The path to precision: comparison analysis of automated neural morphology reconstruction software

The differences in the shape, form and location of neurons are closely linked to their function. Being able to accurately and efficiently reconstruct neurons digitally in a three-dimensional space is necessary for the acquisition of knowledge in this research field. Automation through software helps optimise efficiency, yet manual reconstructions are often preferred. This thesis therefore aims to help standardise the research field more and facilitate communication and collaborative efforts by evaluating three software, Vaa3D, Neutube and NCTracer, in regards to the reconstruction algorithms' accuracy, efficiency, consistency and user experience with the user interface in order to deduce their advantages and shortcomings. A downloadable and executable Java program, which compares similarities between two reconstructions, and scripts were written to measure these parameters. Vaa3D had higher accuracy and a significantly lower execution time, but Neutube and NCTracer showcased more stability and consistent results. Additionally, NCTracer proved to be more intuitive to use. All software exhibited their own drawbacks, but the information presented can aid in improving the software or the development of new software surpassing prior ones.