Generalizations of Ripley’s K-function with Application to Space Curves

Jon Sporring*, Rasmus Waagepetersen, Stefan Sommer

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

3 Citations (Scopus)

Abstract

The intensity function and Ripley’s K-function have been used extensively in the literature to describe the first and second moment structure of spatial point sets. This has many applications including describing the statistical structure of synaptic vesicles. Some attempts have been made to extend Ripley’s K-function to curve pieces. Such an extension can be used to describe the statistical structure of muscle fibers and brain fiber tracks. In this paper, we take a computational perspective and construct new and very general variants of Ripley’s K-function for curves pieces, surface patches etc. We discuss the method from [3] and compare it with our generalizations theoretically, and we give examples demonstrating the difference in their ability to separate sets of curve pieces.

Original languageEnglish
Title of host publicationInformation Processing in Medical Imaging : 26th International Conference, IPMI 2019, Hong Kong, China, June 2–7, 2019, Proceedings
EditorsAlbert C.S. Chung, James C. Gee, Paul A. Yushkevich, Siqi Bao
Number of pages12
PublisherSpringer
Publication date1 Jan 2019
Pages731-742
ISBN (Print)978-3-030-20350-4
ISBN (Electronic)978-3-030-20351-1
DOIs
Publication statusPublished - 1 Jan 2019
Event26th International Conference on Information Processing in Medical Imaging, IPMI 2019 - Hong Kong, China
Duration: 2 Jun 20197 Jun 2019

Conference

Conference26th International Conference on Information Processing in Medical Imaging, IPMI 2019
Country/TerritoryChina
CityHong Kong
Period02/06/201907/06/2019
SeriesLecture Notes in Computer Science
Volume11492 LNCS
ISSN0302-9743

Keywords

  • Currents
  • Descriptive statistics
  • Point and curve processes
  • Ripley’s K-function

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