Radiology

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

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Multimodal Artificial Intelligence Using Endoscopic USG, CT, and MRI to Differentiate Between Serous and Mucinous Cystic Neoplasms.

Introduction Serous cystic neoplasms (SCN) and mucinous cystic neoplasms (MCN) often exhibit similar...

Mammography reporting dataset with BI-RADS system for natural language processing applications: Addressing public data gaps in Spanish.

Applying Natural Language Processing (NLP) to clinical reports is important for automating the analy...

Towards markerless robot-assisted navigation with 2D-3D registration for anterior cruciate ligament reconstruction.

Conventional navigation frameworks in orthopaedic surgery use optical tracking to localize objects i...

Nanoparticle-enabled molecular imaging diagnosis of osteoarthritis.

Osteoarthritis (OA) is the most common type of arthritis and affects patients with chronic pain, whi...

Advances in disease detection through retinal imaging: A systematic review.

Ocular and non-ocular diseases significantly impact millions of people worldwide, leading to vision ...

Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography.

OBJECTIVES: Deep convolutional neural networks (CNNs) are advancing rapidly in medical research, dem...

Trust of Artificial Intelligence-Augmented Point-of-Care Ultrasound Among Pediatric Emergency Physicians.

OBJECTIVES: Artificial intelligence (AI) may improve many aspects of point-of-care ultrasound (POCUS...

Comparative analysis of semantic-segmentation models for screen film mammograms.

Accurate segmentation of mammographic mass is very important as shape characteristics of these masse...

The Current State of Artificial Intelligence on Detecting Pulmonary Embolism via Computerised Tomography Pulmonary Angiogram: A Systematic Review.

Pulmonary embolism (PE) is a life-threatening condition with significant diagnostic challenges due ...

A radiogenomics study on F-FDG PET/CT in endometrial cancer by a novel deep learning segmentation algorithm.

OBJECTIVE: To create an automated PET/CT segmentation method and radiomics model to forecast Mismatc...

Ensemble of weak spectral total-variation learners: a PET-CT case study.

Solving computer vision problems through machine learning, one often encounters lack of sufficient t...

Recognition of flight cadets brain functional magnetic resonance imaging data based on machine learning analysis.

The rapid advancement of the civil aviation industry has attracted significant attention to research...

Explainable machine learning model predicting neurological deterioration in Wilson's disease via MRI radiomics and clinical features.

BACKGROUND: This study aims to build a machine learning (ML) model to predict the deterioration of n...

UltraBones100k: A reliable automated labeling method and large-scale dataset for ultrasound-based bone surface extraction.

BACKGROUND: Ultrasound-based bone surface segmentation is crucial in computer-assisted orthopedic su...

Vascular segmentation of functional ultrasound images using deep learning.

Segmentation of medical images is a fundamental task with numerous applications. While MRI, CT, and ...

Advancing prenatal healthcare by explainable AI enhanced fetal ultrasound image segmentation using U-Net++ with attention mechanisms.

Prenatal healthcare development requires accurate automated techniques for fetal ultrasound image se...

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