Neural networks : the official journal of the International Neural Network Society
May 16, 2025
In the field of healthcare, the acquisition and annotation of medical images present significant challenges, resulting in a scarcity of trainable samples. This data limitation hinders the performance of deep learning models, creating bottlenecks in c...
Significant advances have been made in the application of attention mechanisms to medical image segmentation, and these advances are notably driven by the development of the cross-axis attention mechanism. However, challenges remain in handling compl...
Traditional medical image generation often lacks patient-specific clinical information, limiting its clinical utility despite enhancing downstream task performance. In contrast, medical image translation precisely converts images from one modality to...
INTRODUCTION: With artificial intelligence (AI) becoming increasingly integrated into medical imaging, the Health and Care Professions Council (HCPC) updated its Standards of Proficiency for Radiographers in Autumn 2023. These changes require clinici...
Computer methods and programs in biomedicine
Apr 19, 2025
Federated Learning (FL) has emerged as a promising approach for collaborative medical image analysis while preserving data privacy, making it particularly suitable for radiomics tasks. This paper presents a systematic meta-analysis of recent surveys ...
BACKGROUND: Medical imaging has been essential and has provided clinicians with useful information about the human body to diagnose various health issues. Early diagnosis of diseases based on medical imaging can mitigate the risk of severe consequenc...
BACKGROUND/OBJECTIVES: Reviewing the entire history of imaging exams of a single patient's records is an essential step in clinical practice, but it is time and resource consuming, with potential negative effects on workflow and on the quality of med...
INTRODUCTION: To realise the full potential of artificial intelligence (AI) systems in medical imaging, it is crucial to address challenges, such as cyberterrorism to foster trust and acceptance. This study aimed to determine the principles that enha...
The rapid adoption of Artificial Intelligence (AI) in medical imaging raises fairness and privacy concerns across demographic groups, especially in diagnosis and treatment decisions. While federated learning (FL) offers decentralized privacy preserva...
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