Radiology

Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project.

This review paper presents the practical development of imaging biomarkers in the scope of the PRIMA...

A despeckling method for ultrasound images utilizing content-aware prior and attention-driven techniques.

The despeckling of ultrasound images contributes to the enhancement of image quality and facilitates...

Considerations for environmental sustainability in clinical radiology and radiotherapy practice: A systematic literature review and recommendations for a greener practice.

INTRODUCTION: Environmental sustainability (ES) in healthcare is an important current challenge in t...

A Cadaveric Feasibility Study of an Automatic Multi-Degrees of Freedom Surgical Robot for Percutaneous Scaphoid Guide Pin Insertion.

Percutaneous fixation of scaphoid fractures need accurate guide pin insertion. The emergence of com...

Diagnostic performance of a novel deep learning attenuation correction software for MPI using a cardio dedicated CZT camera. Experience in the clinical practice.

PURPOSE: To evaluate the diagnostic performance of a novel deep learning attenuation correction soft...

The power of the radiologist's last word: can deep learning models accurately differentiate between high-grade gliomas and metastasis through natural language processing on radiology reports?

Ready for testing artificial intelligence in radiology clinical practice: We would do well to be in the front line leveraging their strengths but also highlighting today weaknesses.

Classification of breast lesions in ultrasound images using deep convolutional neural networks: transfer learning versus automatic architecture design.

Deep convolutional neural networks (DCNNs) have demonstrated promising performance in classifying br...

Distinct subtypes of spatial brain metabolism patterns in Alzheimer's disease identified by deep learning-based FDG PET clusters.

PURPOSE: Alzheimer's disease (AD) is a heterogeneous disease that presents a broad spectrum of clini...

Deep learning enabled fast 3D brain MRI at 0.055 tesla.

In recent years, there has been an intensive development of portable ultralow-field magnetic resonan...

Deep neural network-estimated age using optical coherence tomography predicts mortality.

The concept of biological age has emerged as a measurement that reflects physiological and functiona...

A look at radiation detectors and their applications in medical imaging.

The effectiveness and precision of disease diagnosis and treatment have increased, thanks to develop...

Diagnosis of diabetes mellitus using high frequency ultrasound and convolutional neural network.

The incidence of diabetes mellitus has been increasing, prompting the search for non-invasive diagno...

Adaptive machine learning method for photoacoustic computed tomography based on sparse array sensor data.

BACKGROUND AND OBJECTIVE: Photoacoustic computed tomography (PACT) is a non-invasive biomedical imag...

A comparison of 18 F-FDG PET-based radiomics and deep learning in predicting regional lymph node metastasis in patients with resectable lung adenocarcinoma: a cross-scanner and temporal validation study.

OBJECTIVE: The performance of 18 F-FDG PET-based radiomics and deep learning in detecting pathologic...

Deep-Learning-Aided Evaluation of Spondylolysis Imaged with Ultrashort Echo Time Magnetic Resonance Imaging.

Isthmic spondylolysis results in fracture of pars interarticularis of the lumbar spine, found in as ...

Ultra-fast ultrasound blood flow velocimetry for carotid artery with deep learning.

Accurate measurement of blood flow velocity is important for the prevention and early diagnosis of a...

Predicting 'Brainage' in late childhood to adolescence (6-17yrs) using structural MRI, morphometric similarity, and machine learning.

Brain development is regularly studied using structural MRI. Recently, studies have used a combinati...

Autonomous medical needle steering in vivo.

The use of needles to access sites within organs is fundamental to many interventional medical proce...

Imaging of Solid Pulmonary Nodules.

Early detection with accurate classification of solid pulmonary nodules is critical in reducing lung...

Deep Learning Estimation of 10-2 Visual Field Map Based on Macular Optical Coherence Tomography Angiography Measurements.

PURPOSE: To develop deep learning (DL) models estimating the central visual field (VF) from optical ...