In:
Computational Intelligence and Neuroscience, Hindawi Limited, Vol. 2021 ( 2021-9-7), p. 1-13
Kurzfassung:
The vestibular system is the sensory apparatus that helps the body maintain its postural equilibrium, and semicircular canal is an important organ of the vestibular system. The semicircular canals are three membranous tubes, each forming approximately two-thirds of a circle with a diameter of approximately 6.5 mm, and segmenting them accurately is of great benefit for auxiliary diagnosis, surgery, and treatment of vestibular disease. However, the semicircular canal has small volume, which accounts for less than 1% of the overall computed tomography image. Doctors have to annotate the image in a slice-by-slice manner, which is time-consuming and labor-intensive. To solve this problem, we propose a novel 3D convolutional neural network based on 3D U-Net to automatically segment the semicircular canal. We added the spatial attention mechanism of 3D spatial squeeze and excitation modules, as well as channel attention mechanism of 3D global attention upsample modules to improve the network performance. Our network achieved an average dice coefficient of 92.5% on the test dataset, which shows competitive performance in semicircular canals segmentation task.
Materialart:
Online-Ressource
ISSN:
1687-5273
,
1687-5265
DOI:
10.1155/2021/9654059
Sprache:
Englisch
Verlag:
Hindawi Limited
Publikationsdatum:
2021
ZDB Id:
2388208-6