AIMC Topic: Image Interpretation, Computer-Assisted

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Self-supervised graph contrastive learning with diffusion augmentation for functional MRI analysis and brain disorder detection.

Medical image analysis Nov 29, 2024
Resting-state functional magnetic resonance imaging (rs-fMRI) provides a non-invasive imaging technique to study patterns of brain activity, and is increasingly used to facilitate automated brain disorder analysis. Existing fMRI-based learning method...
Supervised Machine Learning Humans Algorithms Image Interpretation, Computer-Assisted Brain Brain Diseases Magnetic Resonance Imaging Brain Mapping
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Classification of melanoma skin Cancer based on Image Data Set using different neural networks.

Scientific reports Nov 29, 2024
This paper aims to address the pressing issue of melanoma classification by leveraging advanced neural network models, specifically basic Convolutional Neural Networks (CNN), ResNet-18, and EfficientNet-B0. Our objectives encompass presenting and eva...
Image Interpretation, Computer-Assisted Skin Neoplasms Image Processing, Computer-Assisted Algorithms Melanoma Humans Neural Networks, Computer
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Automatic classification of HEp-2 specimens by explainable deep learning and Jensen-Shannon reliability index.

Artificial intelligence in medicine Nov 28, 2024
The Anti-Nuclear Antibodies (ANA) test using Human Epithelial type 2 (HEp-2) cells in the Indirect Immuno-Fluorescence (IIF) assay protocol is considered the gold standard for detecting Connective Tissue Diseases. Computer-assisted systems for HEp-2 ...
Deep Learning Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Humans Reproducibility of Results Connective Tissue Diseases Antibodies, Antinuclear
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Multiple-Instance Learning for thyroid gland disease classification: A hands-on experience.

Computers in biology and medicine Nov 28, 2024
The morphological diagnosis of thyroid gland neoplasms presents a dual challenge: it requires the expertise of highly trained specialists and considerable time, particularly when evaluating multiple whole slide images (WSIs) from a single patient. Th...
Thyroid Neoplasms Image Interpretation, Computer-Assisted Humans Diagnosis, Computer-Assisted Thyroid Gland Machine Learning
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Clinical feasibility of a deep learning approach for conventional and synthetic diffusion-weighted imaging in breast cancer: Qualitative and quantitative analyses.

European journal of radiology Nov 27, 2024
PURPOSE: In this study, we aimed to investigate the clinical feasibility of deep learning (DL)-based reconstruction applied to conventional diffusion-weighted imaging (cDWI) and synthetic diffusion-weighted imaging (sDWI) by comparing the DL reconstr...
Humans Retrospective Studies Aged Adult Female Image Interpretation, Computer-Assisted Signal-To-Noise Ratio Diffusion Magnetic Resonance Imaging Deep Learning Breast Breast Neoplasms Feasibility Studies Middle Aged
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FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification.

IEEE transactions on cybernetics Nov 27, 2024
Histopathological tissue classification is a fundamental task in computational pathology. Deep learning (DL)-based models have achieved superior performance but centralized training suffers from the privacy leakage problem. Federated learning (FL) ca...
Image Interpretation, Computer-Assisted Histological Techniques Algorithms Humans Deep Learning
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Segmentation of Low-Grade Brain Tumors Using Mutual Attention Multimodal MRI.

Sensors (Basel, Switzerland) Nov 27, 2024
Early detection and precise characterization of brain tumors play a crucial role in improving patient outcomes and extending survival rates. Among neuroimaging modalities, magnetic resonance imaging (MRI) is the gold standard for brain tumor diagnost...
Image Processing, Computer-Assisted Brain Neoplasms Image Interpretation, Computer-Assisted Multimodal Imaging Humans Astrocytoma Magnetic Resonance Imaging Deep Learning Algorithms
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Automated brain tumor recognition using equilibrium optimizer with deep learning approach on MRI images.

Scientific reports Nov 27, 2024
Brain tumours (BT) affect human health owing to their location. Artificial intelligence (AI) is intended to assist in diagnosing and treating complex diseases by combining technologies like deep learning (DL), big data analytics, and machine learning...
Humans Algorithms Brain Neoplasms Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Deep Learning Image Processing, Computer-Assisted
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Automated Classification of Coronary Plaque on Intravascular Ultrasound by Deep Classifier Cascades.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 27, 2024
Intravascular ultrasound (IVUS) is the gold standard modality for in vivo visualization of coronary arteries and atherosclerotic plaques. Classification of coronary plaques helps to characterize heterogeneous components and evaluate the risk of plaqu...
Humans Ultrasonography, Interventional Coronary Artery Disease Image Interpretation, Computer-Assisted Algorithms Deep Learning Coronary Vessels Plaque, Atherosclerotic
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Spatiotemporal Deep Learning-Based Cine Loop Quality Filter for Handheld Point-of-Care Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 27, 2024
The reliability of automated image interpretation of point-of-care (POC) echocardiography scans depends on the quality of the acquired ultrasound data. This work reports on the development and validation of spatiotemporal deep learning models to asse...
Humans Algorithms Reproducibility of Results Deep Learning Point-of-Care Systems Heart Ventricles Echocardiography Image Interpretation, Computer-Assisted
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