AIMC Topic: Dopamine Plasma Membrane Transport Proteins
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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.
Item Response Modeling and Artificial Neural Network for Differentiation of Parkinson's Patients and Subjects Without Evidence of Dopaminergic Deficit.
CPT: pharmacometrics & systems pharmacology
Mar 5, 2025
Approximately 15% of patients suspected of having Parkinson's disease (PD) present dopamine active transporter (DaT) scans without evidence of dopaminergic deficits (SWEDD), most of which will never develop PD. Leveraging Movement Disorders Society U...
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...
Neural Networks, Computer
Brain
Retrospective Studies
Dopamine Plasma Membrane Transport Proteins
Parkinson Disease
Image Interpretation, Computer-Assisted
Tomography, Emission-Computed, Single-Photon
Middle Aged
Female
Deep Learning
Aged
Convolutional Neural Networks
Male
Humans
Image Processing, Computer-Assisted
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...
Artificial intelligence-based analysis of behavior and brain images in cocaine-self-administered marmosets.
Journal of neuroscience methods
Sep 19, 2024
BACKGROUND: The sophisticated behavioral and cognitive repertoires of non-human primates (NHPs) make them suitable subjects for studies involving cocaine self-administration (SA) schedules. However, ethical considerations, adherence to the 3Rs princi...
Unrealistic Data Augmentation Improves the Robustness of Deep Learning-Based Classification of Dopamine Transporter SPECT Against Variability Between Sites and Between Cameras.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Sep 3, 2024
We propose strongly unrealistic data augmentation to improve the robustness of convolutional neural networks (CNNs) for automatic classification of dopamine transporter SPECT against the variability between sites and between cameras. A CNN was train...
Machine learning for predicting cognitive decline within five years in Parkinson's disease: Comparing cognitive assessment scales with DAT SPECT and clinical biomarkers.
PloS one
Jul 17, 2024
OBJECTIVE: Parkinson's disease (PD) is an age-related neurodegenerative condition characterized mostly by motor symptoms. Although a wide range of non-motor symptoms (NMS) are frequently experienced by PD patients. One of the important and common NMS...
Automated identification of uncertain cases in deep learning-based classification of dopamine transporter SPECT to improve clinical utility and acceptance.
European journal of nuclear medicine and molecular imaging
Dec 22, 2023
PURPOSE: Deep convolutional neural networks (CNN) are promising for automatic classification of dopamine transporter (DAT)-SPECT images. Reporting the certainty of CNN-based decisions is highly desired to flag cases that might be misclassified and, t...
Deep learning-based image analysis identifies a DAT-negative subpopulation of dopaminergic neurons in the lateral Substantia nigra.
Communications biology
Nov 10, 2023
Here we present a deep learning-based image analysis platform (DLAP), tailored to autonomously quantify cell numbers, and fluorescence signals within cellular compartments, derived from RNAscope or immunohistochemistry. We utilised DLAP to analyse su...
Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake.
Neuroradiology
May 20, 2023
PURPOSE: Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imaging using I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (I-FP-CIT) single-photon emission computerized tomography (SPECT) can eval...
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