AIMC Topic: Multimodal Imaging

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An ensemble deep learning model for medical image fusion with Siamese neural networks and VGG-19.

PloS one Oct 23, 2024
Multimodal medical image fusion methods, which combine complementary information from many multi-modality medical images, are among the most important and practical approaches in numerous clinical applications. Various conventional image fusion techn...
Multimodal Imaging Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Magnetic Resonance Imaging Algorithms
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Multimodal ultrasound deep learning to detect fibrosis in early chronic kidney disease.

Renal failure Oct 22, 2024
We developed a multimodal ultrasound (US) deep learning (DL) fusion model to automatically classify early fibrosis in patients with chronic kidney disease (CKD). This prospective study included patients with CKD who underwent continuous gray-scale US...
Multimodal Imaging Fibrosis Female ROC Curve Elasticity Imaging Techniques Aged Adult Kidney Humans Deep Learning Renal Insufficiency, Chronic Prospective Studies Ultrasonography Male Middle Aged
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Multimodal radiomics and deep learning models for predicting early femoral head deformity in LCPD.

European journal of radiology Oct 19, 2024
PURPOSE: To develop a predictive model combining clinical, radiomic, and deep learning features based on X-ray and MRI to identify risk factors for early femoral head deformity in Legg-Calvé-Perthes disease (LCPD).
Humans Male Deep Learning Child, Preschool Child Retrospective Studies Female Radiomics Femur Head Legg-Calve-Perthes Disease Magnetic Resonance Imaging Multimodal Imaging Predictive Value of Tests
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A review of deep learning approaches for multimodal image segmentation of liver cancer.

Journal of applied clinical medical physics Oct 7, 2024
This review examines the recent developments in deep learning (DL) techniques applied to multimodal fusion image segmentation for liver cancer. Hepatocellular carcinoma is a highly dangerous malignant tumor that requires accurate image segmentation f...
Humans Liver Neoplasms Carcinoma, Hepatocellular Image Processing, Computer-Assisted Multimodal Imaging Neural Networks, Computer Algorithms Deep Learning
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Joint self-supervised and supervised contrastive learning for multimodal MRI data: Towards predicting abnormal neurodevelopment.

Artificial intelligence in medicine Sep 30, 2024
The integration of different imaging modalities, such as structural, diffusion tensor, and functional magnetic resonance imaging, with deep learning models has yielded promising outcomes in discerning phenotypic characteristics and enhancing disease ...
Humans Brain Diagnosis, Computer-Assisted Deep Learning Image Interpretation, Computer-Assisted Neurodevelopmental Disorders Magnetic Resonance Imaging Multimodal Imaging Supervised Machine Learning
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Machine learning-assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues.

Journal of biomedical optics Sep 27, 2024
SIGNIFICANCE: Label-free multimodal imaging methods that can provide complementary structural and chemical information from the same sample are critical for comprehensive tissue analyses. These methods are specifically needed to study the complex tum...
Second Harmonic Generation Microscopy Hyperspectral Imaging Pancreas Spectrophotometry, Infrared Fibrillar Collagens Humans Image Processing, Computer-Assisted Machine Learning Multimodal Imaging Pancreatic Neoplasms
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DELR-Net: a network for 3D multimodal medical image registration in more lightweight application scenarios.

Abdominal radiology (New York) Sep 26, 2024
PURPOSE: 3D multimodal medical image deformable registration plays a significant role in medical image analysis and diagnosis. However, due to the substantial differences between images of different modalities, registration is challenging and require...
Magnetic Resonance Imaging Humans Multimodal Imaging Neural Networks, Computer Image Interpretation, Computer-Assisted Deep Learning Brain Imaging, Three-Dimensional Tomography, X-Ray Computed
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Multi-modality artificial intelligence-based transthyretin amyloid cardiomyopathy detection in patients with severe aortic stenosis.

European journal of nuclear medicine and molecular imaging Sep 23, 2024
PURPOSE: Transthyretin amyloid cardiomyopathy (ATTR-CM) is a frequent concomitant condition in patients with severe aortic stenosis (AS), yet it often remains undetected. This study aims to comprehensively evaluate artificial intelligence-based model...
Humans Artificial Intelligence Aged Aged, 80 and over Prospective Studies Female Multimodal Imaging Male Cardiomyopathies Severity of Illness Index Amyloid Neuropathies, Familial Aortic Valve Stenosis
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The application value of support vector machine model based on multimodal MRI in predicting IDH-1mutation and Ki-67 expression in glioma.

BMC medical imaging Sep 16, 2024
PURPOSE: To investigate the application value of support vector machine (SVM) model based on diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) and amide proton transfer- weighted (APTW) imaging in predicting isocitrate dehydrogenase 1...
Multimodal Imaging Mutation Isocitrate Dehydrogenase Ki-67 Antigen Diffusion Magnetic Resonance Imaging Retrospective Studies Support Vector Machine Female Contrast Media Aged Magnetic Resonance Imaging Brain Neoplasms Middle Aged Male ROC Curve Young Adult Glioma Adult Humans
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DeepASD: a deep adversarial-regularized graph learning method for ASD diagnosis with multimodal data.

Translational psychiatry Sep 14, 2024
Autism Spectrum Disorder (ASD) is a prevalent neurological condition with multiple co-occurring comorbidities that seriously affect mental health. Precisely diagnosis of ASD is crucial to intervention and rehabilitation. A single modality may not ful...
Magnetic Resonance Imaging Multimodal Imaging Neuroimaging Autism Spectrum Disorder Brain Deep Learning Humans Neural Networks, Computer
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