Noise reduction with cross-tracer transfer deep learning for low-dose oncological PET
108 Objectives: Deep convolutional neural networks can be robust and effective in noise
reduction for low-dose FDG PET thanks to large amount of training datasets. However …
reduction for low-dose FDG PET thanks to large amount of training datasets. However …
Investigation of lesion detectability using deep learning based denoising methods in oncology PET: a cross-center phantom study
430 Objectives: Previous studies have demonstrated promising performance in reducing
noise in low-statistics PET images when using a deep convolutional neural network (CNN) …
noise in low-statistics PET images when using a deep convolutional neural network (CNN) …
Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET
Previous studies have demonstrated the feasibility of reducing noise with deep learning-
based methods for low-dose fluorodeoxyglucose (FDG) positron emission tomography …
based methods for low-dose fluorodeoxyglucose (FDG) positron emission tomography …
Noise adaptive deep convolutional neural network for whole-body pet denoising
Many factors can impact PET image noise levels including injected dose, wait time, patient's
BMI, scan duration etc.. These factors can lead to a large spatial variation and inter-patient …
BMI, scan duration etc.. These factors can lead to a large spatial variation and inter-patient …
Comparative assessment of attention-based deep learning and non-local mean filtering for joint noise reduction and partial volume correction in low-dose PET …
2729 Introduction: Partial volume effects (PVE) and high noise characteristics of PET images
are two major challenges facing quantitative PET imaging. In this work, we assessed the …
are two major challenges facing quantitative PET imaging. In this work, we assessed the …
Noise and Signal Characteristics of Deep Learning-Based Denoising for a SiPM-based PET/CT Scanner
436 Objectives: Deep convolutional neural networks (DCNN) can be trained to adapt to
different noise levels in input PET images and produce consistent denoised results across …
different noise levels in input PET images and produce consistent denoised results across …
Deep learning-based denoising for PennPET Explorer data
574 Objectives: Promising results have been reported for low-statistics PET data denoising
using a deep convolutional neural network (CNN) with standard-statistics images as the …
using a deep convolutional neural network (CNN) with standard-statistics images as the …
The impact of noise level mismatch between training and testing images for deep learning-based PET denoising
109 Objectives: Deep-learning methods have been applied in PET image denoising.
However, when the noise level in the training and testing images are different, a deep …
However, when the noise level in the training and testing images are different, a deep …
A 3D noise-level-aware network for low-dose PET imaging
P791 Introduction: Positron emission tomography (PET) can provide insight into both the
biochemical and physiological processes of the human body and is widely used in …
biochemical and physiological processes of the human body and is widely used in …
Denoising low-count PET images Using a dilated convolutional neural network for kinetic modeling
437 Objectives: Quantitatively accurate PET images are essential in psychiatric studies to
assess subtle differences between diseases. Recently, development of denoising …
assess subtle differences between diseases. Recently, development of denoising …
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