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Optical Sectioning and Visualization of the Intervertebral Disc from Embryonic Development to Degeneration

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Automatic Segmentation of Specific Intervertebral Discs through a Two-Stage MultiResUNet Model.

Yu-Kai Cheng¹, Chih-Lung Lin^2,3, Yi-Chi Huang⁴

¹Department of Neurosurgery, China Medical University Hospital, Taichung 404, Taiwan.

Journal of Clinical Medicine

|October 23, 2021

Summary

This study introduces a novel two-stage deep learning model for precise automatic segmentation of specific intervertebral discs in medical images, significantly improving accuracy and reducing errors.

Keywords:

U-Net deep learning degenerative disc intervertebral disc segmentation spine image

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Published on: July 25, 2025

Area of Science:

Medical Imaging Analysis
Artificial Intelligence in Healthcare
Deep Learning for Medical Segmentation

Background:

Automatic segmentation of intervertebral discs is crucial for intelligent clinical systems.
Existing MultiResUNet models face challenges in segmenting specific intervertebral discs, leading to errors and noise.

Purpose of the Study:

To develop an improved deep learning model for accurate automatic segmentation of specific intervertebral discs.
To address segmentation errors, misalignment, and noise in targeted disc segmentation.

Main Methods:

A two-stage MultiResUNet deep learning model was proposed.
Techniques including connected-component labeling, automatic cropping, and distance transform were integrated.
The model was evaluated for segmenting specific intervertebral discs in medical images.

Main Results:

The proposed two-stage MultiResUNet model significantly reduced segmentation errors and misalignments for specific intervertebral discs.
Segmentation accuracy reached approximately 94%.
The method demonstrated superior performance compared to U-Net, CNN-based, Attention U-Net, and standard MultiResUNet models.

Conclusions:

The developed two-stage MultiResUNet model offers a robust solution for the automatic segmentation of specific intervertebral discs.
This advancement enhances the utility of deep learning in clinical applications requiring precise intervertebral disc analysis.