AI-Driven Advances in Low-Dose Imaging and Enhancement—A Review

Diagnostics, Journal Year: 2025, Volume and Issue: 15(6), P. 689 - 689

Published: March 11, 2025

The widespread use of medical imaging techniques such as X-rays and computed tomography (CT) has raised significant concerns regarding ionizing radiation exposure, particularly among vulnerable populations requiring frequent imaging. Achieving a balance between high-quality diagnostic minimizing exposure remains fundamental challenge in radiology. Artificial intelligence (AI) emerged transformative solution, enabling low-dose protocols that enhance image quality while significantly reducing doses. This review explores the role AI-assisted imaging, CT, X-ray, magnetic resonance (MRI), highlighting advancements deep learning models, convolutional neural networks (CNNs), other AI-based approaches. These technologies have demonstrated substantial improvements noise reduction, artifact removal, real-time optimization parameters, thereby enhancing accuracy mitigating risks. Additionally, AI contributed to improved radiology workflow efficiency cost reduction by need for repeat scans. also discusses emerging directions AI-driven including hybrid systems integrate post-processing with data acquisition, personalized tailored patient characteristics, expansion applications fluoroscopy positron emission (PET). However, challenges model generalizability, regulatory constraints, ethical considerations, computational requirements must be addressed facilitate broader clinical adoption. potential revolutionize safety, optimizing quality, improving healthcare efficiency, paving way more advanced sustainable future

Language: Английский

Artificial Intelligence and Cancer Health Equity: Bridging the Divide or Widening the Gap

Current Oncology Reports, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 3, 2025

Language: Английский

Artificial Intelligence in Spine Surgery: Imaging-Based Applications for Diagnosis and Surgical Techniques

Current Reviews in Musculoskeletal Medicine, Journal Year: 2025, Volume and Issue: unknown

Published: April 30, 2025

Abstract Purpose of Review Artificial intelligence (AI) has rapidly proliferated though medicine with many novel applications to improve patient care and optimize healthcare delivery. This review investigates recent literature surrounding the influence AI imaging technologies on spine surgical practice diagnosis. Recent Findings Robotic-assisted pedicle screw placement been shown increase rate clinically acceptable while increasing operative time. have also promise in creating 3D reducing radiation exposure. Several models using various modalities reliably identify vertebral osteoporotic fractures, stenosis cancers. Summary Complex spinal anatomy pathology as well integration robotics make surgery a promising field for deployment AI-based technologies. Imaging-based projects show potential enhance diagnostic efficiency, facilitate trainee learning outcomes.

Language: Английский