从口腔照片中对计算机视觉模型进行口腔癌检测的比较研究
Jérôme de Chauveron1, Chenyu Zha2, Géraldine Lescaille3
1Sorbonne Université, Paris, France; CIMI Paris, INSERM U1135, Paris, France; Laboratoire d'Informatique Paris Descartes (LIPADE), Paris, France; Dental Monitoring, Paris, France.
Computer methods and programs in biomedicine
|December 11, 2025
概括
计算机视觉模型显示出从照片中早期检测口腔癌的前景. 然而,区分恶性和良性病变需要进一步开发人工智能模型.
科学领域:
- 医学成像分析分析 医学成像分析
- 人工智能在瘤学中的应用
- 计算机视觉应用程序的应用程序
背景情况:
- 早期发现口腔癌对于患者的生存和治疗的有效性至关重要.
- 计算机视觉模型为口腔病变识别提供了潜在的诊断工具.
研究的目的:
- 评估基于深度学习的对象检测模型,用于识别口腔癌病变.
- 用计算机视觉提供口腔病变检测方法的全面评估.
主要方法:
- 使用深度学习对象检测模型对活检验证的口腔病变数据集进行比较研究.
- 模型进行了微调,超参数进行了优化,并使用精度,灵敏度和特异性来评估性能.
- 系统地测量和分析影响模型性能的参数.
主要成果:
- 在单一类检测口腔病变的高性能,显示有希望的局部化和精度.
- 在两类检测设置中,在区分恶性病变和良性病变方面遇到了挑战.
- 模型性能被系统地分析,突出了需要改进的领域.
结论:
- 人工智能具有显著的潜力,可以帮助早期检测口腔癌.
- 为了检测小病变并区分恶性和良性病变,需要进一步细化.
- 这些发现为推进医疗计算机视觉工具奠定了基础,以改善患者的治疗结果.
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