Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

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Step-by-Step Approach to Design Image Classifiers in AI: An Exemplary Application of the CNN Architecture for Breast Cancer Diagnosis

In recent years, different Convolutional Neural Networks (CNNs) approaches have been applied for ima...

Revealing the Infiltration: Prognostic Value of Automated Segmentation of Non-Contrast-Enhancing Tumor in Glioblastoma

Precise delineation of non-contrast-enhancing tumor (nCET) in glioblastoma (GB) is critical for maxi...

Radiologist-AI workflow can be modified to reduce the risk of medical malpractice claims

Artificial Intelligence (AI) is rapidly changing the legal landscape of radiology. Results from a pr...

Towards automated multi-regional lung parcellation for 0.55-3T 3D T2w fetal MRI

Fetal MRI is increasingly being employed in the diagnosis of fetal lung anomalies and segmentation-d...

Clinical-grade autonomous cytopathology via whole-slide edge tomography

Cytopathology plays a central role in the early detection of cancers such as cervical, lung, and bla...

Assessing accuracy and legitimacy of multimodal large language models on Japan Diagnostic Radiology Board Examination

To assess and compare the accuracy and legitimacy of multimodal large language models (LLMs) on the ...

DWI and Clinical Characteristics Correlations in Acute Ischemic Stroke After Thrombolysis

Magnetic Resonance Diffusion-Weighted Imaging (DWI) is a crucial tool for diagnosing acute ischemic ...

CMANet: Cross-Modal Attention Network for 3-D Knee MRI and Report-Guided Osteoarthritis Assessment

Knee osteoarthritis (OA) is a leading cause of disability worldwide, with early identification of st...

Rad-Path Correlation of Deep Learning Models for Prostate Cancer Detection on MRI

While Deep Learning (DL) models trained on Magnetic Resonance Imaging (MRI) have shown promise for p...

AI-Derived Splenic Response in Cardiac PET Predicts Mortality: A Multi-Site Study

Inadequate pharmacologic stress may limit the diagnostic and prognostic accuracy of myocardial perfu...

Modeling the Impact of Social Determinants on Breast Cancer Screening: A Data-Driven Approach

This study addresses the critical implementation science challenge of operationalizing social determ...

CEREBLEED: Automated quantification and severity scoring of intracranial hemorrhage on non-contrast CT

Intracranial hemorrhage (ICH), whether spontaneous or traumatic, is a neurological emergency with hi...

Urethra contours on MRI: multidisciplinary consensus educational atlas and reference standard for artificial intelligence benchmarking

The urethra is a recommended avoidance structure for prostate cancer treatment. However, even subspe...

Cardiac Function Assessment with Deep-Learning-Based Automatic Segmentation of Free-Running 4D Whole-Heart CMR

Free-running (FR) cardiac MRI enables free-breathing ECG-free fully dynamic 5D (3D spatial+cardiac+r...

AI-Powered Segmentation and Prognosis with Missing MRI in Pediatric Brain Tumors

Brain MRI is the main imaging modality for pediatric brain tumors (PBTs); however, incomplete MRI ex...

Myocardial Native T1 Mapping in the German National Cohort (NAKO): Associations with Age, Sex, and Cardiometabolic Risk Factors

In cardiovascular magnetic resonance (CMR), myocardial native T1 mapping enables quantitative, non-i...

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