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Computational and Mathematical Methods in Medicine
Volume 2015 (2015), Article ID 545809, 13 pages
Research Article

Towards Automated Three-Dimensional Tracking of Nephrons through Stacked Histological Image Sets

1Biomedical Engineering Research Group, School of Electrical & Information Engineering, University of the Witwatersrand Johannesburg, Private Bag 3, Johannesburg 2050, South Africa
2Department of Biomedicine, University of Aarhus, 8000 Aarhus C, Denmark
3Department of Histology and Embryology, China Medical University, Shenyang, Liaoning 110122, China

Received 26 February 2015; Revised 16 May 2015; Accepted 28 May 2015

Academic Editor: Giancarlo Ferrigno

Copyright © 2015 Charita Bhikha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


An automated approach for tracking individual nephrons through three-dimensional histological image sets of mouse and rat kidneys is presented. In a previous study, the available images were tracked manually through the image sets in order to explore renal microarchitecture. The purpose of the current research is to reduce the time and effort required to manually trace nephrons by creating an automated, intelligent system as a standard tool for such datasets. The algorithm is robust enough to isolate closely packed nephrons and track their convoluted paths despite a number of nonideal, interfering conditions such as local image distortions, artefacts, and interstitial tissue interference. The system comprises image preprocessing, feature extraction, and a custom graph-based tracking algorithm, which is validated by a rule base and a machine learning algorithm. A study of a selection of automatically tracked nephrons, when compared with manual tracking, yields a 95% tracking accuracy for structures in the cortex, while those in the medulla have lower accuracy due to narrower diameter and higher density. Limited manual intervention is introduced to improve tracking, enabling full nephron paths to be obtained with an average of 17 manual corrections per mouse nephron and 58 manual corrections per rat nephron.