Radiology

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

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Burnout crisis in Chinese radiology: will artificial intelligence help?

OBJECTIVES: To assess the correlation between the use of artificial intelligence (AI) software and b...

TIRADS-based artificial intelligence systems for ultrasound images of thyroid nodules: protocol for a systematic review.

PURPOSE: The thyroid imaging reporting and data system (TIRADS) was developed as a standard global t...

Generating synthetic clinical text with local large language models to identify misdiagnosed limb fractures in radiology reports.

Large language models (LLMs) demonstrate impressive capabilities in generating human-like content an...

A Near-Infrared Imaging System for Robotic Venous Blood Collection.

Venous blood collection is a widely used medical diagnostic technique, and with rapid advancements i...

Predicting intraoperative 5-ALA-induced tumor fluorescence via MRI and deep learning in gliomas with radiographic lower-grade characteristics.

PURPOSE: Lower-grade gliomas typically exhibit 5-aminolevulinic acid (5-ALA)-induced fluorescence in...

Enhanced breast mass segmentation in mammograms using a hybrid transformer UNet model.

Breast mass segmentation plays a crucial role in early breast cancer detection and diagnosis, and wh...

A Parkinson's disease-related nuclei segmentation network based on CNN-Transformer interleaved encoder with feature fusion.

Automatic segmentation of Parkinson's disease (PD) related deep gray matter (DGM) nuclei based on br...

CIS-UNet: Multi-class segmentation of the aorta in computed tomography angiography via context-aware shifted window self-attention.

Advancements in medical imaging and endovascular grafting have facilitated minimally invasive treatm...

Computer tomography-based radiomics combined with machine learning for predicting the time since onset of epidural hematoma.

Estimation of the age of epidural hematoma (EDH) is a challenge in clinical forensic medicine, and t...

Model Based on Ultrasound Radiomics and Machine Learning to Preoperative Differentiation of Follicular Thyroid Neoplasm.

OBJECTIVES: To evaluate the value of radiomics based on ultrasonography in differentiating follicula...

Whole Slide Imaging, Artificial Intelligence, and Machine Learning in Pediatric and Perinatal Pathology: Current Status and Future Directions.

The integration of artificial intelligence (AI) into healthcare is becoming increasingly mainstream....

A combined model integrating radiomics and deep learning based on multiparametric magnetic resonance imaging for classification of brain metastases.

BACKGROUND: Radiomics and deep learning (DL) can individually and efficiently identify the pathologi...

Exploratory analysis of Type B Aortic Dissection (TBAD) segmentation in 2D CTA images using various kernels.

Type-B Aortic Dissection is a rare but fatal cardiovascular disease characterized by a tear in the i...

Artificial intelligence: a primer for pediatric radiologists.

Artificial intelligence (AI) is increasingly recognized for its transformative potential in radiolog...

Evolving and Novel Applications of Artificial Intelligence in Abdominal Imaging.

Advancements in artificial intelligence (AI) have significantly transformed the field of abdominal r...

The study on ultrasound image classification using a dual-branch model based on Resnet50 guided by U-net segmentation results.

In recent years, the incidence of nodular thyroid diseases has been increasing annually. Ultrasonogr...

Technical feasibility of automated blur detection in digital mammography using convolutional neural network.

BACKGROUND: The presence of a blurred area, depending on its localization, in a mammogram can limit ...

GraFMRI: A graph-based fusion framework for robust multi-modal MRI reconstruction.

PURPOSE: This study introduces GraFMRI, a novel framework designed to address the challenges of reco...

Application of magnetic resonance imaging and artificial intelligence algorithms in cancer screening.

In this society with a high incidence of cancer, cancer screening has become an important method to ...

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