Radiology

Physics-informed neural network for fast prediction of temperature distributions in cancerous breasts as a potential efficient portable AI-based diagnostic tool.

This work presents the development of a novel Physics-Informed Neural Network (PINN) method for fast forward simulation of heat transfer through cancerous breast models. The proposed PINN method combines deep learning and physical principles to predict the temperature distributions in breast tissues and identify potential abnormal regions indicating the presence of tumors. The PINN model is normal...

Diagnostic test accuracy study of a commercially available deep learning algorithm for ischemic lesion detection on brain MRIs in suspected stroke patients from a non-comprehensive stroke center.

PURPOSE: To estimate the ability of a commercially available artificial intelligence (AI) tool to detect acute brain ischemia on Magnetic Resonance Imaging (MRI), compared to an experienced neuroradiologist.

Artificial Intelligence to Improve Patient Understanding of Radiology Reports.

Diagnostic imaging reports are generally written with a target audience of other providers. As a result, the reports are written with medical jargon a...

Robotic-assisted total hip arthroplasty utilizing a fluoroscopy-guided system resulted in improved intra-operative efficiency relative to a computerized tomography-based platform.

Robotic-assisted total hip arthroplasty (THA) using a computerized-tomography (CT) based workflow increases surgical time relative to traditional manu...

A deep learning image analysis method for renal perfusion estimation in pseudo-continuous arterial spin labelling MRI.

Accurate segmentation of renal tissues is an essential step for renal perfusion estimation and postoperative assessment of the allograft. Images are u...

Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia.

(SCZ) is a severe mental disorder associated with persistent or recurrent psychosis, hallucinations, delusions, and thought disorders that affect appr...

Design and Validation of a Soft Robotic Simulator for Transseptal Puncture Training.

OBJECTIVE: Transseptal puncture (TP) is the technique used to access the left atrium of the heart from the right atrium during cardiac catheterization...

TumorDetNet: A unified deep learning model for brain tumor detection and classification.

Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment process and helps to save the lives of a large number of p...

An Interventional Radiologist's Primer of Critical Appraisal of Artificial Intelligence Research.

Recent advances in artificial intelligence (AI) are expected to cause a significant paradigm shift in all digital data-driven aspects of information g...

AC-Faster R-CNN: an improved detection architecture with high precision and sensitivity for abnormality in spine x-ray images.

In clinical medicine, localization and identification of disease on spinal radiographs are difficult and require a high level of expertise in the radi...

Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists.

We determined if a convolutional neural network (CNN) deep learning model can accurately segment acute ischemic changes on non-contrast CT compared to...

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 PRIMAGE (PRedictive In silico Multiscale Analytics to s...

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 precise treatment of conditions such as tumor can...

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 computer-assisted navigation and robotic surgery may ...

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 software (DLACS) for myocardial perfusion imaging (MPI...

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 breast lesions in 2D ultrasound (US) images. Exiting...

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 resonance imaging (MRI) for low-cost, shielding-free, and...

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

The effectiveness and precision of disease diagnosis and treatment have increased, thanks to developments in clinical imaging over the past few decade...

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 diagnostic methods. Although current methods exist, thes...

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 pathological regional nodal metastasis (pN+) in resectable l...