Radiology

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

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Foundation models for radiology: fundamentals, applications, opportunities, challenges, risks, and prospects.

Foundation models (FMs) represent a significant evolution in artificial intelligence (AI), impacting...

Integrating Machine Learning into Myositis Research: a Systematic Review.

Idiopathic inflammatory myopathies (IIM) are a group of autoimmune rheumatic diseases characterized ...

Deep learning-based allergic rhinitis diagnosis using nasal endoscopy images.

Allergic rhinitis typically has edematous and pale turbinates or erythematous and inflamed turbinate...

Gut microbiota composition is related to anxiety and aggression scores in companion dogs.

There is mounting evidence for a link between behaviour and the gut microbiome in animal and human h...

Artificial intelligence in cardiac sarcoidosis: ECG, Echo, CPET and MRI.

PURPOSE OF REVIEW: Cardiac sarcoidosis is a form of inflammatory cardiomyopathy that varies in its c...

Leveraging ChatGPT for Enhancing Learning in Radiology Resident Education.

RATIONALE AND OBJECTIVES: Chat generative pre-trained transformer (ChatGPT) is a generative artifici...

Efficient Ultrasound Breast Cancer Detection with DMFormer: A Dynamic Multiscale Fusion Transformer.

OBJECTIVE: To develop an advanced deep learning model for accurate differentiation between benign an...

Dynamic abdominal MRI image generation using cGANs: A generalized model for various breathing patterns with extensive evaluation.

Organ motion is a limiting factor during the treatment of abdominal tumors. During abdominal interve...

Automated Laser Modified EndoGraft (ALMEG).

OBJECTIVES: To describe the technical details of a new and innovative method for modifying endograft...

Prediction of Motor Symptom Progression of Parkinson's Disease Through Multimodal Imaging-Based Machine Learning.

The unrelenting progression of Parkinson's disease (PD) leads to severely impaired quality of life, ...

AG-MS3D-CNN multiscale attention guided 3D convolutional neural network for robust brain tumor segmentation across MRI protocols.

Accurate segmentation of brain tumors from multimodal Magnetic Resonance Imaging (MRI) plays a criti...

An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging.

Lung and colon cancers (LCC) are among the foremost reasons for human death and disease. Early analy...

Enhanced particle swarm optimization for feature selection in SVM-based Alzheimer's disease diagnosis.

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder marked by neuronal loss, leadin...

Deep Learning based Collateral Scoring on Multi-Phase CTA in patients with acute ischemic stroke in MCA region.

BACKGROUND AND PURPOSE: Collateral circulation is a critical determinant of clinical outcomes in acu...

Potential Time and Recall Benefits for Adaptive AI-Based Breast Cancer MRI Screening.

BACKGROUND: Abbreviated breast MRI protocols are advocated for breast screening as they limit acquis...

Current Research and Development in the Field of Magnetic Resonance Contrast Media.

The next-generation, high relaxivity, gadolinium-based contrast agents (GBCAs) are discussed, togeth...

Usefulness of compressed sensing coronary magnetic resonance angiography with deep learning reconstruction.

PURPOSE: Coronary magnetic resonance angiography (CMRA) scans are generally time-consuming. CMRA wit...

Artificial Intelligence-Enabled Point-of-Care Echocardiography: Bringing Precision Imaging to the Bedside.

PURPOSE OF REVIEW: The integration of artificial intelligence (AI) with point-of-care ultrasound (PO...

Evaluation of AI-based detection of incidental pulmonary emboli in cardiac CT angiography scans.

Incidental pulmonary embolism (PE) is detected in 1% of cardiac CT angiography (CCTA) scans, despite...

pyDOSEIA: A Python Package for Radiological Impact Assessment during Long-term or Accidental Atmospheric Releases.

pyDOSEIA is a Python package designed for meteorological data processing and radiological impact ass...

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