Evaluation of Deep Learning–Based Approaches to Segment Bowel Air Pockets and Generate Pelvic Attenuation Maps from CAIPIRINHA-Accelerated Dixon MR …
Attenuation correction remains a challenge in pelvic PET/MRI. In addition to the
segmentation/model-based approaches, deep learning methods have shown promise in …
segmentation/model-based approaches, deep learning methods have shown promise in …
Feasibility of deep learning–based PET/MR attenuation correction in the pelvis using only diagnostic MR images
This study evaluated the feasibility of using only diagnostically relevant magnetic resonance
(MR) images together with deep learning for positron emission tomography (PET)/MR …
(MR) images together with deep learning for positron emission tomography (PET)/MR …
Zero-echo-time and Dixon deep pseudo-CT (ZeDD CT): direct generation of pseudo-CT images for pelvic PET/MRI attenuation correction using deep convolutional …
Accurate quantification of uptake on PET images depends on accurate attenuation
correction in reconstruction. Current MR-based attenuation correction methods for body PET …
correction in reconstruction. Current MR-based attenuation correction methods for body PET …
Direct pseudoCT generation for pelvis PET/MRI attenuation correction using deep convolutional neural networks with multi-parametric MRI: zero echo-time and dixon …
Accurate quantification of positron emission tomography (PET) uptake depends on accurate
attenuation correction in reconstruction. Current magnetic resonance-based attenuation …
attenuation correction in reconstruction. Current magnetic resonance-based attenuation …
[HTML][HTML] Evaluating a radiotherapy deep learning synthetic CT algorithm for PET-MR attenuation correction in the pelvis
JJ Wyatt, S Kaushik, C Cozzini, RA Pearson, G Petrides… - EJNMMI physics, 2024 - Springer
Background Positron emission tomography–magnetic resonance (PET-MR) attenuation
correction is challenging because the MR signal does not represent tissue density and …
correction is challenging because the MR signal does not represent tissue density and …
Dixon-VIBE deep learning (DIVIDE) pseudo-CT synthesis for pelvis PET/MR attenuation correction
A Torrado-Carvajal, J Vera-Olmos… - Journal of nuclear …, 2019 - Soc Nuclear Med
Whole-body attenuation correction (AC) is still challenging in combined PET/MR scanners.
We describe Dixon-VIBE Deep Learning (DIVIDE), a deep-learning network that allows …
We describe Dixon-VIBE Deep Learning (DIVIDE), a deep-learning network that allows …
mDixon-based synthetic CT generation for PET attenuation correction on abdomen and pelvis jointly using transfer fuzzy clustering and active learning-based …
P Qian, Y Chen, JW Kuo, YD Zhang… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
We propose a new method for generating synthetic CT images from modified Dixon
(mDixon) MR data. The synthetic CT is used for attenuation correction (AC) when …
(mDixon) MR data. The synthetic CT is used for attenuation correction (AC) when …
[HTML][HTML] Pelvic PET/MR attenuation correction in the image space using deep learning
BS Abrahamsen, IS Knudtsen, L Eikenes… - Frontiers in …, 2023 - ncbi.nlm.nih.gov
Methods A convolutional neural network was trained to predict the four-class AC error map
relative to CT-based attenuation correction. Dixon MR images and the four-class attenuation …
relative to CT-based attenuation correction. Dixon MR images and the four-class attenuation …
A female pelvic bone shape model for air/bone separation in support of synthetic CT generation for radiation therapy
Separating bone from air in MR data is one of the major challenges in using MR images to
derive synthetic CT. The problem is further complicated when the anatomic regions filled …
derive synthetic CT. The problem is further complicated when the anatomic regions filled …
Semi-automatic synthetic computed tomography generation for abdomens using transfer learning and semi-supervised classification
J Zheng, J Cao, Z Wang, F Liu, S Wang… - Journal of Medical …, 2019 - ingentaconnect.com
We proposed a new semi-automatic method for generating synthetic CT images from
modified Dixon (mDixon) MR data of abdomens to address the challenges of PET/MR …
modified Dixon (mDixon) MR data of abdomens to address the challenges of PET/MR …
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