Radiology

Transformative Role of Advanced Neural Computation in Clinical Image Diagnostics: A Review of Key Concepts and Applications.

Medical imaging plays a crucial role in modern diagnostic practices, but traditional techniques often face limitations in accuracy, efficiency, and scalability. The emergence of deep learning (DL) has led to significant improvements that are transforming this field. This review discusses how DL algorithms are enhancing diagnostic imaging by improving accuracy, enabling automated analysis, and supp...

Early Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer using a Longitudinal US-based Stack-model.

RATIONALE AND OBJECTIVES: To evaluate the diagnostic performance of a longitudinal ultrasound (US)-based stack-model for early prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer, as well as its practicality in assisting radiologists with diagnostic ability. MATERIALS AND METHODS: A total of 974 patients who underwent NAC were retrospectively inclu...

BoneCoT: multicentre validation of a whole-body skeleton foundation model for bone metastases guided by clinician-derived chain of thought.

Given the rising incidence of bone metastases, computed tomography is widely used worldwide as the initial imaging modality for their detection. Accur...

Machine learning algorithms in the estimation of sex from 3DCT-generated cranial and pelvic measurements.

Sex estimation from skeletal remains is a key component of forensic anthropology, with the skull and pelvis being the most sexually dimorphic elements...

An adaptive attention U-network for recognizing ultrasound images.

ObjectiveThe traditional method of intraspinal anesthesia relies on surface anatomical landmarks for positioning, which is associated with a low accur...

Systematic Review and Exploratory Meta-Analysis of AI-Enabled and Digital Technology-Assisted Interventions for Dental Anxiety During Dental Treatment.

BACKGROUND: Dental anxiety adversely affects receiving dental care when needed. Artificial intelligence (AI)-enabled and digital technology-assisted i...

A-eye: Automated 3D MRI segmentation and morphometric feature extraction for eye and orbit atlas construction.

In this study we introduce automated 3D segmentation of the healthy human adult eye and orbit from Magnetic Resonance Images, to improve ophthalmic di...

Innovation districts and transformative workspaces: A scoping review of AI-pet robots companionship for aging employees balancing productivity and wellbeing.

BACKGROUND: Considering the future of work and an aging workforce, emerging technologies such as artificial intelligence (AI) and robots are promising...

Dual-mode analysis of ischemic stroke based on urine SERS spectra and carotid B-ultrasound.

Achieving noninvasive high-frequency monitoring of ischemic stroke (IS) remains a major clinical challenge for timely intervention and precise seconda...

Lung ultrasound feature tracking to quantify regional lung strain in mechanically ventilated pigs.

BACKGROUND: In patients requiring respiratory support, clinicians rely on physical exam, radiologic, laboratory, and ventilator-derived measures for t...

FL-SDGIN: A federated graph learning approach for schizophrenia diagnosis integrating static and dynamic brain functional networks.

Recent magnetic resonance imaging (MRI) studies have revealed connectivity abnormalities in brain networks of schizophrenia (SZ). Graph Neural Network...

MRI for Prostate Cancer Local Staging: AJR Expert Panel Narrative Review.

The incremental value of multiparametric MRI (mpMRI) in prostate cancer staging has been increasingly recognized, with the accumulated literature indi...

Metabolically Faithful 3D PET Restoration via Volumetric Swin Transformers.

Positron Emission Tomography (PET) diagnostic precision is often compromised by low spatial resolution. Deep learning restoration models tend to sacri...

Comparative review of coronary CT angiography versus conventional catheter angiography: diagnostic value, clinical outcomes, and underlying technical principles.

INTRODUCTION: The diagnostic pathway for coronary artery disease (CAD) is actively transitioning toward noninvasive risk stratification. This review c...

Development and Validation of Machine Learning Models to Optimize Imaging and Referrals for Dizziness in the Emergency Department.

BACKGROUND: Dizziness and vertigo are common emergency department (ED) presentations, but only 2%-5% receive a serious diagnosis, such as stroke or tr...

Technical architecture for integrating vision-language models with DICOM viewers.

Integrating vision-language models (VLMs) into clinical radiology workflows requires exporting two-dimensional images that preserve diagnostic viewing...

Optimization of hypovascular liver lesion detectability in dual-energy CT using deep learning image reconstruction: a phantom study for potential iodine dose reduction.

OBJECTIVE: To determine the optimal low-keV level using deep learning image reconstruction (DLIR) that maximizes lesion detectability, and to assess t...

Multi-view constrained semi-supervised vertebra detection for 3D ultrasound spine volume.

BACKGROUND: Scoliosis is a spinal disorder characterized by a three-dimensional (3D) deformity of the vertebral column. 3D ultrasound imaging has been...

Optimisation of radiation dose and image quality in paediatric chest and abdominal CT examinations: A systematic review.

INTRODUCTION: Computed tomography (CT) is indispensable for the rapid evaluation of paediatric chest and abdominal pathology, yet it delivers relative...

Machine learning-guided discovery of poly(ethylene terephthalate)-binding modules to enhance durable whole-cell degradation.

The enzymatic degradation of poly(ethylene terephthalate) (PET) offers a sustainable route for plastic recycling but is often hindered by limited enzy...