Automatic Detection of Neurons in NeuN-stained Histological Images of Human Brain (CROSBI ID 256809)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Štajduhar, Andrija ; Džaja, Domagoj ; Judaš, Miloš ; Lončarić, Sven
engleski
Automatic Detection of Neurons in NeuN-stained Histological Images of Human Brain
In this paper we propose a new method for automatic detection of neurons in histological sections of the human brain cortex, based on anisotropic diffusion. The anisotropic diffusion is modeled using a partial differential equation (PDE) and is applied to high resolution microscopy images of the brain in order to detect neurons. We also present a novel approach for PDE-model parameter optimization. Due to the issue of inter- observer variability, three human experts have manually annotated neurons in the image dataset on which the proposed method was trained. The average correlation in neuron detection between the human experts was 86.88%, while the average correlation between the proposed method and the human experts is 88.79%, which shows that the proposed method's performance is equal to that of human experts. Moreover, the proposed automatic method provides consistent and reproducible results on all sections and is much faster than human raters or other automatic methods. Additionally, the proposed method's output was verified by a human expert and has correctly distinguished 95.41% of neurons in the test images.
Neuron detection, Partial differential equations, Brain histology, NeuN
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Podaci o izdanju
519
2019.
237-246
objavljeno
0378-4371
1873-2119
10.1016/j.physa.2018.12.027
Povezanost rada
Interdisciplinarne prirodne znanosti, Matematika, Računarstvo