4.6 Article

Content-Based Estimation of Brain MRI Tilt in Three Orthogonal Directions

期刊

JOURNAL OF DIGITAL IMAGING
卷 34, 期 3, 页码 760-771

出版社

SPRINGER
DOI: 10.1007/s10278-020-00400-7

关键词

Magnetic Resonance Imaging (MRI); Principal Component Analysis (PCA); Multimodality Registration; Rotational Effect

资金

  1. Manipal Academy of Higher Education, Manipal

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This study introduces an automatic tilt correction method for brain MR images, measuring angles in X, Z, and Y axes to achieve correction. Experimental results demonstrate that this method outperforms existing studies in correcting tilt.
In a general scenario, the brain images acquired from magnetic resonance imaging (MRI) may experience tilt, distorting brain MR images. The tilt experienced by the brain MR images may result in misalignment during image registration for medical applications. Manually correcting (or estimating) the tilt on a large scale is time-consuming, expensive, and needs brain anatomy expertise. Thus, there is a need for an automatic way of performing tilt correction in three orthogonal directions (X, Y, Z). The proposed work aims to correct the tilt automatically by measuring the pitch angle, yaw angle, and roll angle in X-axis, Z-axis, and Y-axis, respectively. For correction of the tilt around the Z-axis (pointing to the superior direction), image processing techniques, principal component analysis, and similarity measures are used. Also, for correction of the tilt around the X-axis (pointing to the right direction), morphological operations, and tilt correction around the Y-axis (pointing to the anterior direction), orthogonal regression is used. The proposed approach was applied to adjust the tilt observed in the T1- and T2-weighted MR images. The simulation study with the proposed algorithm yielded an error of 0.40 +/- 0.09 degrees, and it outperformed the other existing studies. The tilt angle (in degrees) obtained is ranged from 6.2 +/- 3.94, 2.35 +/- 2.61, and 5 +/- 4.36 in X-, Z-, and Y-directions, respectively, by using the proposed algorithm. The proposed work corrects the tilt more accurately and robustly when compared with existing studies.

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