Automatic brain matter segmentation of computed tomography images using a statistical model: A tool to gain working time!

Abstract

Brain computed tomography (CT) is useful diagnostic tool for the evaluation of several neurological disorders due to its accuracy, reliability, safety and wide availability. In this field, a potentially interesting research topic is the automatic segmentation and recognition of medical regions of interest (ROIs). Herein, we propose a novel automated method, based on the use of the active appearance model (AAM) for the segmentation of brain matter in CT images to assist radiologists in the evaluation of the images. The method described, that was applied to 54 CT images coming from a sample of outpatients affected by cognitive impairment, enabled us to obtain the generation of a model overlapping with the original image with quite good precision. Since CT neuroimaging is in widespread use for detecting neurological disease, including neurodegenerative conditions, the development of automated tools enabling technicians and physicians to reduce working time and reach a more accurate diagnosis is needed.

Keywords

Segmentation active appearance model cerebral ventricles medical imaging clinical decision-making

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References

Liu

Huang

Ihar

. Automatic model-guided segmentation of the human brain ventricular system from CT images. Acad Radiol 2010; 17: 718–726.

Maksimovic

Stankovic

Milovanovic

. Computed tomography image analyzer: 3D reconstruction and segmentation applying active contour models–‘snakes’. Int J Med Inform 2000; 58–59: 29–37.

Sandor

Metcalf

Kim

. Segmentation of brain CT images using the concept of region growing. Int J Biomed Comput 1991; 29: 133–147.

Liow

. A contour tracing algorithm that preserves common boundaries between regions. Comput Vis Image Underst 1991; 53: 313–321.

Chung

. A segmentation model using compound Markov random fields based on a boundary model. IEEE Trans Image Process 2007; 16: 241–252.

Landré

Lebonvallet

Ruan

. A deformable model-based system for 3D analysis and visualization of tumor in PET/CT images. Conf Proc IEEE Eng Med Biol Soc 2008; 2008: 3130–3133.

Liu

Zhang

. Adaptive segmentation of magnetic resonance images with intensity inhomogeneity using level set method. Magn Reson Imaging 2013; 31: 567–574.

Veksler O. Star shape prior for graph-cut image segmentation. Computer Vision – ECCV 2008. Heidelberg: Springer, 2008, pp. 454–467.

Chen

Smith

. Automated ventricular systems segmentation in brain CT images by combining low-level segmentation and high-level template matching. BMC Med Inform Decis Mak 2009; 9: S4.

10.

Chankong

Theera-umpon

Auephanwiriyakul

. Automatic cervical cell segmentation and classification in Pap smears. Comput Methods Programs Biomed 2014; 113: 539–556.

11.

Hsieh

Liu

Liao

. Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing. BMC Med Inform Decis Mak 2011; 11: 54.

12.

Corso

Sharon

Dube

. Efficient multilevel brain tumor segmentation with integrated Bayesian model classification. IEEE Trans Med Imaging 2008; 27: 629–640.

13.

Cootes

Edwards

Taylor

. Active appearance models. IEEE Transactions on Pattern Analysis and Machine Intelligence 2001; 23: 681–685.

14.

Stegmann M. Active appearance models: Theory, extensions and cases. PhD thesis. Technical University of Denmark, 2000.

15.

Cootes

Edwards

Taylor

Active appearance models. In: Burkhardt

Neumann

(eds). European Conference on Computer Vision 1998; Volume 2. Heidelberg: Springer, pp. 484–498.

16.

Prewitt

JMS

. Object enhancement and extraction. Picture processing and psychopictorics, New York: Academic Press, 1970.

17.

Mikkel B Stegmann. AAM-API, http://www2.imm.dtu.dk/∼aam/ (accessed 27 September 2015).

18.

Akdogan

Kiroglu

Onur

. The volume fraction of brain ventricles to total brain volume: A computed tomography stereological study. Folia Morphol (Warsz) 2010; 69: 193–200.

19.

Anderton

. Changes in the ageing brain in health and disease. Philos Trans R Soc Lond B Biol Sci 1997; 352: 1781–1792.

20.

Collins

. Joint level-set shape modeling and appearance modeling for brain structure segmentation. Neuroimage 2007; 36: 672–683.