Improved low-count quantitative PET reconstruction with an iterative neural network

H Lim, IY Chun, YK Dewaraja… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Image reconstruction in low-count PET is particularly challenging because gammas from
natural radioactivity in Lu-based crystals cause high random fractions that lower the …

Do CNNs solve the CT inverse problem?

EY Sidky, I Lorente, JG Brankov… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Objective: This work examines the claim made in the literature that the inverse problem
associated with image reconstruction in sparse-view computed tomography (CT) can be …

Implementation and validation of time-of-flight PET image reconstruction module for listmode and sinogram projection data in the STIR library

N Efthimiou, E Emond, P Wadhwa… - Physics in Medicine …, 2019 - iopscience.iop.org
In this paper, we describe the implementation of support for time-of-flight (TOF) positron
emission tomography (PET) for both listmode and sinogram data in the open source …

Learning with Synthesized Data for Generalizable Lesion Detection in Real Pet Images

X Yang, B Chin, M Silosky, D Litwiller, D Ghosh… - … Conference on Medical …, 2023 - Springer
Deep neural networks have recently achieved impressive performance of automated
tumor/lesion quantification with positron emission tomography (PET) imaging. However …

Learning without Real Data Annotations to Detect Hepatic Lesions in Pet Images

X Yang, BB Chin, M Silosky, J Wehrend… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Objective: Deep neural networks have been recently applied to lesion identification in
fluorodeoxyglucose (FDG) positron emission tomography (PET) images, but they typically …

[HTML][HTML] Clinical application of 18F-DOPA PET/TC in pediatric patients

G Masselli, E Casciani, C De Angelis… - American Journal of …, 2021 - ncbi.nlm.nih.gov
Abstract The use 18 F-DOPA PET/CT for oncologic and non-oncologic pediatric diseases is
well consolidated in clinical practice. The indications include brain tumors, neuroendocrine …

Application of trained Deep BCD-Net to iterative low-count PET image reconstruction

H Lim, Z Huang, JA Fessler… - 2018 IEEE Nuclear …, 2018 - ieeexplore.ieee.org
Image reconstruction in low-count PET is challenging because gammas from natural
radioactivity in Lu-based crystals cause high random fractions that lower the measurement …

Improving Generalizability of PET DL Algorithms: List-Mode Reconstructions Improve DOTATATE PET Hepatic Lesion Detection Performance

X Yang, M Silosky, J Wehrend, DV Litwiller… - Bioengineering, 2024 - mdpi.com
Deep learning (DL) algorithms used for DOTATATE PET lesion detection typically require
large, well-annotated training datasets. These are difficult to obtain due to low incidence of …

Simultaneous activity and attenuation estimation in TOF-PET with TV-constrained nonconvex optimization

Z Ren, EY Sidky, RF Barber, CM Kao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
An alternating direction method of multipliers (ADMM) framework is developed for
nonsmooth biconvex optimization for inverse problems in imaging. In particular, the …

Preliminary investigation of optimization-based image reconstruction for TOF PET with sparse configurations

Z Zhang, B Chen, AE Perkins, CM Kao… - … Meeting on Fully …, 2019 - spiedigitallibrary.org
In this work, we investigate and characterize optimization-based image reconstruction from
list-mode TOFPET data collected by using a digital TOF-PET scanner with reduced …