I/UCRC: Collaborative Research: Detecting Cancer Using Advanced Computer Vision Techniques

I/UCRC：合作研究：使用先进的计算机视觉技术检测癌症

• 批准号: 1230817
• 负责人: Nikolaos Papanikolopoulos
• 金额: $ 10万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-15 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1230817&HistoricalAwards=false
• 关键词: UCRC; Collaborative; Research; Detecting; Cancer

The proposed research proposes to develop novel image processing and machine learning algorithms for the detection and segmentation of cancerous regions from high-resolution images of tissue slides, distinguishing them from healthy/benign regions. The proposed research plans to advance (i) A reliable framework for use in the accurate segmentation of cancerous regions in tissue slides; (ii) New algorithms for texture analysis; (iii) Innovative representations that can increase the system throughput; (iv) Effective machine learning techniques and transparent user interfaces to assist in the reduction of the time that a pathologist needs to examine each slide; and (v) Extensive testing to a variety of cancers including prostate and breast cancer.The proposed work has the potential to yield algorithms to facilitate the design of systems that can increase the likelihood of cancer detection. The work is supported by the Industry Advisory Board as well as individual industry members of the center and has the potential to extend the center?s portfolio. The PIs plan to introduce the research content into summer robotic camps for middle schoolers from underrepresented groups, create a website along with a wiki, visit local groups and K-12 schools, and include the research products into the curricula of the participating institutions.

这项研究建议开发新的图像处理和机器学习算法，用于从组织切片的高分辨率图像中检测和分割癌区域，将它们与健康/良性区域区分开来。拟议的研究计划推进(I)用于准确分割组织切片中的癌症区域的可靠框架；(Ii)用于纹理分析的新算法；(Iii)可增加系统吞吐量的创新表示法；(Iv)有效的机器学习技术和透明的用户界面，以帮助减少病理学家检查每张切片所需的时间；以及(V)对包括前列腺癌和乳腺癌在内的各种癌症进行广泛测试。这项工作得到了行业咨询委员会和中心个别行业成员的支持，并有可能扩大中心的投资组合？S。PIS计划将研究内容引入为来自代表性不足群体的中学生举办的机器人夏令营，创建一个网站和一个维基，访问当地团体和K-12学校，并将研究产品纳入参与机构的课程。