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相关概念视频

Skin Cancer01:30

Skin Cancer

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Skin cancer is a type of cancer that occurs when there is an abnormal growth of skin cells, usually triggered by damage to the DNA within the skin cells. It is primarily caused by exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds. Skin cancer is the most common type of cancer worldwide, and its incidence continues to rise.
Basal Cell Carcinoma (BCC): BCC is the most common type of skin cancer, accounting for about 80% of cases. It typically develops in...
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相关实验视频

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Detection and Isolation of Circulating Melanoma Cells using Photoacoustic Flowmetry
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自动黑色素瘤检测使用优化的五流卷积神经网络.

Vida Esmaeili1, Mahmood Mohassel Feghhi2, Hadi Seyedarabi1

  • 1Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, 51666, Iran.

Scientific reports
|July 2, 2025
PubMed
概括

这项研究引入了新的特征提取方法和优化的四流卷积神经网络 (CNN),以准确检测黑色素瘤. 这种先进的方法在识别皮肤显微镜图像的恶性皮肤癌方面取得了很高的准确性.

关键词:
分类 分类 分类 分类.卷积神经网络是一种卷积神经网络.拒绝这种行为,就是拒绝.黑色素瘤检测检测方法皮肤癌是一种皮肤癌.

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科学领域:

  • 皮肤病学 皮肤病学
  • 医疗成像医学成像
  • 计算机科学 计算机科学

背景情况:

  • 黑色素瘤是一种致命的皮肤癌,全球发病率不断增加,需要准确的早期诊断.
  • 自动黑色素瘤检测面临的挑战包括不平衡的数据集,病变变异性和现有的深度学习模型在识别样本关系方面的局限性.

研究的目的:

  • 开发一种先进的系统,用于在皮肤镜像中自动检测黑色素瘤.
  • 通过提出新的特征提取技术和优化的深度学习架构来克服当前方法的局限性.

主要方法:

  • 预处理技术包括去除毛发,基于生成对抗网络 (GAN) 的平衡,基于CNN的除和图像增强.
  • 四种新的特征提取方法:ULBP-CVA,多块ULBP-NP,多块GULBP-NP和多块梯度ULBP-NP,使用九个拟议的平面.
  • 一个优化的四流CNN (OFSCNN) 用于分类病变颜色,边缘,纹理,局部空间频率和梯度特征.

主要成果:

  • 拟议的OFSCNN在多个数据集中实现了高检测率:99.8% (HAM 10000),99.9% (ISIC 2024),99.62% (ISIC 2017) 和99.6% (ISIC 2016).
  • 新的特征提取方法有效捕捉关键的空间和局部变化,使相似病变的差异化.
  • 与黑色素瘤检测的最先进方法相比,模拟结果显示出更高的性能.

结论:

  • 拟议的方法为准确和自动的黑色素瘤检测提供了一个有希望的解决方案.
  • 先进的预处理,新型特征提取和OFSCNN架构的结合显著提高了诊断性能.