AIMC Topic: Image Interpretation, Computer-Assisted

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DCE-MRI based deep learning analysis of intratumoral subregion for predicting Ki-67 expression level in breast cancer.

Magnetic resonance imaging Mar 13, 2025
OBJECTIVE: To evaluate whether deep learning (DL) analysis of intratumor subregion based on dynamic contrast-enhanced MRI (DCE-MRI) can help predict Ki-67 expression level in breast cancer.
Middle Aged Deep Learning Contrast Media Aged Adult Breast Neoplasms Humans Magnetic Resonance Imaging Ki-67 Antigen Algorithms Dynamic Contrast Enhanced Magnetic Resonance Imaging Breast Image Interpretation, Computer-Assisted Retrospective Studies Female
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Machine learning prediction of right ventricular volume and ejection fraction from two-dimensional echocardiography in patients with pulmonary regurgitation.

The international journal of cardiovascular imaging Mar 13, 2025
Right ventricular (RV) end-diastolic volume (RVEDV) and ejection fraction (RVEF) by cardiac MRI (cMRI) guide management in chronic pulmonary regurgitation (PR). Two-dimensional echocardiography suboptimally correlate with RV volumes. This study teste...
Echocardiography Severity of Illness Index Adolescent Adult Male Stroke Volume Image Interpretation, Computer-Assisted Ventricular Function, Right Pulmonary Valve Insufficiency Humans Machine Learning Female Reproducibility of Results Prognosis Chronic Disease Young Adult Retrospective Studies Predictive Value of Tests Ventricular Dysfunction, Right
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NaMA-Mamba: Foundation model for generalizable nasal disease detection using masked autoencoder with Mamba on endoscopic images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Mar 12, 2025
Artificial intelligence (AI) has shown great promise in analyzing nasal endoscopic images for disease detection. However, current AI systems require extensive expert-labeled data for each specific medical condition, limiting their applications. In th...
Nose Diseases Humans Endoscopy Artificial Intelligence Image Interpretation, Computer-Assisted Machine Learning Autoencoder Algorithms
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SSAT-Swin: Deep Learning-Based Spinal Ultrasound Feature Segmentation for Scoliosis Using Self-Supervised Swin Transformer.

Ultrasound in medicine & biology Mar 12, 2025
OBJECTIVE: Scoliosis, a 3-D spinal deformity, requires early detection and intervention. Ultrasound curve angle (UCA) measurement using ultrasound images has emerged as a promising diagnostic tool. However, calculating the UCA directly from ultrasoun...
Humans Female Male Deep Learning Image Interpretation, Computer-Assisted Adolescent Scoliosis Child Ultrasonography Spine
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UniSAL: Unified Semi-supervised Active Learning for histopathological image classification.

Medical image analysis Mar 12, 2025
Histopathological image classification using deep learning is crucial for accurate and efficient cancer diagnosis. However, annotating a large amount of histopathological images for training is costly and time-consuming, leading to a scarcity of avai...
Supervised Machine Learning Algorithms Humans Neural Networks, Computer Neoplasms Image Interpretation, Computer-Assisted Deep Learning
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FEGGNN: Feature-Enhanced Gated Graph Neural Network for robust few-shot skin disease classification.

Computers in biology and medicine Mar 9, 2025
Accurate and timely classification of skin diseases is essential for effective dermatological diagnosis. However, the limited availability of annotated images, particularly for rare or novel conditions, poses a significant challenge. Although few-sho...
Image Interpretation, Computer-Assisted Graph Neural Networks Algorithms Diagnosis, Computer-Assisted Skin Diseases Humans Neural Networks, Computer
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Automatic cerebral microbleeds detection from MR images via multi-channel and multi-scale CNNs.

Computers in biology and medicine Mar 7, 2025
BACKGROUND: Computer-aided detection (CAD) systems have been widely used to assist medical professionals in interpreting medical images, aiding in the detection of potential diseases. Despite their usefulness, CAD systems cannot yet fully replace doc...
Cerebral Hemorrhage Image Interpretation, Computer-Assisted Neural Networks, Computer Algorithms Female Male Deep Learning Magnetic Resonance Imaging Humans
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AI-based association analysis for medical imaging using latent-space geometric confounder correction.

Medical image analysis Mar 6, 2025
This study addresses the challenges of confounding effects and interpretability in artificial-intelligence-based medical image analysis. Whereas existing literature often resolves confounding by removing confounder-related information from latent rep...
Artificial Intelligence Algorithms Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Humans
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UGS-M3F: unified gated swin transformer with multi-feature fully fusion for retinal blood vessel segmentation.

BMC medical imaging Mar 6, 2025
Automated segmentation of retinal blood vessels in fundus images plays a key role in providing ophthalmologists with critical insights for the non-invasive diagnosis of common eye diseases. Early and precise detection of these conditions is essential...
Algorithms Deep Learning Image Processing, Computer-Assisted Humans Fundus Oculi Image Interpretation, Computer-Assisted Retinal Vessels
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D-GET: Group-Enhanced Transformer for Diabetic Retinopathy Severity Classification in Fundus Fluorescein Angiography.

Journal of medical systems Mar 6, 2025
Early detection of Diabetic Retinopathy (DR) is vital for preserving vision and preventing deterioration of eyesight. Fundus Fluorescein Angiography (FFA), recognized as the gold standard for diagnosing DR, effectively reveals abnormalities in retina...
Humans Diabetic Retinopathy Algorithms Severity of Illness Index Image Interpretation, Computer-Assisted Deep Learning Fluorescein Angiography Fundus Oculi
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