AIMC Topic: Positron-Emission Tomography
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Artificial Intelligence in Head and Neck Imaging.
Seminars in ultrasound, CT, and MR
Feb 11, 2022
Artificial intelligence (AI) can be applied to head and neck imaging to augment image quality and various clinical tasks including segmentation of tumor volumes, tumor characterization, tumor prognostication and treatment response, and prediction of ...
Deep-learning-based fast TOF-PET image reconstruction using direction information.
Radiological physics and technology
Feb 8, 2022
Although deep learning for application in positron emission tomography (PET) image reconstruction has attracted the attention of researchers, the image quality must be further improved. In this study, we propose a novel convolutional neural network (...
Anomaly detection in chest F-FDG PET/CT by Bayesian deep learning.
Japanese journal of radiology
Jan 30, 2022
PURPOSE: To develop an anomaly detection system in PET/CT with the tracer F-fluorodeoxyglucose (FDG) that requires only normal PET/CT images for training and can detect abnormal FDG uptake at any location in the chest region.
Deep learning for image classification in dedicated breast positron emission tomography (dbPET).
Annals of nuclear medicine
Jan 27, 2022
OBJECTIVE: This study aimed to investigate and determine the best deep learning (DL) model to predict breast cancer (BC) with dedicated breast positron emission tomography (dbPET) images.
Investigating Simultaneity for Deep Learning-Enhanced Actual Ultra-Low-Dose Amyloid PET/MR Imaging.
AJNR. American journal of neuroradiology
Jan 27, 2022
BACKGROUND AND PURPOSE: Diagnostic-quality amyloid PET images can be created with deep learning using actual ultra-low-dose PET images and simultaneous structural MR imaging. Here, we investigated whether simultaneity is required; if not, MR imaging-...
A review on AI in PET imaging.
Annals of nuclear medicine
Jan 14, 2022
Artificial intelligence (AI) has been applied to various medical imaging tasks, such as computer-aided diagnosis. Specifically, deep learning techniques such as convolutional neural network (CNN) and generative adversarial network (GAN) have been ext...
A cross-scanner and cross-tracer deep learning method for the recovery of standard-dose imaging quality from low-dose PET.
European journal of nuclear medicine and molecular imaging
Dec 24, 2021
PURPOSE: A critical bottleneck for the credibility of artificial intelligence (AI) is replicating the results in the diversity of clinical practice. We aimed to develop an AI that can be independently applied to recover high-quality imaging from low-...
Subtyping of mild cognitive impairment using a deep learning model based on brain atrophy patterns.
Cell reports. Medicine
Dec 21, 2021
Trajectories of cognitive decline vary considerably among individuals with mild cognitive impairment (MCI). To address this heterogeneity, subtyping approaches have been developed, with the objective of identifying more homogeneous subgroups. To date...
Comparison of deep learning-based emission-only attenuation correction methods for positron emission tomography.
European journal of nuclear medicine and molecular imaging
Dec 9, 2021
PURPOSE: This study aims to compare two approaches using only emission PET data and a convolution neural network (CNN) to correct the attenuation (μ) of the annihilation photons in PET.
Deep learning-based attenuation map generation and correction; could it be useful clinically?
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Dec 7, 2021
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