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Updated: Jun 12, 2026
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Manual Segmentation of the Human Choroid Plexus Using Brain MRI
Published on: December 15, 2023
Automatic segmentation of spinal cord MRI using symmetric boundary tracing
Dipti Prasad Mukherjee1, Irene Cheng, Nilanjan Ray
1Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata 700108, India. dipti@isical.ac.in
Summary
This study introduces an automatic algorithm for spinal cord MRI extraction, eliminating manual seeding. The method accurately identifies the spinal cord for surgical planning.
Area of Science:
- Medical Imaging
- Computational Anatomy
- Neurosurgery
Background:
- Spinal cord segmentation from MRI is crucial for surgical planning.
- Existing methods often require manual seed placement, limiting efficiency and reproducibility.
- Automated segmentation can improve workflow and accuracy.
Purpose of the Study:
- To develop a fully automatic algorithm for spinal cord extraction from MRI.
- To enable accurate segmentation without manual intervention.
- To facilitate surgical planning through precise volume of interest (VOI) construction.
Main Methods:
- An adaptive active contour tracing algorithm was developed.
- The algorithm performs fully automatic segmentation of the spinal cord.
- The extracted spinal cord data is used to construct a VOI.
Main Results:
- The algorithm successfully and accurately extracts the spinal cord from MRI data.
- Manual seed selection is no longer required, offering a significant advantage over prior methods.
- The generated VOI provides visual guidance for surgical procedures.
Conclusions:
- The developed adaptive active contour tracing algorithm offers a fully automatic solution for spinal cord MRI segmentation.
- This automation enhances precision and efficiency in preparing for spinal surgeries.
- The technique holds potential for improving outcomes in rehabilitation surgery planning.
