for treatment of cancers
    • Task-specific design of imaging algorithms
    • List-mode SPECT systems
    • No-gold-standard evaluation (NGSE)
    • Using deep learning to advance quantitative PET
    • Physics and deep-learning-based CT-less SPECT
    • Deep-learning-based methods for brain SPECT
    • Other projects
      • Detectors for nuclear-medicine imaging
      • Diffusion MRI
      • Computational methods for optical tomography

©2023 Washington University in St. Louis