A review of deep learning based methods for medical image multi-organ segmentation
Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …
performance in many medical image segmentation tasks. Many deep learning-based …
Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods
The rapid expansion of machine learning is offering a new wave of opportunities for nuclear
medicine. This paper reviews applications of machine learning for the study of attenuation …
medicine. This paper reviews applications of machine learning for the study of attenuation …
MRI‐only based synthetic CT generation using dense cycle consistent generative adversarial networks
Purpose Automated synthetic computed tomography (sCT) generation based on magnetic
resonance imaging (MRI) images would allow for MRI‐only based treatment planning in …
resonance imaging (MRI) images would allow for MRI‐only based treatment planning in …
Deep learning-based attenuation correction in the absence of structural information for whole-body positron emission tomography imaging
Deriving accurate structural maps for attenuation correction (AC) of whole-body positron
emission tomography (PET) remains challenging. Common problems include truncation …
emission tomography (PET) remains challenging. Common problems include truncation …
Whole-body PET estimation from low count statistics using cycle-consistent generative adversarial networks
Lowering either the administered activity or scan time is desirable in PET imaging as it
decreases the patient's radiation burden or improves patient comfort and reduces motion …
decreases the patient's radiation burden or improves patient comfort and reduces motion …
MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method
Magnetic resonance imaging (MRI) has been widely used in combination with computed
tomography (CT) radiation therapy because MRI improves the accuracy and reliability of …
tomography (CT) radiation therapy because MRI improves the accuracy and reliability of …
Evaluation of a deep learning-based pelvic synthetic CT generation technique for MRI-based prostate proton treatment planning
The purpose of this work is to validate the application of a deep learning-based method for
pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy …
pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy …
Artificial intelligence in multiparametric magnetic resonance imaging: A review
Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the
clinical workflow for the diagnosis and treatment planning of various diseases. Machine …
clinical workflow for the diagnosis and treatment planning of various diseases. Machine …
Deep learning-based image quality improvement for low-dose computed tomography simulation in radiation therapy
Low-dose computed tomography (CT) is desirable for treatment planning and simulation in
radiation therapy. Multiple rescanning and replanning during the treatment course with a …
radiation therapy. Multiple rescanning and replanning during the treatment course with a …
[HTML][HTML] Machine-learning based classification of glioblastoma using delta-radiomic features derived from dynamic susceptibility contrast enhanced magnetic …
Background Glioblastoma is the most aggressive brain tumor with poor prognosis. The
purpose of this study is to improve the tissue characterization of these highly heterogeneous …
purpose of this study is to improve the tissue characterization of these highly heterogeneous …