基于视觉的辅助,用于在喉腔镜检查中识别声,并进行知识蒸
Thao Thi Phuong Dao1,2,3,4, Minh-Khoi Pham5, Mai-Khiem Tran1,2,3
1University of Science, VNU-HCMC, Ho Chi Minh City, Vietnam.
Studies in health technology and informatics
|January 25, 2024
概括
这项研究引入了新的声图像数据集和轻量级AI模型用于喉腔镜检查. 由人工智能辅助的系统实现了高精度,使智能手机上的便携式诊断成为可能.
科学领域:
- 耳鼻喉科 耳鼻喉科 耳鼻喉科
- 计算机视觉 计算机视觉
- 医疗成像医学成像
背景情况:
- 喉腔镜图像对于耳鼻喉科的研究至关重要.
- 喉图像数据集的稀缺性限制了对比研究.
- 计算机视觉的进步可以增强诊断工具.
研究的目的:
- 为了介绍一种新的声图像数据集.
- 开发一种轻量级的人工智能模型,用于喉图像分析.
- 创建一个人工智能辅助的智能手机解决方案,用于便携式喉腔镜.
主要方法:
- 创建一个新的喉图像数据集.
- 实现模型压缩的知识蒸.
- 开发一个轻量级的神经网络 (学生模型).
- 将模型集成到智能手机应用程序中.
主要成果:
- 拟议的轻量级模型实现了~98.4%的准确性.
- 与EfficientNetB1.1相比,模型重量减少了高达88%.
- 开发了一个人工智能辅助的智能手机系统用于喉腔镜检查.
结论:
- 这项研究提供了一个有价值的喉图像数据集.
- 一个压缩,高效的AI模型适用于手持式喉腔镜设备.
- 这种人工智能辅助系统可便于便携式和智能语音观察和诊断.
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