RT Journal Article
SR Electronic
T1 Single-axon level automatic segmentation and feature extraction from immuhistochemical images of peripheral nerves
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.06.24.169557
DO 10.1101/2020.06.24.169557
A1 Viktor Tóth
A1 Naveen Jayaprakash
A1 Adam Abbas
A1 Ariba Khan
A1 Stavros Zanos
A1 Theodoros P. Zanos
YR 2020
UL http://biorxiv.org/content/early/2020/06/29/2020.06.24.169557.abstract
AB Quantitative descriptions of the morphology and structure of peripheral nerves is central in the development of bioelectronic devices interfacing the nerves. While histological procedures and microscopy techniques yield high-resolution detailed images of individual axons, automated methods to extract relevant information at the single-axon level are not widely available. We implemented a segmentation algorithm that allows for subsequent feature extraction in immunohistochemistry (IHC) images of peripheral nerves at the single fiber scale. These features include short and long cross-sectional diameters, area, perimeter, thickness of surrounding myelin and polar coordinates of single axons within a nerve or nerve fascicle. We evaluated the performance of our algorithm using manually annotated IHC images of 27 fascicles of the swine cervical vagus; the accuracy of single-axon detection was 82%, and of the classification of fiber myelination was 89%.Competing Interest StatementThe authors have declared no competing interest.