Radiology

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

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Optimized deep learning networks for accurate identification of cancer cells in bone marrow.

Radiologists utilize pictures from X-rays, magnetic resonance imaging, or computed tomography scans ...

Ultrasound for breast cancer detection: A bibliometric analysis of global trends between 2004 and 2024.

With the advancement of computer technology and imaging equipment, ultrasound has emerged as a cruci...

Optimization and correction of breast dynamic optical imaging projection data based on deep learning.

Breast cancer poses a significant health threat to women, necessitating advancements in diagnostic t...

TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs.

Characterization of breast parenchyma in dynamic contrast-enhanced magnetic resonance imaging (DCE-M...

Enhancing Aortic Aneurysm Surveillance: Transformer Natural Language Processing for Flagging and Measuring in Radiology Reports.

BACKGROUND: Incidental findings of aortic aneurysms (AAs) often go unreported, and established patie...

Deep plug-and-play MRI reconstruction based on multiple complementary priors.

Magnetic resonance imaging (MRI) is widely used in clinical diagnosis as a safe, non-invasive, high-...

Achieving accurate prostate auto-segmentation on CT in the absence of MR imaging.

BACKGROUND: Magnetic resonance imaging (MRI) is considered the gold standard for prostate segmentati...

Deep convolutional neural network for automatic segmentation and classification of jaw tumors in contrast-enhanced computed tomography images.

The purpose of this study was to evaluate the performance of convolutional neural network (CNN)-base...

Ultrasound-based artificial intelligence model for prediction of Ki-67 proliferation index in soft tissue tumors.

RATIONALE AND OBJECTIVES: To investigate the value of deep learning (DL) combined with radiomics and...

Enhancing Radiologists' Performance in Detecting Cerebral Aneurysms Using a Deep Learning Model: A Multicenter Study.

RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL)-based model for detecting...

Large Language Models can Help with Biostatistics and Coding Needed in Radiology Research.

INTRODUCTION: Original research in radiology often involves handling large datasets, data manipulati...

Assessment of a fully-automated diagnostic AI software in prostate MRI: Clinical evaluation and histopathological correlation.

OBJECTIVE: This study aims to evaluate the diagnostic performance of a commercial, fully-automated, ...

Diagnostic accuracy of artificial intelligence for identifying systolic and diastolic cardiac dysfunction in the emergency department.

INTRODUCTION: Cardiac point-of-care ultrasound (POCUS) can evaluate for systolic and diastolic dysfu...

Early cancer detection using deep learning and medical imaging: A survey.

Cancer, characterized by the uncontrolled division of abnormal cells that harm body tissues, necessi...

A genetic programming Rician noise reduction and explainable deep learning model for Alzheimer's diseases severity prediction.

BACKGROUND: Degradation of magnetic resonance imaging (MRI) remains a challenging issue, with noise ...

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