Radiology

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Equivariant Spatiotemporal Transformers with MDL-Guided Feature Selection for Malignancy Detection in Dynamic PET

Dynamic Positron Emission Tomography (PET) scans offer rich spatiotemporal data for detecting malign...

Automated Assessment of Choroidal Mass Dimensions Using Static and Dynamic Ultrasonographic Imaging

To develop and validate an artificial intelligence (AI)-based model that automatically measures chor...

Miniaturized Four-Dimensional Functional Ultrasound for Mapping Human Brain Activity

Real-time brain monitoring for neurosurgery and neuroscience research of natural behaviors demands p...

Machine Learning-Based Reconstruction of 2D MRI for Quantitative Morphometry in Epilepsy

Structural neuroimaging analyses require ‘research quality’ images, acquired with costly MRI acquisi...

Classification of familial and non-familial ADHD using auto-encoding network and binary hypothesis testing

Family history is one the most powerful risk factor for attention-deficit/hyperactivity disorder (AD...

Automated biometry for assessing cephalopelvic disproportion in 3D 0.55T fetal MRI at term

Fetal MRI offers detailed three-dimensional visualisation of both fetal and maternal pelvic anatomy,...

Real-world federated learning for the brain imaging scientist

Federated learning (FL) could boost deep learning in neuroimaging but is rarely deployed in a real-w...

A Hybrid CNN-Transformer Deep Learning Model for Differentiating Benign and Malignant Breast Tumors Using Multi-View Ultrasound Images

Breast cancer is a leading malignancy threatening women’s health globally, making early and accurate...

Using deep learning methods to shorten acquisition time in children’s renal cortical imaging

This study evaluates the capability of diffusion-based generative models to reconstruct diagnostic-q...

Quantitative Analysis of Breast Nuclei Morphology for Cancer Diagnosis Using Supervised Machine Learning

Breast cancer is the most frequently diagnosed malignancy among women worldwide and a major cause of...

Evaluating Large Language Model Diagnostic Performance on JAMA Clinical Challenges via a Multi-Agent Conversational Framework

Standard clinical LLM benchmarks use multiple-choice vignettes that present all information up front...

Toward Non-Invasive Voice Restoration: A Deep Learning Approach Using Real-Time MRI

Despite recent advances in brain–computer interfaces (BCIs) for speech restoration, existing systems...

Dual-Branch EfficientNet Architecture for ACL Tear Detection in Knee MRI

We propose a deep learning approach for detecting anterior cruciate ligament (ACL) tears from knee M...

Feature-Based Machine Learning for Brain Metastasis Detection Using Clinical MRI

Brain metastases represent one of the most common intracranial malignancies, yet early and accurate ...

Deep Learning for Breast Mass Discrimination: Integration of B-Mode Ultrasound & Nakagami Imaging with Automatic Lesion Segmentation

This study aims to enhance breast cancer diagnosis by developing an automated deep learning framewor...

Predictive modeling of hematoma expansion from non-contrast computed tomography in spontaneous intracerebral hemorrhage patients

Hematoma expansion is a consistent predictor of poor neurological outcome and mortality after sponta...

Machine Learning-Based Meningioma Location Classification Using Vision Transformers and Transfer Learning

In this study, we aimed to use advanced machine learning (ML) techniques, specifically transfer lear...

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