Selected Publication:
SHR
Neuro
Cancer
Cardio
Lipid
Metab
Microb
Egger, J; Nimsky, C; Chen, X.
Vertebral body segmentation with GrowCut: Initial experience, workflow and practical application.
SAGE Open Med. 2017; 5(11):2050312117740984-2050312117740984
Doi: 10.1177/2050312117740984
[OPEN ACCESS]
Web of Science
PubMed
FullText
FullText_MUG
- Leading authors Med Uni Graz
-
Egger Jan
- Altmetrics:
- Dimensions Citations:
- Plum Analytics:
- Scite (citation analytics):
- Abstract:
-
Spinal diseases are very common; for example, the risk of osteoporotic fracture is 40% for White women and 13% for White men in the United States during their lifetime. Hence, the total number of surgical spinal treatments is on the rise with the aging population, and accurate diagnosis is of great importance to avoid complications and a reappearance of the symptoms. Imaging and analysis of a vertebral column is an exhausting task that can lead to wrong interpretations. The overall goal of this contribution is to study a cellular automata-based approach for the segmentation of vertebral bodies between the compacta and surrounding structures yielding to time savings and reducing interpretation errors.
To obtain the ground truth, T2-weighted magnetic resonance imaging acquisitions of the spine were segmented in a slice-by-slice procedure by several neurosurgeons. Subsequently, the same vertebral bodies have been segmented by a physician using the cellular automata approach GrowCut.
Manual and GrowCut segmentations have been evaluated against each other via the Dice Score and the Hausdorff distance resulting in 82.99% ± 5.03% and 18.91 ± 7.2 voxel, respectively. Moreover, the times have been determined during the slice-by-slice and the GrowCut course of actions, indicating a significantly reduced segmentation time (5.77 ± 0.73 min) of the algorithmic approach.
In this contribution, we used the GrowCut segmentation algorithm publicly available in three-dimensional Slicer for three-dimensional segmentation of vertebral bodies. To the best of our knowledge, this is the first time that the GrowCut method has been studied for the usage of vertebral body segmentation. In brief, we found that the GrowCut segmentation times were consistently less than the manual segmentation times. Hence, GrowCut provides an alternative to a manual slice-by-slice segmentation process.
- Find related publications in this database (Keywords)
-
Segmentation
-
vertebral body
-
GrowCut
-
magnetic resonance imaging
-
Dice Score