宫图像可视化和改进用于诊断和治疗的临床支持
Van Tien Tran1,2, Thanh Hai Pham3, Ngoc Khuong Cat Phan4,5
1Faculty of Applied Science, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, Dien Hong Ward, Ho Chi Minh City, Vietnam. tranvantien@hcmut.edu.vn.
Scientific reports
|November 25, 2025
概括
一种新的宫图像可视化和改进 (CIVI) 技术通过改善图像对比度和亮度来增强宫内皮质瘤 (CIN) 诊断. 这种方法有助于更清晰地识别组织,支持更好的治疗决策.
科学领域:
- 医学成像医学成像
- 妇科瘤学 妇科瘤学
- 数字图像处理是数字图像处理.
背景情况:
- 宫白光成像 (CWLI) 对于诊断宫内皮质瘤 (CIN) 是至关重要的.
- 现有的CWLI方法存在着照明不良,对比度低,反光反射等问题,阻碍了准确的诊断.
- 需要改进可视化,以提高宫组织异常的分化.
研究的目的:
- 引入和验证一个新的图像处理框架,宫图像可视化和改进 (CIVI).
- 为了提高结肠镜图像的对比度和亮度,同时保持组织学准确性.
- 改善宫组织差异的识别,以更好地管理CIN.
主要方法:
- CIVI集成了镜面反射去除,照明校正和局部对比度增强.
- 该技术应用于52个组织学确认的CWLI图像中,CIN等级为1-3-3.
- 局部二进制模式 (LBP) 分析和迈克尔森对比 (MC) 用于定量评估.
- 专家镜师对图像质量改进进行了定性评估.
主要成果:
- 病变和正常组织之间的LBP平均距离显著增加 (0.192到0.391).
- 血液区域的平均MC从0.216提高到0.290.
- 专家评论员报告说,所有CIN等级的平均图像质量得分增加了0.71.
结论:
- CIVI框架显示了增强宫图像可视化的巨大潜力.
- 改进的图像质量可以导致更好的诊断准确性CIN.
- 这项技术可以支持更明智的治疗决策和个性化的患者护理.
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