Radiology

OA-HybridCNN (OHC): An advanced deep learning fusion model for enhanced diagnostic accuracy in knee osteoarthritis imaging.

Knee osteoarthritis (KOA) is a leading cause of disability globally. Early and accurate diagnosis is...

PET image nonuniformity texture features for metastasis risk prediction in osteosarcoma.

OBJECTIVE: PET image analysis provides tumor heterogeneity data related to neoadjuvant chemotherapy ...

New Targets for Imaging in Nuclear Medicine.

Nuclear medicine is rapidly evolving with new molecular imaging targets and advanced computational t...

Keypoint localization and parameter measurement in ultrasound biomicroscopy anterior segment images based on deep learning.

BACKGROUND: Accurate measurement of anterior segment parameters is crucial for diagnosing and managi...

A Deep Learning Approach for Mandibular Condyle Segmentation on Ultrasonography.

Deep learning techniques have demonstrated potential in various fields, including segmentation, and ...

Progressive Distillation With Optimal Transport for Federated Incomplete Multi-Modal Learning of Brain Tumor Segmentation.

Multi-modal Magnetic Resonance Imaging (MRI) provide sufficient complementary information for brain ...

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma From Multi-Sequence Magnetic Resonance Imaging Based on Deep Fusion Representation Learning.

Recent studies have identified microvascular invasion (MVI) as the most vital independent biomarker ...

Towards High-Quality MRI Reconstruction With Anisotropic Diffusion-Assisted Generative Adversarial Networks and Its Multi-Modal Images Extension.

Recently, fast Magnetic Resonance Imaging reconstruction technology has emerged as a promising way t...

PEARL: Cascaded Self-Supervised Cross-Fusion Learning for Parallel MRI Acceleration.

Supervised deep learning (SDL) methodology holds promise for accelerated magnetic resonance imaging ...

AI-driven early diagnosis of specific mental disorders: a comprehensive study.

One of the areas where artificial intelligence (AI) technologies are used is the detection and diagn...

From Image to Diagnosis: Convolutional Neural Networks in Tongue Lesions.

Clinical examination of the tongue is essential for diagnosing systemic and local diseases. However,...

Artificial intelligence guided imaging as a tool to fill gaps in health care delivery.

Deep vein thrombosis (DVT) causes significant morbidity/mortality and timely diagnosis often via ult...

Advanced holographic convolutional dense networks and Tangent runner optimization for enhanced polycystic ovarian disease classification.

Polycystic Ovarian Disease (PCOD) is among the most prevalent endocrine disorders complicating the h...

Fluorescence-based spectrometric and imaging methods and machine learning analyses for microbiota analysis.

Most microbiota determination (skin, gut, soil, etc.) are currently conducted in a laboratory using ...

Quality of reporting of studies on artificial intelligence in radiology: what is the current state of the field?

Pix2Pix generative-adversarial network in improving the quality of T2-weighted prostate magnetic resonance imaging: a multi-reader study.

PURPOSE: To assess the performance and feasibility of generative deep learning in enhancing the imag...

Semisupervised adaptive learning models for IDH1 mutation status prediction.

The mutation status of isocitrate dehydrogenase1 (IDH1) in glioma is critical information for the di...

The Role of Large Language Models (LLMs) in Breast Imaging Today and in the Near Future.

This narrative review focuses on the integration of large language models (LLMs), such as GPT-4 and ...

An optimized deep neural network with explainable artificial intelligence framework for brain tumour classification.

Brain tumour classification plays a significant role in improving patient care, treatment planning, ...

PSMA PET/CT for prostate cancer diagnosis: current applications and future directions.

Prostate cancer (PCa) requires improved diagnostic strategies beyond conventional imaging. This revi...

The Role of Artificial Intelligence in Providing Real-Time Guidance During Interventional Cardiology Procedures: A Narrative Review.

Integrating artificial intelligence (AI) in interventional cardiology revolutionizes procedural guid...