Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

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Method of Forearm Muscles 3D Modeling Using Robotic Ultrasound Scanning.

The accurate assessment of muscle morphology and function is crucial for medical diagnostics, rehabi...

Information Extraction from Lumbar Spine MRI Radiology Reports Using GPT4: Accuracy and Benchmarking Against Research-Grade Comprehensive Scoring.

: This study aimed to create a pipeline for standardized data extraction from lumbar-spine MRI radio...

Deep learning prediction of mammographic breast density using screening data.

This study investigated a series of deep learning (DL) models for the objective assessment of four c...

A fine-tuned convolutional neural network model for accurate Alzheimer's disease classification.

Alzheimer's disease (AD) is one of the primary causes of dementia in the older population, affecting...

Deep learning-based uncertainty quantification for quality assurance in hepatobiliary imaging-based techniques.

Recent advances in deep learning models have transformed medical imaging analysis, particularly in r...

A semantic segmentation model for automatic precise identification of pituitary microadenomas with preoperative MRI.

PURPOSE: Magnetic resonance imaging (MRI) is an essential technique for diagnosing pituitary adenoma...

Unsupervised Domain Adaptation for Cross-Modality Cerebrovascular Segmentation.

Cerebrovascular segmentation from time-of-flight magnetic resonance angiography (TOF-MRA) and comput...

CorrMorph: Unsupervised Deformable Brain MRI Registration Based on Correlation Mining.

Deformable image registration, as a fundamental prerequisite for many medical image analysis tasks, ...

Unpaired Optical Coherence Tomography Angiography Image Super-Resolution via Frequency-Aware Inverse-Consistency GAN.

For optical coherence tomography angiography (OCTA) images, the limited scanning rate leads to a tra...

LGG-NeXt: A Next Generation CNN and Transformer Hybrid Model for the Diagnosis of Alzheimer's Disease Using 2D Structural MRI.

Incurable Alzheimer's disease (AD) plagues many elderly people and families. It is important to accu...

Self-Supervised Multi-Scale Multi-Modal Graph Pool Transformer for Sellar Region Tumor Diagnosis.

The sellar region tumor is a brain tumor that only exists in the brain sellar, which affects the cen...

LKAN: LLM-Based Knowledge-Aware Attention Network for Clinical Staging of Liver Cancer.

Clinical staging of liver cancer (CSoLC), an important indicator for evaluating primary liver cancer...

Deep Geometric Learning With Monotonicity Constraints for Alzheimer's Disease Progression.

Alzheimer's disease (AD) is a devastating neurodegenerative condition that precedes progressive and ...

Brain tumor segmentation and detection in MRI using convolutional neural networks and VGG16.

BackgroundIn this research, we explore the application of Convolutional Neural Networks (CNNs) for t...

Radiomics across modalities: a comprehensive review of neurodegenerative diseases.

Radiomics allows extraction from medical images of quantitative features that are able to reveal tis...

A Novel Theranostic Strategy for Malignant Pulmonary Nodules by Targeted CECAM6 with Zr/I-Labeled Tinurilimab.

Lung adenocarcinoma (LUAD) constitutes a major cause of cancer-related fatalities worldwide. Early i...

AI in SPECT Imaging: Opportunities and Challenges.

SPECT is a widely used imaging modality in nuclear medicine which provides essential functional insi...

FET-UNet: Merging CNN and transformer architectures for superior breast ultrasound image segmentation.

PURPOSE: Breast cancer remains a significant cause of mortality among women globally, highlighting t...

A domain adaptation model for carotid ultrasound: Image harmonization, noise reduction, and impact on cardiovascular risk markers.

Deep learning has been used extensively for medical image analysis applications, assuming the traini...

Large Language Models in Summarizing Radiology Report Impressions for Lung Cancer in Chinese: Evaluation Study.

BACKGROUND: Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities...

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