Abstract
An automatic analysis of images of the histological slices is one of main steps in process of description of structure of neural network in norm and pathology. Understanding of structure and functions of that networks may help to improve neuro-rehabilitation technologies and to translate experimental data to the clinical practice. Main problem of the automatic analysis is complexity of research object and high variance of its parameters, such as thickness and transparency of slice, intensity and type of histological marker, etc. Variance of parameters make every step of neuron detection very hard and complex task. We represent algorithm of neuron detection on images of spinal cord slices using deep neural network. Networks with different parameters are compared to previous algorithm that based on pixels’ filtration by color.
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This work performed with financial support of Russian Science Foundation by Grant â„– 14-15-00788.
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Fomin, I., Mikhailov, V., Bakhshiev, A., Merkulyeva, N., Veshchitskii, A., Musienko, P. (2018). Detection of Neurons on Images of the Histological Slices Using Convolutional Neural Network. In: Kryzhanovsky, B., Dunin-Barkowski, W., Redko, V. (eds) Advances in Neural Computation, Machine Learning, and Cognitive Research. NEUROINFORMATICS 2017. Studies in Computational Intelligence, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-66604-4_13
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