AIMC Topic: Positron-Emission Tomography
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Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Feb 11, 2020
INTRODUCTION: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge.
PET image super-resolution using generative adversarial networks.
Neural networks : the official journal of the International Neural Network Society
Feb 3, 2020
The intrinsically low spatial resolution of positron emission tomography (PET) leads to image quality degradation and inaccurate image-based quantitation. Recently developed supervised super-resolution (SR) approaches are of great relevance to PET bu...
Research of Multimodal Medical Image Fusion Based on Parameter-Adaptive Pulse-Coupled Neural Network and Convolutional Sparse Representation.
Computational and mathematical methods in medicine
Jan 24, 2020
Visual effects of medical image have a great impact on clinical assistant diagnosis. At present, medical image fusion has become a powerful means of clinical application. The traditional medical image fusion methods have the problem of poor fusion re...
Machine learning derived input-function in a dynamic F-FDG PET study of mice.
Biomedical physics & engineering express
Jan 13, 2020
Tracer kinetic modelling, based on dynamic F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is used to quantify glucose metabolism in humans and animals. Knowledge of the arterial input-function (AIF) is required for such measurements. O...
A Classification Algorithm by Combination of Feature Decomposition and Kernel Discriminant Analysis (KDA) for Automatic MR Brain Image Classification and AD Diagnosis.
Computational and mathematical methods in medicine
Dec 30, 2019
Magnetic resonance (MR) imaging is a widely used imaging modality for detection of brain anatomical variations caused by brain diseases such as Alzheimer's disease (AD) and mild cognitive impairment (MCI). AD considered as an irreversible neurodegene...
Positron-Emission Tomography
Image Interpretation, Computer-Assisted
Linear Models
Humans
Pattern Recognition, Automated
Reproducibility of Results
Machine Learning
Neuroimaging
Biomarkers
Aged
Algorithms
Brain
Male
Databases, Factual
Image Processing, Computer-Assisted
Female
Middle Aged
Disease Progression
Magnetic Resonance Imaging
Discriminant Analysis
Diagnosis, Computer-Assisted
Alzheimer Disease
Cognitive Dysfunction
The clinical feasibility of deep learning-based classification of amyloid PET images in visually equivocal cases.
European journal of nuclear medicine and molecular imaging
Dec 6, 2019
PURPOSE: Although most deep learning (DL) studies have reported excellent classification accuracy, these studies usually target typical Alzheimer's disease (AD) and normal cognition (NC) for which conventional visual assessment performs well. A clini...
Convolutional Neural Network Detection of Axillary Lymph Node Metastasis Using Standard Clinical Breast MRI.
Clinical breast cancer
Dec 5, 2019
BACKGROUND: Axillary lymph node status is important for breast cancer staging and treatment planning as the majority of breast cancer metastasis spreads through the axillary lymph nodes. There is currently no reliable noninvasive imaging method to de...
Datasets as Topic
Fluorodeoxyglucose F18
Sentinel Lymph Node
Lymphatic Metastasis
Magnetic Resonance Imaging
Axilla
Reproducibility of Results
Humans
Anatomic Landmarks
Breast Neoplasms
Neural Networks, Computer
Feasibility Studies
ROC Curve
Female
Radiopharmaceuticals
Image Processing, Computer-Assisted
Positron-Emission Tomography
CNN-based PET sinogram repair to mitigate defective block detectors.
Physics in medicine and biology
Dec 5, 2019
Positron emission tomography (PET) scanners continue to increase sensitivity and axial coverage by adding an ever expanding array of block detectors. As they age, one or more block detectors may lose sensitivity due to a malfunction or component fail...
Evolving the pulmonary nodules diagnosis from classical approaches to deep learning-aided decision support: three decades' development course and future prospect.
Journal of cancer research and clinical oncology
Nov 30, 2019
PURPOSE: Lung cancer is the commonest cause of cancer deaths worldwide, and its mortality can be reduced significantly by performing early diagnosis and screening. Since the 1960s, driven by the pressing needs to accurately and effectively interpret ...
Cognitive signature of brain FDG PET based on deep learning: domain transfer from Alzheimer's disease to Parkinson's disease.
European journal of nuclear medicine and molecular imaging
Nov 25, 2019
PURPOSE: Although functional brain imaging has been used for the early and objective assessment of cognitive dysfunction, there is a lack of generalized image-based biomarker which can evaluate individual's cognitive dysfunction in various disorders....
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