AIMC Topic: Positron-Emission Tomography
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True ultra-low-dose amyloid PET/MRI enhanced with deep learning for clinical interpretation.
European journal of nuclear medicine and molecular imaging
Jan 8, 2021
PURPOSE: While sampled or short-frame realizations have shown the potential power of deep learning to reduce radiation dose for PET images, evidence in true injected ultra-low-dose cases is lacking. Therefore, we evaluated deep learning enhancement u...
Improved amyloid burden quantification with nonspecific estimates using deep learning.
European journal of nuclear medicine and molecular imaging
Jan 7, 2021
PURPOSE: Standardized uptake value ratio (SUVr) used to quantify amyloid-β burden from amyloid-PET scans can be biased by variations in the tracer's nonspecific (NS) binding caused by the presence of cerebrovascular disease (CeVD). In this work, we p...
Deep learning detection of informative features in tau PET for Alzheimer's disease classification.
BMC bioinformatics
Dec 28, 2020
BACKGROUND: Alzheimer's disease (AD) is the most common type of dementia, typically characterized by memory loss followed by progressive cognitive decline and functional impairment. Many clinical trials of potential therapies for AD have failed, and ...
Detection of transient neurotransmitter response using personalized neural networks.
Physics in medicine and biology
Dec 18, 2020
Measurement of stimulus-induced dopamine release and other types of transient neurotransmitter response (TNR) from dynamic positron emission tomography (PET) images typically suffers from limited detection sensitivity and high false positive (FP) rat...
A physics-guided modular deep-learning based automated framework for tumor segmentation in PET.
Physics in medicine and biology
Dec 18, 2020
An important need exists for reliable positron emission tomography (PET) tumor-segmentation methods for tasks such as PET-based radiation-therapy planning and reliable quantification of volumetric and radiomic features. To address this need, we propo...
Artificial intelligence applications for oncological positron emission tomography imaging.
European journal of radiology
Nov 30, 2020
Positron emission tomography (PET), a functional and dynamic molecular imaging technique, is generally used to reveal tumors' biological behavior. Radiomics allows a high-throughput extraction of multiple features from images with artificial intellig...
Conditional Generative Adversarial Networks Aided Motion Correction of Dynamic F-FDG PET Brain Studies.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Nov 27, 2020
This work set out to develop a motion-correction approach aided by conditional generative adversarial network (cGAN) methodology that allows reliable, data-driven determination of involuntary subject motion during dynamic F-FDG brain studies. Ten he...
FBP-Net for direct reconstruction of dynamic PET images.
Physics in medicine and biology
Nov 20, 2020
Dynamic positron emission tomography (PET) imaging can provide information about metabolic changes over time, used for kinetic analysis and auxiliary diagnosis. Existing deep learning-based reconstruction methods have too many trainable parameters an...
Artificial Intelligence for Response Evaluation With PET/CT.
Seminars in nuclear medicine
Nov 11, 2020
Positron emission tomography (PET)/computed tomography (CT) are nuclear diagnostic imaging modalities that are routinely deployed for cancer staging and monitoring. They hold the advantage of detecting disease related biochemical and physiologic abno...
Artificial Intelligence for Optimization and Interpretation of PET/CT and PET/MR Images.
Seminars in nuclear medicine
Nov 11, 2020
Artificial intelligence (AI) has recently attracted much attention for its potential use in healthcare applications. The use of AI to improve and extract more information out of medical images, given their parallels with natural images and the immens...
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