Latest AI and machine learning research in radiology for healthcare professionals.
BACKGROUND: Accurate segmentation of the clinical target volume (CTV) corresponding to the prostate with or without proximal seminal vesicles is required on transrectal ultrasound (TRUS) images during prostate brachytherapy procedures. Implanted needles cause artifacts that may make this task difficult and time-consuming. Thus, previous studies have focused on the simpler problem of segmentation i...
Artificial intelligence (AI) has the potential to bring transformative improvements to the field of radiology; yet, there are barriers to widespread clinical adoption. One of the most important barriers has been access to large, well-annotated, widely representative medical image datasets, which can be used to accurately train AI programs. Creating such datasets requires time and expertise and run...
Early detection of unruptured intracranial aneurysms (UIAs) enables better rupture risk and preventative treatment assessment. UIAs are usually diagno...
To properly repair and maintain implants, which are bone tissue implants that replace natural tooth roots, it is crucial to accurately identify their ...
Major depressive disorder (MDD) is often accompanied with suicidal ideation (SI). Previous studies suggested that MDD patients who experienced suicida...
BACKGROUND: To investigate the potential of combining compressed sensing (CS) and deep learning (DL) for accelerated two-dimensional (2D) and three-di...
BACKGROUND: Recent advancements in computing power and state-of-the-art algorithms have helped in more accessible and accurate diagnosis of numerous d...
BACKGROUND: ScanNavAnatomy Peripheral Nerve Block (ScanNav™) is an artificial intelligence (AI)-based device that produces a colour overlay on real-ti...
BACKGROUND: For men with prostate cancer, radiographic progression may occur without a concordant rise in prostate-specific antigen (PSA). Our study a...
The reconstruction of blood velocity in a vessel from contrast enhanced x-ray computed tomography projections is a complex inverse problem. It can be ...
PURPOSE: The aim of this study was to compare the physical properties of small focal spot imaging with deep learning reconstruction (DLR) and small or...
In minimally invasive endovascular procedures, surgeons rely on catheters with low dexterity and high aspect ratios to reach an anatomical target. How...
PURPOSE: Positron emission tomography (PET) image quality can be improved by higher injected activity and/or longer acquisition time, but both may oft...
INTRODUCTION: Conventional interventional modalities for preserving or improving cognitive function in patients with brain tumour undergoing radiother...
The fifteenth edition of the international workshop organized by the "Tumour Targeting and Radiotherapies network" of the Cancéropôle Grand-Ouest focu...
Despite recent medical advancements, breast cancer remains one of the most prevalent and deadly diseases among women. Although machine learning-based ...
Positron emission tomography/computed tomography (PET/CT) is increasingly used in oncology, neurology, cardiology, and emerging medical fields. The su...
BACKGROUND AND OBJECTIVE: Deep learning based medical image analysis technologies have the potential to greatly improve the workflow of neuro-radiolog...
Ultrasound imaging is commonly used to aid in fetal development. It has the advantage of being real-time, low-cost, non-invasive, and easy to use. How...