医学视觉问题答案:一项调查
Zhihong Lin1, Donghao Zhang2, Qingyi Tao3
1Faculty of Engineering, Monash University, Clayton, VIC, 3800, Australia.
Artificial intelligence in medicine
|September 6, 2023
概括
本次调查探讨了医疗视觉问题答案 (VQA) 系统,这些系统使用人工智能来回答有关医疗图像的临床问题. 它审查了数据集,方法和挑战,以指导未来在这个专业的人工智能领域的研究.
科学领域:
- 人工智能的人工智能
- 医学成像分析 医学成像分析
- 计算机视觉 计算机视觉
背景情况:
- 医学视觉问题答案 (VQA) 将人工智能与视觉问题答案挑战相结合.
- 现有的通用域VQA研究需要针对医疗应用进行特定的探索,因为其具有独特的任务特征.
研究的目的:
- 提供医疗VQA当前状况的全面概述.
- 识别和讨论公开可用的医疗VQA数据集,包括其来源,大小和特征.
- 审查和分析现有的方法,他们的创新,以及医疗VQA的潜在进展.
主要方法:
- 系统地收集和讨论最新的,公开可用的医疗VQA数据集.
- 在医疗VQA任务中使用的技术和创新的审查和总结.
- 对医学特定挑战和未来研究方向的分析.
主要成果:
- 目前医疗VQA数据集的目录,详细说明数据特征.
- 用于医学VQA的各种方法的概述.
- 确定该领域未来研究的关键挑战和有希望的途径.
结论:
- 医疗VQA领域需要专门的调查,因为它的专业性质.
- 这项调查为进入医学VQA领域的研究人员提供了宝贵的见解.
- 鼓励开展进一步的研究,以应对已确定的挑战,并推进医疗人工智能能力.
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