Radiology

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

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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...

In vivo evaluation of complex polyps with endoscopic optical coherence tomography and deep learning during routine colonoscopy: a feasibility study.

Standard-of-care (SoC) imaging for assessing colorectal polyps during colonoscopy, based on white-li...

Deep learning of structural MRI predicts fluid, crystallized, and general intelligence.

Can brain structure predict human intelligence? T1-weighted structural brain magnetic resonance imag...

Feasibility of Ultra-low Radiation and Contrast Medium Dosage in Aortic CTA Using Deep Learning Reconstruction at 60 kVp: An Image Quality Assessment.

OBJECTIVE: To assess the viability of using ultra-low radiation and contrast medium (CM) dosage in a...

Water-Stable Magnetic Lipiodol Micro-Droplets as a Miniaturized Robotic Tool for Drug Delivery.

Magnetic microrobots, designed to navigate the complex environments of the human body, show promise ...

From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.

With the increasing demand for precision medicine in cancer patients, radiogenomics emerges as a pro...

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