AIMC Topic: Amyloid

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Ultra-Low-Dose F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs.

Radiology Dec 11, 2018
Purpose To reduce radiotracer requirements for amyloid PET/MRI without sacrificing diagnostic quality by using deep learning methods. Materials and Methods Forty data sets from 39 patients (mean age ± standard deviation [SD], 67 years ± 8), including...
Multimodal Imaging Alzheimer Disease Aniline Compounds Positron-Emission Tomography Deep Learning Cognitive Dysfunction Magnetic Resonance Imaging Brain Diseases Lewy Body Disease Stilbenes Amyloid Parkinsonian Disorders Humans Retrospective Studies Female Aged Male Middle Aged
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Adaptive template generation for amyloid PET using a deep learning approach.

Human brain mapping May 11, 2018
Accurate spatial normalization (SN) of amyloid positron emission tomography (PET) images for Alzheimer's disease assessment without coregistered anatomical magnetic resonance imaging (MRI) of the same individual is technically challenging. In this st...
Carbon Radioisotopes Positron-Emission Tomography Amyloid Thiazoles Benzothiazoles Radiopharmaceuticals Alzheimer Disease Aniline Compounds Female Cognitive Dysfunction Humans Male Algorithms Imaging, Three-Dimensional Deep Learning Magnetic Resonance Imaging Supervised Machine Learning Brain
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Amino acid composition predicts prion activity.

PLoS computational biology Apr 10, 2017
Many prion-forming proteins contain glutamine/asparagine (Q/N) rich domains, and there are conflicting opinions as to the role of primary sequence in their conversion to the prion form: is this phenomenon driven primarily by amino acid composition, o...
Humans Machine Learning Computational Biology Amino Acid Sequence Amyloid Prions Yeasts Asparagine Glutamine
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Combined thioflavin T-Congo red fluorescence assay for amyloid fibril detection.

Methods and applications in fluorescence Sep 6, 2016
Fluorescence represents one of the most powerful tools for the detection and structural characterization of the pathogenic protein aggregates, amyloid fibrils. The traditional approaches to the identification and quantification of amyloid fibrils are...
Benzothiazoles Congo Red Fluorescent Dyes Kinetics Reproducibility of Results Amyloid Fluorescence Thiazoles Protein Binding
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Classification of amyloid status using machine learning with histograms of oriented 3D gradients.

NeuroImage. Clinical May 10, 2016
Brain amyloid burden may be quantitatively assessed from positron emission tomography imaging using standardised uptake value ratios. Using these ratios as an adjunct to visual image assessment has been shown to improve inter-reader reliability, howe...
Humans Carbon Radioisotopes Brain Aged, 80 and over Ethylene Glycols Positron-Emission Tomography Sensitivity and Specificity Radiopharmaceuticals Female Stilbenes Male Alzheimer Disease Reproducibility of Results Amyloid Support Vector Machine Aged Aniline Compounds Image Interpretation, Computer-Assisted
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Prediction of Peptide and Protein Propensity for Amyloid Formation.

PloS one Aug 4, 2015
Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo str...
Protein Structure, Secondary Amyloidogenic Proteins Neural Networks, Computer Amino Acid Sequence Amyloid
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Assessing amyloid fibrils and amorphous aggregates: A review.

International journal of biological macromolecules Jun 1, 2025
Protein misfolding and aggregation play a central role in the progression of neurodegenerative diseases such as Alzheimer's and Parkinson's. These aggregates manifest either as structured amyloid fibrils enriched in β-sheet conformations or as irregu...
Humans Animals Amyloid Protein Aggregates Protein Aggregation, Pathological
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AmyloidPETNet: Classification of Amyloid Positivity in Brain PET Imaging Using End-to-End Deep Learning.

Radiology Jun 1, 2024
Background Visual assessment of amyloid PET scans relies on the availability of radiologist expertise, whereas quantification of amyloid burden typically involves MRI for processing and analysis, which can be computationally expensive. Purpose To dev...
Humans Brain Retrospective Studies Deep Learning Alzheimer Disease Positron-Emission Tomography Amyloid Female Aged Aged, 80 and over Male
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MRI-based Deep Learning Assessment of Amyloid, Tau, and Neurodegeneration Biomarker Status across the Alzheimer Disease Spectrum.

Radiology Oct 1, 2023
Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disease, but incurs considerable cost and exposure to ionizing radiation. MRI currently has limited use in characterizing ATN status. Deep learning techniq...
Apolipoproteins E Positron-Emission Tomography Amyloid tau Proteins Aged Male Deep Learning Cognitive Dysfunction Humans Magnetic Resonance Imaging Biomarkers Amyloid beta-Peptides Retrospective Studies Alzheimer Disease Female
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Deep-SMOLM: deep learning resolves the 3D orientations and 2D positions of overlapping single molecules with optimal nanoscale resolution.

Optics express Sep 26, 2022
Dipole-spread function (DSF) engineering reshapes the images of a microscope to maximize the sensitivity of measuring the 3D orientations of dipole-like emitters. However, severe Poisson shot noise, overlapping images, and simultaneously fitting high...
Deep Learning Image Processing, Computer-Assisted Nanotechnology Microscopy Amyloid
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