Radiology

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

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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 ...

Quantum Computing in Medicine.

Quantum computing (QC) represents a paradigm shift in computational power, offering unique capabilit...

Advancing clinical MRI exams with artificial intelligence: Japan's contributions and future prospects.

In this narrative review, we review the applications of artificial intelligence (AI) into clinical m...

Automatic TNM staging of colorectal cancer radiology reports using pre-trained language models.

BACKGROUND AND OBJECTIVE: Colorectal cancer is one of the major causes of cancer death worldwide. Es...

Manual data labeling, radiology, and artificial intelligence: It is a dirty job, but someone has to do it.

In this letter to the editor, authors highlight the key role of data labeling in training AI models ...

Validation of SynthSeg segmentation performance on CT using paired MRI from radiotherapy patients.

INTRODUCTION: Manual segmentation of medical images is labor intensive and especially challenging fo...

Application of artificial intelligence in VSD prenatal diagnosis from fetal heart ultrasound images.

BACKGROUND: Developing a combined artificial intelligence (AI) and ultrasound imaging to provide an ...

An intelligent magnetic resonance imagining-based multistage Alzheimer's disease classification using swish-convolutional neural networks.

Alzheimer's disease (AD) refers to a neurological disorder that causes damage to brain cells and res...

Accuracy of deep learning-based attenuation correction in Tc-GSA SPECT/CT hepatic imaging.

INTRODUCTION: Attenuation correction (AC) is necessary for accurate assessment of radioactive distri...

Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentation.

This paper explores uncertainty quantification (UQ) as an indicator of the trustworthiness of automa...

A Deep Learning-Based Approach to Characterize Skull Physical Properties: A Phantom Study.

Transcranial ultrasound imaging is a popular method to study cerebral functionality and diagnose bra...

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