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Comparison of two methods for the estimation of subcortical volume and asymmetry using magnetic resonance imaging: a methodological study
Authors:Tolga Ertekin  Niyazi Acer  Semra Içer  Ahmet T. Ilıca
Affiliation:1. Department of Anatomy, School of Medicine, University of Erciyes, Kayseri, 38039, Turkey
2. Department of Biomedical Engineering, Engineering Faculty, University of Erciyes, Kayseri, Turkey
3. Department of Radiology, Gulhane Military Medical School, Ankara, Turkey
Abstract:

Purpose

The subcortical brain structures are associated with other structures of nervous system; therefore, they have major influence on sensory–motor, limbic and cognitive information processing. Magnetic resonance imaging provides a detailed knowledge of normal and diseased anatomical structures for medical research. The aim of the current study was to compare the volumes of subcortical brain structures and determine the probable volumetric asymmetry in healthy subjects using stereological (point-counting) and semi-automatic segmentation methods.

Methods

MR scans were obtained from 30 subjects (17 males, 13 females) free of any psychiatric, neurological or cognitive impairment. MR images were analyzed by using stereological (point-counting) and semi-automatic segmentation methods.

Results

We did not find any significant differences among the subjects with respect to gender using both methods. This study showed no significant asymmetry in subcortical structures according to methods. Also, no significant difference was found between point-counting and semi-automated segmentation methods for the volumes of subcortical structures (p > 0.05).

Conclusion

From these results, it can be concluded that the semi-automated segmentation method and stereological technique can be used for reliable volume estimation of subcortical structures. However, the stereological method takes less time than semi-automated segmentation; it is simple, reliable and inexpensive. Further studies are required with larger samples in order to support these data.
Keywords:
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