Accelerated SPECT image reconstruction with a convolutional neural network
1351 Purpose: Image-guided procedures involving radionuclides, such as hepatic
radioembolization, would benefit from the availability of SPECT/CT during intervention by …
radioembolization, would benefit from the availability of SPECT/CT during intervention by …
[HTML][HTML] Accelerated SPECT image reconstruction with FBP and an image enhancement convolutional neural network
MMA Dietze, W Branderhorst, B Kunnen, MA Viergever… - EJNMMI physics, 2019 - Springer
Abstract Background Monte Carlo-based iterative reconstruction to correct for photon scatter
and collimator effects has been proven to be superior over analytical correction schemes in …
and collimator effects has been proven to be superior over analytical correction schemes in …
[PDF][PDF] Improved low count quantitative SPECT reconstruction with a trained deep learning based regularizer
Improved low count quantitative SPECT reconstruction with a trained deep-learning based
regularizer Page 1 Improved low count quantitative SPECT reconstruction with a trained …
regularizer Page 1 Improved low count quantitative SPECT reconstruction with a trained …
SPECT image reconstruction by deep learning using a two-step training method
1353 Objectives: Machine learning technique has been widely used for image analysis and
outcome prediction in the field of medical imaging. Recently it was also implemented in CT …
outcome prediction in the field of medical imaging. Recently it was also implemented in CT …
SPECT image reconstruction by a learnt neural network
1478 Objectives: SPECT is an important functional imaging modality. It is less expensive
and more prevalent than other functional imaging modalities such as PET and fMRI, but …
and more prevalent than other functional imaging modalities such as PET and fMRI, but …
Spect imaging reconstruction method based on deep convolutional neural network
C Chrysostomou, L Koutsantonis… - 2019 IEEE Nuclear …, 2019 - ieeexplore.ieee.org
In this paper, we explore a novel method for tomographic image reconstruction in the field of
SPECT imaging. Deep Learning methodologies and more specifically deep convolutional …
SPECT imaging. Deep Learning methodologies and more specifically deep convolutional …
A reconstruction method based on deep convolutional neural network for spect imaging
C Chrysostomou, L Koutsantonis… - 2018 IEEE Nuclear …, 2018 - ieeexplore.ieee.org
We explore a novel method for tomographic image reconstruction in the field of Single
Photon Emission Computerized Tomography (SPECT) imaging. Deep Learning …
Photon Emission Computerized Tomography (SPECT) imaging. Deep Learning …
Deep convolutional neural network for low projection spect imaging reconstruction
C Chrysostomou, L Koutsantonis… - 2020 IEEE Nuclear …, 2020 - ieeexplore.ieee.org
In this paper, we present a novel method for tomographic image reconstruction in SPECT
imaging with a low number of projections. Deep convolutional neural networks (CNN) are …
imaging with a low number of projections. Deep convolutional neural networks (CNN) are …
A Convolutional Neural Network for SPECT Image Reconstruction
Z Guan - 2022 - search.proquest.com
Purpose: Single photon emission computed tomography (SPECT) is considered as a
functional nuclear medicine imaging technique which is commonly used in the clinic …
functional nuclear medicine imaging technique which is commonly used in the clinic …
[HTML][HTML] 90Y SPECT scatter estimation and voxel dosimetry in radioembolization using a unified deep learning framework
Purpose 90Y SPECT-based dosimetry following radioembolization (RE) in liver
malignancies is challenging due to the inherent scatter and the poor spatial resolution of …
malignancies is challenging due to the inherent scatter and the poor spatial resolution of …