AIMC Topic: Tomography, Emission-Computed, Single-Photon

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Detection of parkinson's disease with neuroimaging modalities using machine learning and artificial intelligence: a systematic review.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
The application of machine learning (ML) and artificial intelligence (AI) algorithms in medical imaging is an emerging area of interest, particularly in the context of clinical decision-making. Here, we report on the overall performance (i.e., sensit...

[Tc]Tc-Sestamibi/[Tc]NaTcO Subtraction SPECT of Parathyroid Glands Using Analysis of Principal Components.

Journal of nuclear medicine technology
The aim of the study was to validate a new method for semiautomatic subtraction of [Tc]Tc-sestamibi and [Tc]NaTcO SPECT 3-dimensional datasets using principal component analysis (PCA) against the results of parathyroid surgery and to compare its perf...

Using machine learning for detection of Parkinson's disease and mild cognitive impairment.

PloS one
BACKGROUND: Parkinson's disease is a movement disorder featuring motor symptoms and cognitive decline, which can manifest as mild cognitive impairment. The incidence of mild cognitive impairment increases with disease progression, and Parkinson's dis...

Web based AI-driven framework combining multi-modal data with CNN and LLM for Parkinson's disease diagnosis.

Scientific reports
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by a wide spectrum of motor and non-motor symptoms, often leading to delayed or inaccurate diagnosis. Conventional diagnostic methods frequently suffer from limited se...

Limited-angle SPECT image reconstruction using deep image prior.

Physics in medicine and biology
. 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
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
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...

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
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
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...