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Comparison and Evaluation of Segmentation Techniques for Brain MRI using Gold Standard
Objective: Automated segmentation is an active research for medical images. Accuracy of automated segmentation methods plays a vital role during brain image analysis. Segmentation being an important area of research, determining its performance is also important. Gold Standard is required for comparison during segmentation evaluation. Method: The Gold Standard for segmentation of medical images is the manual drawing of region of interest. This manual tracing is performed by experts (radiologists). The deviation of segmentation when compared with the experts and the quality of segmentation are inversely proportional. Analysis: The quantitative methods indicate the performance of the segmentation methods when compared with Gold Standard. Evaluation metrics mostly fall into three categories: Area Based Evaluation method (Dice coefficient, Jaccard Coefficient, Relative Volume Difference, Volume Overlap error), Surface Evaluation type (Average Symmetric Surface Distance, Root Mean Square Symmetric Surface Distance, Scatter Plot) and Specificity, Sensitivity and Accuracy.
Gold Standard, Segmentation, MRI, Manual Segmentation, Automated Segmentation, Evaluation Metrics.
- Andreasen NC, Rajarethinam R, Cizadlo T, et al. Automatic atlas-based volume estimation of human brain regions from MR images. J Comput Assist Tomogr. 1996; 20(1):98–106.
- Jack JCR, Twomey CK, Zinsmeister A, et al. Anterior temporal lobes and hippocampal Formations: Normative volumetric measurements from MR images in young adults. Radiology. 1989; 172:549–54.
- Kertesz A, Polk M, Black SE, Howell J. Sex, handedness, and the morphometry of cerebral assymmetries on magnetic resonance imaging. Brain Res. 1990; 530:40–8.
- Shenton ME, Kikinis R, Jolesz FA, et al. Abnormalities of the left temporal lobe and thought disorder in schizophrenia: A quantitative magnetic resonance imaging study. N Engl J Med. 1992; 327:604–12.
- Andreasen NC, Ehrhardt JC, Swayze VW, et al. Magnetic resonance of the brain in schizophrenia: The pathophysiological significance of structural abnormalities. Arch Gen Psychiatry. 1990; 47:35–44.
- Reiss AL, Faruque F, Naidu S, et al. Neuroanatomy of Rett syndrome: A volumetric imaging study. Ann Neurol. 1993; 34:227–34.
- Roberts N, Cruz-Orive LM, Reid NMK, Brodie DA, Edwards RHT. Unbiased estimation of human body composition by the Cavalieri method using magnetic resonance imaging. J Microscopy 1993; 171:239–53.
- Pakkenberg B, Boesen J, Albeck M, Gjerris F. Unbiased and efficient estimation of total ventricular volume of the brain obtained from CT scans by a stereological method. Neuroradiology. 1989; 31:413–7.
- Mustaqeen A, Javed A, Fatima T. An efficient brain tumor detection algorithm using watershed and thresholding based segmentation. IJ Image, Graphics and Signal Processing. 2012; 10:34–9.
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