.png){kind=icon}
返回
Automatic microarray spot segmentation using a snake-Fisher model
.png){kind=icon}
PRE
AI
DOI：10.1109/TMI.2008.915697.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Inspired by Paragious and Deriche's work, which unifies boundary-based and region-based image partition approaches, we integrate the snake model and the Fisher criterion to capture, respectively, the boundary information and region information of microarray images. We then use the proposed algorithm to segment the spots in the microarray images, and compare our results with those obtained by commercial software. Our algorithm is automatic because the parameters are adaptively estimated from the data without human intervention.
Keyword:
microarray image
spot segmentation
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.8
论文数:
6.2K
被引数:
3.7W
机构
引用论文
Development and Validation of the University of Washington Clinical Assessment of Music Perception Test华盛顿大学音乐知觉临床评估测试的开发和验证
OAAI
OAAI分享收藏
The Stanford Microarray Database: data access and quality assessment tools.png)
NUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏
查看更多内容