AIMC Topic: Multimodal Imaging

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Logarithmic Fuzzy Entropy Function for Similarity Measurement in Multimodal Medical Images Registration.

Computational and mathematical methods in medicine Feb 12, 2020
Multimodal medical images are useful for observing tissue structure clearly in clinical practice. To integrate multimodal information, multimodal registration is significant. The entropy-based registration applies a structure descriptor set to replac...
Brain Mapping Multimodal Imaging Image Interpretation, Computer-Assisted Neuroimaging Brain Image Processing, Computer-Assisted Tomography, X-Ray Computed Magnetic Resonance Imaging Reproducibility of Results Fuzzy Logic Models, Statistical Humans Algorithms Normal Distribution Entropy
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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...
Humans Tomography, X-Ray Computed Multimodal Imaging Neoplasms Neural Networks, Computer Computational Biology Algorithms Positron-Emission Tomography Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Databases, Factual Tomography, Emission-Computed, Single-Photon Brain
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Multimodality image registration in the head-and-neck using a deep learning-derived synthetic CT as a bridge.

Medical physics Jan 2, 2020
PURPOSE: To develop and demonstrate the efficacy of a novel head-and-neck multimodality image registration technique using deep-learning-based cross-modality synthesis.
Deep Learning Image Processing, Computer-Assisted Head and Neck Neoplasms Magnetic Resonance Imaging Multimodal Imaging Humans Tomography, X-Ray Computed
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Hypergraph based multi-task feature selection for multimodal classification of Alzheimer's disease.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 19, 2019
Multi-modality based classification methods are superior to the single modality based approaches for the automatic diagnosis of the Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, most of the multi-modality based methods usuall...
Pattern Recognition, Automated Neuroimaging Machine Learning Female Aged Aged, 80 and over Multimodal Imaging Alzheimer Disease Image Interpretation, Computer-Assisted Male Brain Mapping Humans
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Disentangling brain functional network remodeling in corticobasal syndrome - A multimodal MRI study.

NeuroImage. Clinical Dec 2, 2019
OBJECTIVE: The clinical diagnosis of corticobasal syndrome (CBS) represents a challenge for physicians and reliable diagnostic imaging biomarkers would support the diagnostic work-up. We aimed to investigate the neural signatures of CBS using multimo...
Aged Male Middle Aged Support Vector Machine Humans Female Cerebral Cortex Connectome Nerve Net Basal Ganglia Diseases Magnetic Resonance Imaging Multimodal Imaging Neuroimaging Gray Matter
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Integrating machining learning and multimodal neuroimaging to detect schizophrenia at the level of the individual.

Human brain mapping Nov 18, 2019
Schizophrenia is a severe psychiatric disorder associated with both structural and functional brain abnormalities. In the past few years, there has been growing interest in the application of machine learning techniques to neuroimaging data for the d...
Connectome Young Adult Neural Pathways Adult Diffusion Tensor Imaging Rest Humans Male Neuroimaging Machine Learning Middle Aged Magnetic Resonance Imaging Gray Matter Female White Matter Multimodal Imaging Reproducibility of Results Image Processing, Computer-Assisted Schizophrenia Support Vector Machine
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Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction.

PloS one Oct 7, 2019
One of the main technical challenges of PET/MRI is to achieve an accurate PET attenuation correction (AC) estimation. In current systems, AC is accomplished by generating an MRI-based surrogate computed tomography (CT) from which AC-maps are derived....
Multimodal Imaging Female Positron-Emission Tomography Humans Aged Fluorodeoxyglucose F18 Neural Networks, Computer Male Analysis of Variance Algorithms Magnetic Resonance Imaging Brain
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Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis.

Human brain mapping Oct 1, 2019
Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be due to clinical heterogeneity ...
Adult Male Middle Aged Anxiety Depression Age Factors Magnetic Resonance Imaging Case-Control Studies Functional Neuroimaging Humans Machine Learning Female Multimodal Imaging Sex Factors Neuroimaging Depressive Disorder
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Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets.

Medical physics Aug 20, 2019
PURPOSE: Accurate tumor segmentation is a requirement for magnetic resonance (MR)-based radiotherapy. Lack of large expert annotated MR datasets makes training deep learning models difficult. Therefore, a cross-modality (MR-CT) deep learning segmenta...
Multimodal Imaging Image Processing, Computer-Assisted Lung Neoplasms Carcinoma, Non-Small-Cell Lung Magnetic Resonance Imaging Humans Tomography, X-Ray Computed Deep Learning
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Deep Convolution Neural Network (DCNN) Multiplane Approach to Synthetic CT Generation From MR images-Application in Brain Proton Therapy.

International journal of radiation oncology, biology, physics Jul 2, 2019
PURPOSE: The first aim of this work is to present a novel deep convolution neural network (DCNN) multiplane approach and compare it to single-plane prediction of synthetic computed tomography (sCT) by using the real computed tomography (CT) as ground...
Glioblastoma Reproducibility of Results Feasibility Studies Radiotherapy, Image-Guided Radiotherapy Dosage Humans Radiotherapy Planning, Computer-Assisted Brain Neoplasms Air Technology, Radiologic Neural Networks, Computer Magnetic Resonance Imaging Head Skull Algorithms Multimodal Imaging Proton Therapy Tomography, X-Ray Computed
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