8 citations · 11 across the 5 of their papers we have counts for
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Beyond the Tumor: Recurrence-Prone Radiomics for Prognostication in Negative PSMA PET/CT scans of Prostate Cancer
Fereshteh Yousefirizi, Sara Harsini, Mobin Mohebi +14
In patients with biochemical recurrence of prostate cancer and negative PSMA PET/CT, radiomics features extracted from recurrence-prone organs can predict clinical progression and…
Uncertainty Propagation from Projections to Region Counts in Tomographic Imaging: Application to Radiopharmaceutical Dosimetry
Lucas Polson, Sara Kurkowska, Chenguang Li +6
Radiopharmaceutical therapies (RPTs) present a major opportunity to improve cancer therapy. Although many current RPTs use the same injected activity for all patients, there is int…
Computationally Efficient Collimator-Detector Response Compensation in High Energy SPECT using 1D Convolutions and Rotations
Lucas Polson, Pedro Esquinas, Sara Kurkowska +7
Modeling of the collimator-detector response (CDR) in SPECT reconstruction enables improved resolution and accuracy, and is thus important for quantitative imaging applications suc…
Deep learning-based noise reduction in low dose SPECT Myocardial Perfusion Imaging: Quantitative assessment and clinical performance
Narges Aghakhan Olia, Alireza Kamali-Asl1, Sanaz Hariri Tabrizi +4
Clinical SPECT-MPI images of 345 patients acquired from a dedicated cardiac SPECT in list-mode format were retrospectively employed to predict normal-dose images from low-dose data…
Deep-Fill: Deep Learning Based Sinogram Domain Gap Filling in Positron Emission Tomography
Isaac Shiri, Peyman Sheikhzadeh, Mohammad Reza Ay
One of the major challenges in design and developing of PET, scanners are the presence of inactive areas between the detector blocks which degrade the image spatial resolution and…