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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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Quantitative Tomography Lab
Reblogged this on Quantitative Tomography Lab and commented:
The published abstracts can now be found here:
https://rahmimlab.com/publications/conference_proceedings/