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 language | English |
|---|---|
| Title of host publication | 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2020 - Proceedings |
| Publisher | IEEE |
| Pages | 992-1000 |
| Number of pages | 9 |
| ISBN (Electronic) | 9789881476883 |
| Publication status | Published - 7 Dec 2020 |
| Externally published | Yes |
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