Radiology

Artificial intelligence for automated detection of joint bleeding via ultrasound in hemophilia: advancing standardization.

BACKGROUND: Musculoskeletal ultrasound (US) is a noninvasive tool for joint assessment in persons with hemophilia. Early detection of joint bleeding using a remote US system operated by patients or caregivers and reviewed by Comprehensive Care Centers could improve personalized management. A computer-aided diagnosis (CAD) system for automatic detection of joint effusion may support clinicians in p...

Non-contrast multimodal cardiac MRI for predicting coronary microvascular dysfunction in patients with hypertrophic cardiomyopathy.

OBJECTIVE: In hypertrophic cardiomyopathy (HCM), detection of coronary microcirculatory dysfunction (CMD) usually relies on contrast-enhanced cardiac magnetic resonance (CMR). This study sought to develop a practical non-contrast radiomics model to identify CMD, minimizing reliance on contrast agents. METHODS: A total of 290 patients with HCM were stratified by the presence or absence of CMD and r...

Carbon quantum dots exacerbate Parkinson's disease-like pathology through microglia-mediated neuroinflammatory responses with toxicological implications.

The global burden of Parkinson's disease (PD) is projected to double by 2050, with early-onset cases demonstrating accelerated progression and limited...

A universal machine learning model for the electronic density of states.

In the last few years several "universal" interatomic potentials have appeared, using machine-learning approaches to predict energy and forces of atom...

Fully automated, deep learning, cardiac CT-based multimodal network for cardiovascular risk stratification in high-risk perioperative patients.

AIMS: Major adverse cardiac events (MACE) significantly impact perioperative morbidity and mortality. We aimed to develop a fully automated multimodal...

An artificial intelligence prediction model for optimizing patient selection for cardiac imaging for the investigation of suspected coronary artery disease.

AIMS: Nearly, 40% of patients undergoing elective invasive coronary angiography (ICA) are diagnosed with non-obstructive coronary artery disease (CAD)...

Artificial Intelligence in Mammography Screening: A Narrative Review of Progress, Pitfalls, and Potential.

Artificial intelligence (AI), particularly deep learning (DL), is transforming the field of medical imaging and holds substantial promise for advancin...

Impact of Deep Learning-Based Time-of-Flight PET Images of Small Tumors Using a Human Anatomic Phantom.

Time-of-flight (ToF) in PET improves image quality by enhancing the signal-to-noise ratio, and recent deep learning (DL)-based ToF (DL-ToF) methods fu...

MRI In Vivo Detection of Amyloid-β Protein Deposition in Different Brain Regions of Patients with AD and MCI.

To investigate a non-invasive magnetic resonance imaging (MRI)-based method for detecting amyloid-β (Aβ) protein deposition in different brain regions...

3D region-growing nnU-Net improves pulmonary embolism detection on CTPA: a dual-cohort validation study.

OBJECTIVES: We compared three customized nnU-Net models (A: baseline two-dimensional (2D); B: 2D + region-growing; C: three-dimensional (3D) + region-...

Predicting the Value of Radiology Artificial Intelligence Applications: Large-Scale Predeployment Evaluation of a Portfolio of Models.

Background: Real-world performance of radiology artificial intelligence (AI) applications frequently diverges from previously reported results, creati...

Deconstruction and reconstruction of degrading effects in ultrasound imaging: aberration, multiple reverberation, and trailing reverberation.

Ultrasound image degradation in the human body arises from the propagation and reflection of acoustical waves in a complex acoustical environment. The...

Comparison of Atheroma Burden Changes Using Conventional vs. End-Diastolic Intravascular Ultrasound Segmentation　- Post Hoc Analysis of the PACMAN-AMI Study.

BACKGROUND: This study compared changes in percentage atheroma volume (PAV) using an end-diastolic (ED) intravascular ultrasound (IVUS) segmentation a...

Machine Learning-Based Preoperative Predicting TERT Promoter Mutation and EGFR Gene Amplification Phenotype in IDH Wild-Type Glioblastoma Using Advanced MR Habitat Imaging.

BACKGROUND AND PURPOSE: The telomerase reverse transcriptase (TERT) gene promoter mutation is a crucial factor for identifying an isocitrate dehydroge...

Multimodal CT-based imaging biomarkers for mechanical reperfusion in acute ischemic stroke.

Mechanical thrombectomy (MT) has emerged as the primary treatment for restoring blood flow in acute ischemic stroke (AIS) patients with large vessel o...

Performance of deep learning-based segmentation of soft tissue sarcoma by MRI sequence, tumor type and location.

OBJECTIVE: Soft tissue sarcomas (STS) are a rare and heterogeneous group of tumors that pose a significant challenge for surgical planning. This study...

PHIVE: A physics-informed variational encoder enables rapid spectral fitting of brain metabolite mapping at 7T.

Magnetic Resonance Spectroscopic Imaging (MRSI) enables non-invasive mapping of brain metabolite concentrations but remains computationally intensive ...

FADFNet: A fine-tunable and adaptive decomposition-fusion network for cross-dataset low-dose CT and low-dose PET image reconstruction.

Low-dose computed tomography (LDCT) and low-dose positron emission tomography (LDPET) are pivotal for minimizing radiation risks in clinical practice,...

Convolutional neural networks for prostate cancer detection, classification, and segmentation: A systematic review and bibliometric analysis.

BACKGROUND: Prostate cancer represents the second most common malignancy among men globally, necessitating accurate diagnostic methodologies for optim...

Development and validation of a multimodal deep learning model for early esophageal squamous neoplasia detection and invasion depth prediction.

Early detection of esophageal squamous cell carcinoma (ESCC) is critical for optimizing patient outcomes. Magnifying endoscopy and endoscopic ultrason...