医学图像多模态融合技术的发展

Bharat Singhal, A. Aggarwal
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引用次数: 0

摘要

成像技术在医学成像、诊断和治疗中起着至关重要的作用。不幸的是,由于这些模式的基本成像原理之间的差异,单个成像设备无法同时同步创建信息丰富的图像。因此,医疗专业人员不得不花费大量的精力和时间来分析从多个设备收集的完整的医疗数据信息。因此,需要一种多模态图像融合方法来增强医学图像,从而帮助医务人员及时提供准确的诊断。为此,我们深入研究了现有的医学图像融合技术,设计了一种基于GAN的多模态图像融合技术,以提高医学图像的质量,更好地诊断疾病,并使用标准数据集对所提出的技术进行了比较评估和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Multimodal Fusion Technique for Medical Images
Imaging technology plays a vital role in medical imaging, diagnosis and treatment using different modalities in imaging devices. Unfortunately, a single imaging device cannot create information rich images synchronously at the same time due to the difference between the fundamental imaging principles of these modalities. As a result, medical professionals have to spend a lot of energy and time to analyze the complete medical data information gathered from multiple devices. Hence a multimodal image fusion method is required in order to enhance the medical images which further can help medical professionals provide an accurate diagnosis in a timely manner. For which, we have gone thoroughly through the existing state-of-art techniques related to Medical Image Fusion and designed a multi-modal Image Fusion Technique based on GAN in order to enhance the quality of the medical image for better diagnosis of diseases and perform comparative evaluation and validation of proposed techniques using the standard datasets.
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