AIMC Topic: Positron-Emission Tomography
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The Residual Center of Mass: An Image Descriptor for the Diagnosis of Alzheimer Disease.
Neuroinformatics
Apr 1, 2019
A crucial quest in neuroimaging is the discovery of image features (biomarkers) associated with neurodegenerative disorders. Recent works show that such biomarkers can be obtained by image analysis techniques. However, these techniques cannot be dire...
Hybrid 11C-MET PET/MRI Combined With "Machine Learning" in Glioma Diagnosis According to the Revised Glioma WHO Classification 2016.
Clinical nuclear medicine
Mar 1, 2019
PURPOSE: With the advent of the revised WHO classification from 2016, molecular features, including isocitrate dehydrogenase (IDH) mutation have become important in glioma subtyping. This pilot trial analyzed the potential for C-methionine (MET) PET/...
Volumetric Histogram-Based Alzheimer's Disease Detection Using Support Vector Machine.
Journal of Alzheimer's disease : JAD
Jan 1, 2019
In this research work, machine learning techniques are used to classify magnetic resonance imaging brain scans of people with Alzheimer's disease. This work deals with binary classification between Alzheimer's disease and cognitively normal. Supervis...
Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology.
Molecular imaging
Jan 1, 2019
Machine learning (ML) algorithms have found increasing utility in the medical imaging field and numerous applications in the analysis of digital biomarkers within positron emission tomography (PET) imaging have emerged. Interest in the use of artific...
Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.
Neuroinformatics
Oct 1, 2018
Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET),...
[Big data and artificial intelligence for diagnostic decision support in atypical dementia].
Der Nervenarzt
Aug 1, 2018
The differential diagnosis of atypical dementia remains difficult. The use of positron emission tomography (PET) still represents the gold standard for imaging diagnostics. According to the current evidence, however, magnetic resonance imaging (MRI) ...
Penalized PET Reconstruction Using Deep Learning Prior and Local Linear Fitting.
IEEE transactions on medical imaging
Jun 1, 2018
Motivated by the great potential of deep learning in medical imaging, we propose an iterative positron emission tomography reconstruction framework using a deep learning-based prior. We utilized the denoising convolutional neural network (DnCNN) meth...
Artificial Neural Network Enhanced Bayesian PET Image Reconstruction.
IEEE transactions on medical imaging
Jun 1, 2018
In positron emission tomography (PET) image reconstruction, the Bayesian framework with various regularization terms has been implemented to constrain the radio tracer distribution. Varying the regularizing weight of a maximum a posteriori (MAP) algo...
Image reconstruction by domain-transform manifold learning.
Nature
Mar 21, 2018
Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio a...
Robotic-Assisted and Image-Guided MRI-Compatible Stereoelectroencephalography.
The Canadian journal of neurological sciences. Le journal canadien des sciences neurologiques
Jan 1, 2018
BACKGROUND: Stereoelectroencephalography has been in regular use at the Montreal Neurological Institute since 1972. The technique has been in constant evolution to incorporate advances in materials, imaging, and robotics technology. MRI-compatible el...
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