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Increasing the confidence of F-Florbetaben PET interpretations: Machine learning quantitative approximation.

Revista espanola de medicina nuclear e imagen molecular
AIM: To assess the added value of semiquantitative parameters on the visual assessment and to study the patterns of F-Florbetaben brain deposition.

Aggregation-Induced Emission Probe for Specific Turn-On Quantification of Soluble Transferrin Receptor: An Important Disease Marker for Iron Deficiency Anemia and Kidney Diseases.

Analytical chemistry
Transferrin receptor (TfR) is overexpressed on the surface of many cancer cells due to its vital roles in iron circulation and cellular respiration. Soluble transferrin receptor (sTfR), a truncated extracellular form of TfR in serum, is an important ...

RSM and ANN modeling-based optimization approach for the development of ultrasound-assisted liposome encapsulation of piceid.

Ultrasonics sonochemistry
Piceid, a naturally occurring derivative of resveratrol found in many plants, has recently been considered as a potential nutraceutical. However, its poorly water-soluble property could cause a coupled problem of biological activities concerning drug...

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

Radiology
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...

Visual interpretation of [F]Florbetaben PET supported by deep learning-based estimation of amyloid burden.

European journal of nuclear medicine and molecular imaging
PURPOSE: Amyloid PET which has been widely used for noninvasive assessment of cortical amyloid burden is visually interpreted in the clinical setting. As a fast and easy-to-use visual interpretation support system, we analyze whether the deep learnin...

Performance evaluation in [18F]Florbetaben brain PET images classification using 3D Convolutional Neural Network.

PloS one
High accuracy has been reported in deep learning classification for amyloid brain scans, an important factor in Alzheimer's disease diagnosis. However, the possibility of overfitting should be considered, as this model is fitted with sample data. The...

Translating amyloid PET of different radiotracers by a deep generative model for interchangeability.

NeuroImage
It is challenging to compare amyloid PET images obtained with different radiotracers. Here, we introduce a new approach to improve the interchangeability of amyloid PET acquired with different radiotracers through image-level translation. Deep genera...

PET/CT for Brain Amyloid: A Feasibility Study for Scan Time Reduction by Deep Learning.

Clinical nuclear medicine
PURPOSE: This study was to develop a convolutional neural network (CNN) model with a residual learning framework to predict the full-time 18F-florbetaben (18F-FBB) PET/CT images from corresponding short-time scans.

Identification of Microorganism in Infected Wounds by Positively Charged Selective Sensor Array and Deep Learning Algorithm.

Analytical chemistry
Microorganism are ubiquitous and intimately connected with human health and disease management. The accurate and fast identification of pathogenic microorganisms is especially important for diagnosing infections. Herein, three tetraphenylethylene der...