Omnisphero comprises a self-developed algorithm called ‘Neuronal Tracer’ to quantify neurons in a heterogeneous cell population with varying cell densities. Most software requires the user to adjust multiple parameters on several sample images to optimize shape recognition, which results in a time consuming optimization procedure. Therefore, we implemented a new concept in ‘Omnisphero’, in which the user defines a neuron by manual assignment rather than by defining an object over parameter settings using the manual counting tool described above on image extracts. Consequently, the program optimizes automatically all parameters until the best ratio between the Detection power (DP) and false positive (FP)-rate is achieved, without extending the FP-rate above a maximal user defined value.
Results can be plotted as concentration response curves to study the dose dependent effect of substances on neuronal differentiation. The quality of the neuonal identification can be judged by plotting the DP and FP-rate graphs. Since Omnisphero is able to import coordinates of identified neurons of other software, a direct comparison among automated methods enables the user to identify the most appropriate software for his or her cell culture.
In order to obtain ground truth for validating the automated quantification, Omnisphero provides the user with a manual counting tool to quantify neurons. This counting tool saves all coordinates of the user defined neurons by mapping the position of the cursor to the closest surrounding nucleus.