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Jun 5, 2024 · We present a framework for understanding AI models in medical imaging, leveraging generative AI and interdisciplinary expert review to identify and interpret visual cues …
Jan 31, 2025 · In this paper, we explore an innovative AI methodology specifically tailored for generating synthetic medical images while preserving concealed imaging biomarkers.
Meanwhile, generative adversarial networks (GANs) have achieved remarkable synthetic image generation capabilities. This paper comprehensively reviews contemporary GAN techniques …
Jun 27, 2024 · This paper presents a comprehensive systematic review of generative models (GANs, VAEs, DMs, and LLMs) used to synthesize various medical data types, including …
Jan 6, 2025 · As 2024 draws to a close, generative AI in healthcare has achieved remarkable milestones. This year has been defined by both groundbreaking innovation and insightful …
May 22, 2024 · We summarize key research trends and practical uses for synthetically generated data for radiological applications of AI. Specifically, we discuss different types of techniques for …
Jun 24, 2024 · Key applications include data augmentation that involves generating real-world medical imaging data to supplement datasets subject to privacy concerns or rarity. The …
Mar 6, 2024 · Generative AI models, such as variational autoencoders (VAEs), generative adversarial networks (GANs), and text-to-image diffusion models, offer a promising solution to …
Our method demonstrates strong generalization across 11 medical image seg-mentation tasks and 19 datasets, covering various diseases, organs, and modalities. It improves performance …
Our aim is to offer insights into their current and future applications in medical research, particularly in the context of synthesis applications, generation techniques, and evaluation …
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