AIMC Topic: Tomography, Emission-Computed, Single-Photon
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Limited-angle SPECT image reconstruction using deep image prior.
Physics in medicine and biology
Jul 9, 2025
. In single-photon emission computed tomography (SPECT) image reconstruction, limited-angle conditions lead to a loss of frequency components, which distort the reconstructed tomographic image along directions corresponding to the non-collected proje...
AI in SPECT Imaging: Opportunities and Challenges.
Seminars in nuclear medicine
Apr 3, 2025
SPECT is a widely used imaging modality in nuclear medicine which provides essential functional insights into cardiovascular, neurological, and oncological diseases. However, SPECT imaging suffers from limited quantitative accuracy due to low spatial...
Artificial Intelligence-Enhanced Perfusion Scoring Improves the Diagnostic Accuracy of Myocardial Perfusion Imaging.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Apr 1, 2025
We previously demonstrated that a deep learning (DL) model of myocardial perfusion SPECT imaging improved accuracy for detection of obstructive coronary artery disease (CAD). We aimed to improve the clinical translatability of this artificial intelli...
Fully automatic categorical analysis of striatal subregions in dopamine transporter SPECT using a convolutional neural network.
Annals of nuclear medicine
Mar 16, 2025
OBJECTIVE: To provide fully automatic scanner-independent 5-level categorization of the [I]FP-CIT uptake in striatal subregions in dopamine transporter SPECT.
Artificial intelligence-powered coronary artery disease diagnosis from SPECT myocardial perfusion imaging: a comprehensive deep learning study.
European journal of nuclear medicine and molecular imaging
Feb 20, 2025
BACKGROUND: Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is a well-established modality for noninvasive diagnostic assessment of coronary artery disease (CAD). However, the time-consuming and experience-...
Interpretation of basal nuclei in brain dopamine transporter scans using a deep convolutional neural network.
Nuclear medicine communications
Feb 18, 2025
OBJECTIVE: Functional imaging using the dopamine transporter (DAT) as a biomarker has proven effective in assessing dopaminergic neuron degeneration in the striatum. In assessing the neuron degeneration, visual and semiquantitative methods are used t...
Middle Aged
Deep Learning
Convolutional Neural Networks
Female
Humans
Tomography, Emission-Computed, Single-Photon
Neural Networks, Computer
Aged
Dopamine Plasma Membrane Transport Proteins
Image Processing, Computer-Assisted
Brain
Parkinson Disease
Male
Retrospective Studies
Image Interpretation, Computer-Assisted
Diffusion-driven multi-modality medical image fusion.
Medical & biological engineering & computing
Feb 11, 2025
Multi-modality medical image fusion (MMIF) technology utilizes the complementarity of different modalities to provide more comprehensive diagnostic insights for clinical practice. Existing deep learning-based methods often focus on extracting the pri...
Deep learning-based CT-free attenuation correction for cardiac SPECT: a new approach.
BMC medical imaging
Feb 4, 2025
BACKGROUND: Computed tomography attenuation correction (CTAC) is commonly used in cardiac SPECT imaging to reduce soft-tissue attenuation artifacts. However, CTAC is prone to inaccuracies due to CT artifacts and SPECT-CT mismatch, along with addition...
First comparison between artificial intelligence-guided coronary computed tomography angiography versus single-photon emission computed tomography testing for ischemia in clinical practice.
Coronary artery disease
Dec 20, 2024
BACKGROUND: Noninvasive cardiac testing with coronary computed tomography angiography (CCTA) and single-photon emission computed tomography (SPECT) are becoming alternatives to invasive angiography for the evaluation of obstructive coronary artery di...
Incorporating label uncertainty during the training of convolutional neural networks improves performance for the discrimination between certain and inconclusive cases in dopamine transporter SPECT.
European journal of nuclear medicine and molecular imaging
Nov 27, 2024
PURPOSE: Deep convolutional neural networks (CNN) hold promise for assisting the interpretation of dopamine transporter (DAT)-SPECT. For improved communication of uncertainty to the user it is crucial to reliably discriminate certain from inconclusiv...
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