An adaptively optimized algorithm for counting nuclei in X-ray micro-CT scans of whole organisms

TL;DR

This paper introduces an adaptively optimized algorithm for counting cell nuclei in X-ray micro-CT scans of whole organisms, specifically zebrafish, addressing artifacts and partial volume effects for accurate cell quantification.

Contribution

It presents a novel adaptive calibration method that improves nuclei counting accuracy in micro-CT scans of biological specimens.

Findings

Effective in zebrafish eye nuclei counting across different ages

Handles scanning artifacts and partial volume effects

Demonstrates improved accuracy over existing methods

Abstract

Living organisms are primarily made of cells. Identifying them and characterizing their geometry and spatial distribution is a first step towards building multi-scale models of these biomaterials. We propose a method to count cells using nuclei in an X-ray microtomographic scan of a zebrafish. To account for scanning artifacts and partial volume effect, the method is adaptively calibrated using parameters approximated from the manifold of manually selected and optimized special cases. The methodology is tested on nuclei in the eyes of zebrafish larvae of different ages.