AIMC Topic: Image Interpretation, Computer-Assisted

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Combining artificial intelligence assisted image segmentation and ultrasound based radiomics for the prediction of carotid plaque stability.

BMC medical imaging Mar 17, 2025
PURPOSE: Utilizing artificial intelligence (AI) technology for the segmentation of plaques on ultrasound images to evaluate the stability of carotid artery plaques and analyze its diagnostic accuracy in differentiating vulnerable plaques from stable ...
Ultrasonography, Doppler, Color Carotid Stenosis Humans Radiomics Image Interpretation, Computer-Assisted Artificial Intelligence Male Retrospective Studies Carotid Arteries Middle Aged Plaque, Atherosclerotic ROC Curve Female Support Vector Machine Aged Ischemic Stroke Sensitivity and Specificity
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LI-RADS-based hepatocellular carcinoma risk mapping using contrast-enhanced MRI and self-configuring deep learning.

Cancer imaging : the official publication of the International Cancer Imaging Society Mar 17, 2025
BACKGROUND: Hepatocellular carcinoma (HCC) is often diagnosed using gadoxetate disodium-enhanced magnetic resonance imaging (EOB-MRI). Standardized reporting according to the Liver Imaging Reporting and Data System (LI-RADS) can improve Gd-MRI interp...
Adult Male Middle Aged Risk Assessment Deep Learning Liver Neoplasms Retrospective Studies Female Aged Image Interpretation, Computer-Assisted Carcinoma, Hepatocellular Gadolinium DTPA Contrast Media Magnetic Resonance Imaging Humans
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LHR-RFL: Linear Hybrid-Reward-Based Reinforced Focal Learning for Automatic Radiology Report Generation.

IEEE transactions on medical imaging Mar 17, 2025
Radiology report generation that aims to accurately describe medical findings for given images, is pivotal in contemporary computer-aided diagnosis. Recently, despite considerable progress, current radiology report generation models still struggled t...
Algorithms Natural Language Processing Radiology Humans Machine Learning Reward Image Interpretation, Computer-Assisted
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Pyramid Network With Quality-Aware Contrastive Loss for Retinal Image Quality Assessment.

IEEE transactions on medical imaging Mar 17, 2025
Captured retinal images vary greatly in quality. Low-quality images increase the risk of misdiagnosis. This motivates to design effective retinal image quality assessment (RIQA) methods. Current deep learning-based methods usually classify the image ...
Neural Networks, Computer Algorithms Deep Learning Humans Retina Image Interpretation, Computer-Assisted
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Toward Integrating Federated Learning With Split Learning via Spatio-Temporal Graph Framework for Brain Disease Prediction.

IEEE transactions on medical imaging Mar 17, 2025
Functional Magnetic Resonance Imaging (fMRI) is used for extracting blood oxygen signals from brain regions to map brain functional connectivity for brain disease prediction. Despite its effectiveness, fMRI has not been widely used: on the one hand, ...
Magnetic Resonance Imaging Machine Learning Federated Learning Humans Image Interpretation, Computer-Assisted Algorithms Brain Diseases Brain
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CoD-MIL: Chain-of-Diagnosis Prompting Multiple Instance Learning for Whole Slide Image Classification.

IEEE transactions on medical imaging Mar 17, 2025
Multiple instance learning (MIL) has emerged as a prominent paradigm for processing the whole slide image with pyramid structure and giga-pixel size in digital pathology. However, existing attention-based MIL methods are primarily trained on the imag...
Multiple-Instance Learning Algorithms Algorithms Natural Language Processing Image Interpretation, Computer-Assisted Humans Machine Learning
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MGAug: Multimodal Geometric Augmentation in Latent Spaces of Image Deformations.

Medical image analysis Mar 15, 2025
Geometric transformations have been widely used to augment the size of training images. Existing methods often assume a unimodal distribution of the underlying transformations between images, which limits their power when data with multimodal distrib...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Brain Humans Deep Learning Algorithms Imaging, Three-Dimensional
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Liver lesion segmentation in ultrasound: A benchmark and a baseline network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Mar 14, 2025
Accurate liver lesion segmentation in ultrasound is a challenging task due to high speckle noise, ambiguous lesion boundaries, and inhomogeneous intensity distribution inside the lesion regions. This work first collected and annotated a dataset for l...
Humans Neural Networks, Computer Liver Benchmarking Algorithms Image Interpretation, Computer-Assisted Ultrasonography Liver Neoplasms
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Optimized attention-enhanced U-Net for autism detection and region localization in MRI.

Psychiatry research. Neuroimaging Mar 14, 2025
Autism spectrum disorder (ASD) is a neurodevelopmental condition that affects a child's cognitive and social skills, often diagnosed only after symptoms appear around age 2. Leveraging MRI for early ASD detection can improve intervention outcomes. Th...
Attention Image Interpretation, Computer-Assisted Neuroimaging Autism Spectrum Disorder Sensitivity and Specificity Humans Deep Learning Male Child Magnetic Resonance Imaging
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AI-ready rectal cancer MR imaging: a workflow for tumor detection and segmentation.

BMC medical imaging Mar 14, 2025
BACKGROUND: Magnetic Resonance (MR) imaging is the preferred modality for staging in rectal cancer; however, despite its exceptional soft tissue contrast, segmenting rectal tumors on MR images remains challenging due to the overlapping appearance of ...
Image Interpretation, Computer-Assisted Aged Male Middle Aged Magnetic Resonance Imaging Workflow Rectal Neoplasms Humans Artificial Intelligence Female
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