Radiology

Multimodal Machine Learning and Deep Learning Approaches for Parkinson's Disease Diagnosis: A Comprehensive Survey.

Parkinson's disease (PD) is a progressive neurodegenerative disorder that profoundly affects patients' quality of life. Early and accurate diagnosis is essential for timely intervention and improved outcomes, yet traditional clinical evaluations often fall short. This review examines recent advancements in machine learning (ML) and deep learning (DL) techniques that promise more objective, quantit...

The influence of age and the presence of prostate cancer on prostate volume, PSA and PSA density.

OBJECTIVE: To assess prostate volume (PV) changes with age in symptomatic and asymptomatic men with and without clinically significant prostate cancer (csPCa). In symptomatic patients, we additionally analysed the effect of age and csPCa on PSA and PSA-density (PSA-D) and compared these to current National Institute for Health and Care Excellence (NICE) recommended PSA age-range thresholds. Patien...

AI-Based STroke Risk fActor Classification and Treatment (ABSTRACT) study.

BACKGROUND: Stroke is a leading cause of death and disability worldwide, costing the UK approximately £26 billion annually. While lifestyle modificati...

Development of an automatic segmentation system for anterolateral thigh flap perforators in maxillofacial reconstruction.

The anterior thigh (ALT) flap is commonly used in reconstructive surgery, especially in maxillary reconstruction. Accurately identifying the perforato...

Mask - Region-based Convolutional Neural Networks (R-CNN) with Radiomics Integration and Gray Level Co-occurrence Matrix (GLCM) for brain tumor detection and segmentation.

Early diagnosis of brain tumors is important for successful treatment and better patient consequences in industrial information systems. This research...

Artificial Intelligence-Based Analysis of Central Nervous System Vasculopathy in Pediatric Sickle Cell Anemia.

In children with sickle cell anemia (SCA), central nervous system (CNS) complications such as chronic vasculopathy, silent cerebral infarcts, and over...

Accelerating MRI With Longitudinally-Informed Latent Posterior Sampling.

PURPOSE: To accelerate MRI acquisition by incorporating the previous scans of a subject during reconstruction. Although longitudinal imaging constitut...

Parietal repetitive transcranial magnetic stimulation enhances functional connectivity in patients with minimally conscious state.

The basis of disorders of consciousness is the destruction of brain functional connectivity, and the restoration of damaged connectivity is considered...

MRI-based deep learning and radiomics for preoperative prediction of P53abn endometrial cancer: A multicenter study.

PURPOSE: To develop and validate a non-invasive magnetic resonance imaging (MRI)-based deep learning and radiomics approach for the preoperative diffe...

Cerebrovascular 5D flow MRI.

BACKGROUND: 4D flow MRI facilitates quantification of cardiac phase-resolved blood velocity vector fields and has successfully been deployed to study ...

Defining Physician-AI Collaboration in Pulmonary and Critical Care Medicine: Concepts and Illustrative Examples for Clinical Reasoning.

The exponential growth of medical data and complexity in Pulmonary and Critical Care Medicine (PCCM) necessitates a paradigm shift in clinical reasoni...

Reproducibility of cardiac volumetric parameters derived from fully automatically prescribed image planes: a direct comparison to manual planning at 1.5-T and 3-T MRI.

OBJECTIVES: The prescription of cardiac MRI (CMR) image planes is essential for comparable volumetric assessment, but manual planning is time-consumin...

Features of B-mode ultrasound and contrast-enhanced ultrasound of carotid plaque based on deep learning enhance the prediction of vulnerable plaques associated with acute ischemic stroke.

OBJECTIVES: To develop an AI model using ultrasound features of carotid plaque for predicting the risk of acute ischemic stroke (AIS) and assess its e...

Performance of AI vs radiology residents in the detection of intracranial hemorrhage on emergency CT: a real-world analysis.

OBJECTIVE: To evaluate the performance of a commercial artificial intelligence (AI) software in detecting intracranial hemorrhage (ICH) in emergency s...

Prospective pilot evaluation of a deep learning model for kidney stone detection on CT using a web-based workflow platform.

Rapid and reliable detection of kidney stones on non-contrast abdominal CT is essential for timely decision-making in emergency radiology. However, ri...

Optimal management of oligometastatic prostate cancer: current state and future directions.

PURPOSE: Oligometastatic prostate cancer (oligoPCa) represents a clinical state of limited metastatic spread in which metastasis-directed therapy (MDT...

Strain Imaging in Heart Failure.

Strain imaging, performed with echocardiography and cardiovascular magnetic resonance (CMR), is a noninvasive technique for detecting subclinical myoc...

Climate Change and Globally Sustainable Cardiovascular Magnetic Resonance.

Climate change is driving increased cardiovascular risk and demand for medical imaging. While cardiovascular magnetic resonance (CMR) plays a critical...

Transformer-based architectures in MRI brain tumor segmentation: A review.

Transformers have been actively utilized in the deep learning field recently. Vision Transformer (ViT), as one of its important applications in the co...

Artificial Intelligence Impact on Radiologist Performance in Breast Cancer Screening with Digital Breast Tomosynthesis.

PURPOSE: Assess impact of artificial intelligence (AI) on radiologists' detection of cancer on digital breast tomosynthesis (DBT) exams based on densi...