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

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Convolutional Neural Networks for Neuroimaging in Parkinson's Disease: Is Preprocessing Needed?

International journal of neural systems
Spatial and intensity normalizations are nowadays a prerequisite for neuroimaging analysis. Influenced by voxel-wise and other univariate comparisons, where these corrections are key, they are commonly applied to any type of analysis and imaging moda...

Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death based on adenosine myocardial perfusion SPECT (MPS) and associated clinical data, and compared their performance to baseline logistic regression (LR)....

Extraction, selection and comparison of features for an effective automated computer-aided diagnosis of Parkinson's disease based on [I]FP-CIT SPECT images.

European journal of nuclear medicine and molecular imaging
PURPOSE: This work aimed to assess the potential of a set of features extracted from [I]FP-CIT SPECT brain images to be used in the computer-aided "in vivo" confirmation of dopaminergic degeneration and therefore to assist clinical decision to diagno...

Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning.

JACC. Cardiovascular imaging
OBJECTIVES: This study evaluated the added predictive value of combining clinical information and myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) data using machine learning (ML) to predict major adverse cardiac ...

Support vector machine-based classification of neuroimages in Alzheimer's disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals.

Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)
OBJECTIVE: To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (T1-MRI), F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and regional cerebral blood flo...

New Dandelion Algorithm Optimizes Extreme Learning Machine for Biomedical Classification Problems.

Computational intelligence and neuroscience
Inspired by the behavior of dandelion sowing, a new novel swarm intelligence algorithm, namely, dandelion algorithm (DA), is proposed for global optimization of complex functions in this paper. In DA, the dandelion population will be divided into two...

Refining diagnosis of Parkinson's disease with deep learning-based interpretation of dopamine transporter imaging.

NeuroImage. Clinical
Dopaminergic degeneration is a pathologic hallmark of Parkinson's disease (PD), which can be assessed by dopamine transporter imaging such as FP-CIT SPECT. Until now, imaging has been routinely interpreted by human though it can show interobserver va...