Publication detail

Comparison of Segmentation Methods in Analysis of MR and CT Images of Pediatric Spine

MIKULKA, J. CHALUPA, D. KOLAŘÍK, M. ŘÍHA, K. BARTUŠEK, K. FILIPOVIČ, M.

Original Title

Comparison of Segmentation Methods in Analysis of MR and CT Images of Pediatric Spine

Type

conference paper

Language

English

Original Abstract

Scoliosis is the most common spinal deformity in children. Only early treatment during spinal growth can significantly reduce the associated problems caused by the deformity in adults. The aim of this study is to use a spine model to numerically simulate the changes in spinal stresses during correction of congenital deformity by vertebral osteotomy. In the first stage, CT imaging was used as a reference to obtain correctly segmented vertebral groups due to the low quality of MRI image data. Registration techniques were optimized to process all MRI and CT image sequences. An SVM classifier was used with Dice coefficients of 0.98 for CT and 0.95, 0.97, 0.91 and 0.92 for T1 hard, T2 hard, T1 soft and T2 soft, respectively. In the next phase of the project, deep learning algorithms were used to obtain MRI segmentation. Two different segmentation algorithms were proposed using the U-Net network. Standard and patchwise approach with rotational averaging for both CT and MRI dataset. The standard segmentation produced more accurate results with a Dice coefficient of 0.96 for the CT dataset and 0.94 for the MRI dataset. The patchwise method provided slightly better results when processing the actual dataset containing the new data acquired by our MRI scanner. With the smaller MRI dataset, we achieved comparable Dice coefficients in both datasets. The presented results suggest the possibility of using CT and even MR imaging exclusively for spine segmentation if visualization of surrounding tissues and automatic 3D spine modeling is desired.

Keywords

Printing, Image segmentation, Solid modeling, Three-dimensional displays, Magnetic resonance imaging, Computed tomography, Surgery

Authors

MIKULKA, J.; CHALUPA, D.; KOLAŘÍK, M.; ŘÍHA, K.; BARTUŠEK, K.; FILIPOVIČ, M.

Released

21. 11. 2021

ISBN

978-1-7281-7247-7

Book

2021 Photonics & Electromagnetics Research Symposium (PIERS)

ISBN

1559-9450

Periodical

Progress In Electromagnetics

State

United States of America

Pages from

449

Pages to

454

Pages count

6

BibTex

@inproceedings{BUT177478,
  author="Jan {Mikulka} and Daniel {Chalupa} and Martin {Kolařík} and Kamil {Říha} and Karel {Bartušek} and Milan {Filipovič}",
  title="Comparison of Segmentation Methods in Analysis of MR and CT Images of Pediatric Spine",
  booktitle="2021 Photonics & Electromagnetics Research Symposium (PIERS)",
  year="2021",
  journal="Progress In Electromagnetics",
  pages="449--454",
  doi="10.1109/PIERS53385.2021.9694940",
  isbn="978-1-7281-7247-7",
  issn="1559-9450"
}