AI融合多模态影像实现实时癌症诊断，提升早期发现准确率。
Advancements in Real-Time Oncology Diagnosis: Harnessing AI and Image Fusion Techniques
- 结合AI与多种影像技术实现跨模态实时分析
- 涵盖超声、荧光、光谱等10余种成像方式
- 适用于宫颈癌等多部位肿瘤，适合临床辅助诊断
基于人工智能的实时影像分析可帮助肿瘤科医生以高精度和早期阶段诊断癌症。本文综述了不同癌症类型中基于实时AI的影像分析在决策中的应用。文章探讨了多种实时技术，包括技术解决方案、基于AI的影像分析、多部位图像融合诊断以及电磁引导穿刺追踪。重点覆盖超声图像融合、基于不同光谱技术的体内实时癌症诊断、基于光学成像的实时癌症检测、弹性成像诊断、基于类脑架构的宫颈癌检测、基于荧光成像的癌症诊断以及基于高光谱成像的癌症诊断。最后，展望了未来解决实时影像癌症诊断现存问题的可能方向。
原文摘要 · Abstract (English)
Real-time computer-aided diagnosis using artificial intelligence (AI), with images, can help oncologists diagnose cancer with high accuracy and in an early phase. We reviewed real-time AI-based analyzed images for decision-making in different cancer types. This paper provides insights into the present and future potential of real-time imaging and image fusion. It explores various real-time techniques, encompassing technical solutions, AI-based imaging, and image fusion diagnosis across multiple anatomical areas, and electromagnetic needle tracking. To provide a thorough overview, this paper discusses ultrasound image fusion, real-time in vivo cancer diagnosis with different spectroscopic techniques, different real-time optical imaging-based cancer diagnosis techniques, elastography-based cancer diagnosis, cervical cancer detection using neuromorphic architectures, different fluorescence image-based cancer diagnosis techniques, and hyperspectral imaging-based cancer diagnosis. We close by offering a more futuristic overview to solve existing problems in real-time image-based cancer diagnosis.
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