Radiology

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

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Lung MRI: Indications, Capabilities, and Techniques- Expert Panel Narrative Review.

Lung MRI provides both structural and functional information across a spectrum of parenchymal and ai...

A machine learning model using echocardiographic myocardial strain to detect myocardial ischemia.

Coronary functional assessment plays a critical role in guiding decisions regarding coronary revascu...

Systematic review on the impact of deep learning-driven worklist triage on radiology workflow and clinical outcomes.

OBJECTIVES: To perform a systematic review on the impact of deep learning (DL)-based triage for redu...

Deep Learning with Domain Randomization in Image and Feature Spaces for Abdominal Multiorgan Segmentation on CT and MRI Scans.

Purpose To develop a deep learning segmentation model that can segment abdominal organs on CT and M...

Non-invasive prediction of DCE-MRI radiomics model on CCR5 in breast cancer based on a machine learning algorithm.

BackgroundNon-invasive methods with universal prognostic guidance for detecting breast cancer (BC) s...

Imaging patterns and recommendations for diagnosis, staging, and management of lung cancer.

Lung cancer is the second most commonly diagnosed cancer worldwide. In the present era of targeted t...

Machine learning-based fusion model for predicting HER2 expression in breast cancer by Sonazoid-enhanced ultrasound: a multicenter study.

PURPOSE: To predict human epidermal growth factor receptor 2 (HER2) expression in breast cancer (BC)...

Res-ECA-UNet++: an automatic segmentation model for ovarian tumor ultrasound images based on residual networks and channel attention mechanism.

OBJECTIVE: Ultrasound imaging has emerged as the preferred imaging modality for ovarian tumor screen...

Cerebral ischemia detection using deep learning techniques.

Cerebrovascular accident (CVA), commonly known as stroke, stands as a significant contributor to con...

New Insights into the Diagnosis and Treatment of Hepatocellular Carcinoma.

Hepatocellular carcinoma remains one of the leading contributors to global cancer mortality, frequen...

Trading off Iodine and Radiation Dose in Coronary Computed Tomography.

Coronary CT angiography (CCTA) has seen steady progress since its inception, becoming a key player i...

FDG-PET as a pre-operative biomarker for predicting and optimizing response to subcallosal cingulate area deep brain stimulation.

BACKGROUND: Deep brain stimulation targeting the subcallosal cingulate area (SCC-DBS) has emerged as...

Application of ChatGPT 4.0 in radiological dose management: Perceptions of radiographers with varying expertise.

INTRODUCTION: Conversational Artificial Intelligence (CAI) is transforming healthcare by introducing...

Deep-Learning Reconstruction for 7T MP2RAGE and SPACE MRI: Improving Image Quality at High Acceleration Factors.

BACKGROUND AND PURPOSE: Deep learning (DL) reconstruction has been successful in realizing otherwise...

Challenges in Using Deep Neural Networks Across Multiple Readers in Delineating Prostate Gland Anatomy.

Deep learning methods provide enormous promise in automating manually intense tasks such as medical ...

A 3D deep learning model based on MRI for predicting lymphovascular invasion in rectal cancer.

BACKGROUND: The assessment of lymphovascular invasion (LVI) is crucial in the management of rectal c...

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