Radiology

Emerging applications of artificial intelligence for obstetric ultrasound: A scoping review.

BACKGROUND: The WHO recommends that all pregnant women receive an ultrasound (US) scan prior to 24 weeks gestation to encourage early identification of various conditions, such as fetal anomalies, multiple gestation, and placental abnormalities; however, global access to US remains limited. This has prompted many research groups to develop artificial intelligence (AI) approaches for obstetric US. ...

Artificial intelligence application in the prediction of spontaneous preterm birth by cervical length in the first trimester of pregnancy: Comparison of three measurement methods.

OBJECTIVES: The current study evaluates the efficacy of artificial intelligence (AI)-assisted measurement of cervical length (CL) in predicting spontaneous preterm birth (sPTB), comparing the traditional single-line and two-line methods with the innovative AI-line method in the first trimester of pregnancy. MATERIALS AND METHODS: This study is a retrospective secondary analysis of ultrasound image...

Knowledge-guided multi-geometric window transformer for cardiac cine MRI reconstruction.

Magnetic resonance imaging (MRI) plays a crucial role in clinical diagnosis, yet traditional MR image acquisition often requires a prolonged duration,...

Predicting Cerebral Aneurysm Recurrence after Coil Embolization: A Novel Deep Learning Approach Using Time-of-flight Magnetic Resonance Angiography.

The recurrence of cerebral aneurysms after coil embolization remains a significant concern in clinical practice. This study introduced a novel approac...

Hemispheric Network Dynamics During Auditory Language Comprehension and Its Clinical Implications Regarding Resting-State Functional Magnetic Resonance Imaging.

PURPOSE: With growing interest in modeling neurobehavior, there is increased interest in understanding patterns of functional connectivity (FC) during...

Diagnostic Accuracy of Artificial Intelligence in Detecting Pleural Effusion on Ultrasound Imaging: A Systematic Review and Meta-Analysis.

Artificial intelligence (AI) interpretation of ultrasound (US) images is promising, yet its accuracy in diagnosing pleural effusions remains unclear. ...

Wavelet-Based Frequency Replacement and Edge Enhancement for Semi-Supervised Fetal Ultrasound Image Segmentation.

OBJECTIVES: Ultrasound image segmentation remains a significant challenge due to inherent low contrast and blurred anatomical boundaries. Fully superv...

Workflow-embedded AI as a cognitive scaffold: A randomized trial on knowledge retention and diagnostic competency in undergraduate radiology education.

BACKGROUND: Traditional didactic methods in medical imaging education, predominantly reliant on static images (non-augmented, traditional PACS workflo...

Automatic measurement and evaluation of anterior segment anatomical structures via UBM images using a deep learning-based approach.

PURPOSE: To develop a deep-learning model capable of measuring essential anterior segment (AS) parameters derived from preoperative ultrasound biomicr...

UltraMN: Advancing Real-Time Median Nerve Ultrasound Monitoring With a Multitask Deep Learning Framework.

OBJECTIVE: This study aims to develop an advanced deep learning framework to overcome the challenges associated with real-time ultrasound monitoring o...

3D imaging-based AI models outperform demographic models and excel in tibial sizing compared with 2D models in total knee arthroplasty planning: A systematic review.

PURPOSE: Accurate preoperative implant sizing is a critical component of successful total knee arthroplasty (TKA). Artificial intelligence (AI) has em...

Rapid spatio-temporal MR fingerprinting using physics-informed implicit neural representation.

The potential of Magnetic Resonance Fingerprinting (MRF), which allows for rapid and simultaneous multi-parametric quantitative MRI, is often limited ...

Year in Review: Axial Spondyloarthritis.

Axial spondyloarthritis is a chronic inflammatory disease primarily affecting the sacroiliac joints and spine. Over the past two years, significant pr...

MRI-to-PET synthesis via deep learning for amyloid-β quantification in Alzheimer's disease.

OBJECTIVES: Amyloid-β (Aβ) PET is crucial for diagnosing and monitoring Alzheimer's disease (AD), but its high cost and radiation exposure limit its u...

How much radiologist time can be saved by implementing AI in screen-reading mammograms?

OBJECTIVE: There is a lack of breast radiologists in Norway and in Europe. Artificial intelligence (AI) offers an alternative to solely human readers ...

Emerging Diagnostic Indications for Endoscopic Ultrasound.

Endoscopic ultrasound (EUS) has evolved from a diagnostic imaging tool into a versatile platform that enables high-precision access, sampling, and the...

The use of digital gamification, extended reality, artificial intelligence, and integrated digital learning tools in palliative care education of undergraduate nurses: A systematic review.

BACKGROUND: Nurses are at the forefront of providing palliative care, playing a critical role in ensuring high-quality support for patients and their ...

Decoding Temporomandibular Disorders: Identifying Stage-Specific and Functional Patterns in the Articular Disc.

BACKGROUND: Despite affecting approximately 30% of the population, the pathogenesis of temporomandibular disorders (TMD) remains poorly understood. Co...

[When everything is well-coordinated in an interdisciplinary manner-Is there a need for operating room management?].

Even in the ideal case of well-coordinated cooperation between anesthesiological and surgical as well as interventional colleagues, a departmental con...

Building a national repository of dural-based lesions: clinical, pathological, and demographic insights from the Indian population.

BACKGROUND: Meningiomas are the most common dural-based intracranial tumors, yet Indian literature is predominantly composed of limited single-center ...