Radiology

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

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Radiomics-based MRI model to predict hypoperfusion in lacunar infarction.

BACKGROUND: Approximately 20-30 % of patients with acute ischemic stroke due to lacunar infarction e...

Multi-modal MRI synthesis with conditional latent diffusion models for data augmentation in tumor segmentation.

Multimodality is often necessary for improving object segmentation tasks, especially in the case of ...

Application of an AI-Based Model for Non-Invasive Sonographic Assessment for Injection Laryngoplasty.

OBJECTIVE: Hyaluronic acid (HA) can be degraded over time. However, the persistence of the effects a...

Flip Learning: Weakly supervised erase to segment nodules in breast ultrasound.

Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasou...

AI-based deformable hippocampal mesh reflects hippocampal morphological characteristics in relation to cognition in healthy older adults.

Magnetic resonance imaging (MRI)-derived hippocampus measurements have been associated with differen...

Thinking Like Sonographers: Human-Centered CNN Models for Gout Diagnosis From Musculoskeletal Ultrasound.

We explore the potential of deep convolutional neural network (CNN) models for differential diagnosi...

Multiple Instance Learning-Based Prediction of Blood-Brain Barrier Opening Outcomes Induced by Focused Ultrasound.

OBJECTIVE: Targeted blood-brain barrier (BBB) opening using focused ultrasound (FUS) and micro/nanob...

X-ray Coronary Angiogram images and SYNTAX score to develop Machine-Learning algorithms for CHD Diagnosis.

Coronary Heart Disease (CHD) is becoming a leading cause of death worldwide. To assess coronary arte...

Evaluating the Diagnostic Accuracy of ChatGPT-4 Omni and ChatGPT-4 Turbo in Identifying Melanoma: Comparative Study.

ChatGPT is increasingly used in healthcare. Fields like dermatology and radiology could benefit from...

Development of an Intuitive Interface With Haptic Enhancement for Robot-Assisted Endovascular Intervention.

Robot-assisted endovascular intervention has the potential to reduce radiation exposure to surgeons ...

Association of Psychological Resilience With Decelerated Brain Aging in Cognitively Healthy World Trade Center Responders.

BACKGROUND: Despite their exposure to potentially traumatic stressors, the majority of World Trade C...

An extragradient and noise-tuning adaptive iterative network for diffusion MRI-based microstructural estimation.

Diffusion MRI (dMRI) is a powerful technique for investigating tissue microstructure properties. How...

A CT-based deep learning-driven tool for automatic liver tumor detection and delineation in patients with cancer.

Liver tumors, whether primary or metastatic, significantly impact the outcomes of patients with canc...

AI in radiological imaging of soft-tissue and bone tumours: a systematic review evaluating against CLAIM and FUTURE-AI guidelines.

BACKGROUND: Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with va...

Nanomaterial-Based Molecular Imaging in Cancer: Advances in Simulation and AI Integration.

Nanomaterials represent an innovation in cancer imaging by offering enhanced contrast, improved targ...

Discussion of a Simple Method to Generate Descriptive Images Using Predictive ResNet Model Weights and Feature Maps for Recurrent Cervix Cancer.

BACKGROUND: Predictive models like Residual Neural Networks (ResNets) can use Magnetic Resonance Ima...

A machine learning model based on placental magnetic resonance imaging and clinical factors to predict fetal growth restriction.

OBJECTIVES: To create a placental radiomics-clinical machine learning model to predict FGR.

Comparison of MRI and CT based deep learning radiomics analyses and their combination for diagnosing intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) and other subtypes of primary liver cancer (PLC) have overlap...

Comparative Analysis of ChatGPT-4o and Gemini Advanced Performance on Diagnostic Radiology In-Training Exams.

Background The increasing integration of artificial intelligence (AI) in medical education and clini...

PET and CT based DenseNet outperforms advanced deep learning models for outcome prediction of oropharyngeal cancer.

BACKGROUND: In the HECKTOR 2022 challenge set [1], several state-of-the-art (SOTA, achieving best pe...

American College of Veterinary Radiology and European College of Veterinary Diagnostic Imaging position statement on artificial intelligence.

The American College of Veterinary Radiology (ACVR) and the European College of Veterinary Diagnosti...

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