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. 2023 Jun;24(6):e13996.
doi: 10.1002/acm2.13996. Epub 2023 Apr 20.

Lumbar spine segmentation method based on deep learning

Hongjiang Lu  1 , Mingying Li  1 , Kun Yu  2 , Yingjiao Zhang  3 , Liang Yu  4
Affiliations

Lumbar spine segmentation method based on deep learning

Hongjiang Lu et al. J Appl Clin Med Phys. 2023 Jun.

Abstract

Aiming at the difficulties of lumbar vertebrae segmentation in computed tomography (CT) images, we propose an automatic lumbar vertebrae segmentation method based on deep learning. The method mainly includes two parts: lumbar vertebra positioning and lumbar vertebrae segmentation. First of all, we propose a lumbar spine localization network of Unet network, which can directly locate the lumbar spine part in the image. Then, we propose a three-dimensional XUnet lumbar vertebrae segmentation method to achieve automatic lumbar vertebrae segmentation. The method proposed in this paper was validated on the lumbar spine CT images on the public dataset VerSe 2020 and our hospital dataset. Through qualitative comparison and quantitative analysis, the experimental results show that the method proposed in this paper can obtain good lumbar vertebrae segmentation performance, which can be further applied to detection of spinal anomalies and surgical treatment.

Keywords: CT images; lumbar vertebrae segmentation; spinal anomalies; surgical treatment.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
UNet‐based localization network.
FIGURE 2
FIGURE 2
Cropping result of the lumbar vertebrae image for two samples, where the lumbar vertebrae region is in the rectangle with red line.
FIGURE 3
FIGURE 3
Schematic diagram of 3D multi‐scale XUNet network.
FIGURE 4
FIGURE 4
Example of computed tomography (CT) image of lumbar spine. (a) horizontal plane; (b) sagittal plane; (c) coronal plane.
FIGURE 5
FIGURE 5
Mask and heat map of lumbar vertebrae for an example.
FIGURE 6
FIGURE 6
The images before and after adding the windows for an example.
FIGURE 7
FIGURE 7
Horizontal visualization of lumbar vertebrae segmentation results of (a) original image, (b) ground truth, (c) Unet, (d) IFCN, (e) nnUnet, and (f) proposed method.
FIGURE 8
FIGURE 8
Sagittal visualization of lumbar vertebrae segmentation results of (a) original image, (b) ground truth, (c) Unet, (d) IFCN, (e) nnUnet, and (f) proposed method.
FIGURE 9
FIGURE 9
Coronal visualization of lumbar vertebrae segmentation results of (a) original image,(b) ground truth, (c) Unet, (d) IFCN, (e) nnUnet, and (f) proposed method.
FIGURE 10
FIGURE 10
3D visualization of the lumbar vertebrae of (a) ground truth, (b) Unet result, (c) IFCN, (d) nnUnet, and (e) proposed method.
See this image and copyright information in PMC

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