Application of Image Processing and Circular Statistics to 3D Cellular Alignment

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Alignment and orientation of cells play an important part in the function of biological tissue. Recent developments in bioengineering using 3D scaffolds have created an increased need for computational techniques to measure orientation which extend beyond 2D measures to produce 3D measures of orientation. Initial studies of 3D alignment have focused on determining individual orientations, however, to truly understand the impact these structures have on the cellular alignment we need to understand the overall distribution of the orientations and their statistics. Hence, in this paper we develop an approach for determining 3D cellular alignment based on image gradients and directional statistics. The intensity gradients of the volumetric image are used to construct a 3D vector field and the local dominant orientations of this vector field then determined.

Original languageEnglish
Title of host publication2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings
PublisherIEEE
Pages992-1000
Number of pages9
ISBN (Electronic)9789881476883
Publication statusPublished - 7 Dec 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 APSIPA.

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Signal Processing
  • Decision Sciences (miscellaneous)
  • Instrumentation

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