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相关概念视频

Skin Cancer01:30

Skin Cancer

4.2K
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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Clinical Applications of Epidermal Stem Cells01:19

Clinical Applications of Epidermal Stem Cells

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Epidermal stem cells (EpiSCs) are mainly located at the basal layer of the epidermis. These cells repair minor injuries of the skin and replace dead skin cells. However, EpiSCs’ cannot heal severe wounds such as major burns or those from diabetes or hereditary disorders. In such cases, culturing the epidermal stem cells from the patient is possible and has yielded successful treatment options, such as laboratory-grown skin grafts. These grafts are synthesized using a patient’s own...
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Renewal of Skin Epidermal Stem Cells01:12

Renewal of Skin Epidermal Stem Cells

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The skin is divided into epidermis, dermis, and hypodermis, the skin's outermost, middle, and inner layers. The human epidermal layer regularly undergoes renewal, where old, dead cells are replaced by new cells. Epidermal stem cells or EpiSCs divide and differentiate to restore the lost cells. For the renewal process, some EpiSCs continuously self-renew. In contrast, few others differentiate into transit-amplifying cells, which later form prickle or spinous cells, followed by granular...
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相关实验视频

Updated: Jul 18, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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基于生成对抗网络的皮肤病变细分,皮肤病变细分.

Shubham Innani1, Prasad Dutande2, Ujjwal Baid2,3

  • 1Center of Excellence in Signal and Image Processing, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded, Maharashtra, India. shubham.innani@gmail.com.

Scientific reports
|August 18, 2023
PubMed
概括

我们开发了Efficient-GAN (EGAN),这是一种用于皮肤镜图像中精确细分皮肤病变的新框架. EGAN的性能优于现有的方法,为皮肤癌检测提供了更好的诊断支持.

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科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 皮肤病学 皮肤病学

背景情况:

  • 准确的皮肤癌诊断依赖于皮肤病变的精确细分从皮肤镜图像.
  • 计算机辅助诊断 (CAD) 工具可以通过自动化这种细分过程来帮助临床医生.

研究的目的:

  • 引入一种基于对抗性学习的新型框架,即Efficient-GAN (EGAN),用于自动化皮肤病变细分.
  • 开发一个轻量级版本,移动GAN (MGAN),用于在资源有限的环境中高效部署.

主要方法:

  • 拟议的EGAN框架使用无监督生成网络来生成病变口罩.
  • 发电机模块具有以压缩激发为基础的上下压缩化合物缩放路径和以非对称侧面连接为基础的自下而上的路径.
  • 实现了分辨器模块和基于形态的平滑损失,以确保精确和平滑的损伤边界.

主要成果:

  • 在国际皮肤成像协作损伤数据集上,EGAN取得了最先进的表现.
  • 达到了90.1%的子系数,83.6%的贾卡德相似性和94.5%的准确性.
  • 移动GAN (MGAN) 显示了可比性能,训练参数显著减少,推断速度更快.

结论:

  • 拟议的EGAN框架显著提高了皮肤病变细分的准确性.
  • MGAN为实时应用程序和低资源设置提供了一个计算效率高的替代方案.
  • 这些进展有望改善皮肤病学中的计算机辅助诊断.