Image Analysis using Persistent Homology
演讲者
Shizuo Kaji
时间
2024年04月18日 14:30 至 15:30
地点
A3-4-101
线上
Zoom 928 682 9093
(BIMSA)
摘要
Deep convolutional networks have proved to be extremely powerful in image analysis. However, they tend to be biased toward local features such as texture and often fail to capture the global structure of image and volume data. Persistent homology (PH), a tool from the emerging field of topological data analysis, has been successfully used to detect global characteristics of data that are overlooked by conventional methods. We present Cubical Ripser, an open-source software designed for high-efficiency computation of PH of cubical complexes. We will discuss how PH can be integrated into a standard image analysis pipeline with some practical applications.