Presentations at 2019 SNMMI Annual Meeting

Eight accepted works by our group and collaborators (4 oral; 4 posters) are being presented at the 2019 Annual Meeting of the Society of Nuclear Medicine & Molecular Imaging (SNMMI) in Anaheim, June 22-25:

  • K. H. Leung, S. Ashrafinia, M. S. Sadaghiani, P. Dalaie, R. Tulbah, Y. Yin, R. VanDenBerg, J. P. Leal, M. A. Gorin, Y. Du, M. G. Pomper, S. P. Rowe, and A. Rahmim
    A fully automated deep-learning based method for lesion segmentation in 18F-DCFPyL PSMA PET images of patients with prostate cancer
  • Y. Zhu, Y. Gao, O. Rousset, D. F. Wong, and A. Rahmim
    Post-reconstruction MRI-guided enhancement of PET images using parallel level set method with Bregman iteration
  • J. Kim, S. Seo, S. Ashrafinia, A. Rahmim, V. Sossi, and I. S. Klyuzhin
    Training of deep convolutional neural nets to extract radiomic signatures of tumors
  • P. E. Bravo, B. Fuchs, A. K Tahari, D. Pryma, J. Dubroff, and A. Rahmim
    Quantitative renal PET imaging with Rubidium-82 can discriminate individuals with different degrees of renal impairment
  • S. Ashrafinia, M. S. Sadaghiani, P. Dalaie, R. Tulbah, Y. Yin, K. H. Leung, R. VanDenBerg, J. P. Leal, M. A. Gorin, M. G. Pomper, A. Rahmim, and S. P. Rowe
    Characterization of segmented 18F-DCFPyL PET/CT lesions in the context of PSMA-RADS structured reporting
  • I. Shiri, K. H. Leung, P. Ghafarian, P. Geramifar, M. Oveisi, M. R. Ay, and A. Rahmim
    HiResPET: high resolution PET image generation using deep convolution encoder decoder network
  • I. Shiri, K H. Leung, P. Geramifar, P. Ghafarian, M. Oveisi, M. Reza Ay, and A. Rahmim
    PSFNET: ultrafast generation of PSF-modelled-like PET images using deep convolutional neural network
  • I. Shiri, K. H. Leung, P. Ghafarian, P. Geramifar, M. Oveisi, M. R. Ay, and A. Rahmim
    Simultaneous attenuation correction and reconstruction of PET images using deep convolutional encoder decoder networks from emission data

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