AIMC Topic: Positron-Emission Tomography
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Deep-learning-based attenuation correction in dynamic [O]HO studies using PET/MRI in healthy volunteers.
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Jul 11, 2021
Quantitative [O]HO positron emission tomography (PET) is the accepted reference method for regional cerebral blood flow (rCBF) quantification. To perform reliable quantitative [O]HO-PET studies in PET/MRI scanners, MRI-based attenuation-correction (M...
Rapid high-quality PET Patlak parametric image generation based on direct reconstruction and temporal nonlocal neural network.
NeuroImage
Jul 9, 2021
Parametric imaging based on dynamic positron emission tomography (PET) has wide applications in neurology. Compared to indirect methods, direct reconstruction methods, which reconstruct parametric images directly from the raw PET data, have superior ...
Artificial Intelligence for PET Image Reconstruction.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Jul 8, 2021
Assessment of deep learning-based PET attenuation correction frameworks in the sinogram domain.
Physics in medicine and biology
Jul 7, 2021
This study set out to investigate various deep learning frameworks for PET attenuation correction in the sinogram domain. Different models for both time-of-flight (TOF) and non-TOF PET emission data were implemented, including direct estimation of th...
A transfer learning approach to facilitate ComBat-based harmonization of multicentre radiomic features in new datasets.
PloS one
Jul 1, 2021
PURPOSE: To facilitate the demonstration of the prognostic value of radiomics, multicenter radiomics studies are needed. Pooling radiomic features of such data in a statistical analysis is however challenging, as they are sensitive to the variability...
Follow-Up Studies
Magnetic Resonance Imaging
Cervix Uteri
Decision Support Systems, Clinical
Treatment Outcome
Aged
Chemoradiotherapy
Aged, 80 and over
Positron-Emission Tomography
Young Adult
Retrospective Studies
Image Interpretation, Computer-Assisted
Humans
Adult
Tomography, X-Ray Computed
Datasets as Topic
Machine Learning
Uterine Cervical Neoplasms
Female
Middle Aged
Artificial intelligence in medical imaging: implications for patient radiation safety.
The British journal of radiology
Jun 23, 2021
Artificial intelligence, including deep learning, is currently revolutionising the field of medical imaging, with far reaching implications for almost every facet of diagnostic imaging, including patient radiation safety. This paper introduces basic ...
Automated Data Quality Control in FDOPA brain PET Imaging using Deep Learning.
Computer methods and programs in biomedicine
Jun 22, 2021
INTRODUCTION: With biomedical imaging research increasingly using large datasets, it becomes critical to find operator-free methods to quality control the data collected and the associated analysis. Attempts to use artificial intelligence (AI) to per...
The predictive power of artificial intelligence on mediastinal lymphnode metastasis.
General thoracic and cardiovascular surgery
Jun 16, 2021
OBJECTIVE: The aim of this study was to create the preoperative predictive model on mediastinal lymph-node metastasis based on artificial intelligence in surgically resected lung adenocarcinoma.
Deep learning for whole-body medical image generation.
European journal of nuclear medicine and molecular imaging
May 22, 2021
BACKGROUND: Artificial intelligence (AI) algorithms based on deep convolutional networks have demonstrated remarkable success for image transformation tasks. State-of-the-art results have been achieved by generative adversarial networks (GANs) and tr...
A Multiprocessing Scheme for PET Image Pre-Screening, Noise Reduction, Segmentation and Lesion Partitioning.
IEEE journal of biomedical and health informatics
May 11, 2021
Accurate segmentation and partitioning of lesions in PET images provide computer-aided procedures and doctors with parameters for tumour diagnosis, staging and prognosis. Currently, PET segmentation and lesion partitioning are manually measured by ra...
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