Publication: 3D reconstruction from multiple imaging planes: A pilot study of bone tumor MR images
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2016-01-28
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2-s2.0-84963828718
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Mahidol University
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SCOPUS
Bibliographic Citation
2015 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015. (2016), 354-359
Suggested Citation
Weerayuth Chanapai, Praman Fuangfa, Suphaneewan Jaovisidha, Adisak Nartthanarung, Panrasee Ritthipravat 3D reconstruction from multiple imaging planes: A pilot study of bone tumor MR images. 2015 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2015. (2016), 354-359. doi:10.1109/ISSPIT.2015.7394359 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/43472
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Title
3D reconstruction from multiple imaging planes: A pilot study of bone tumor MR images
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Abstract
© 2015 IEEE. MRI inter-slice gap is required during the image acquisition process in order to prevent leakage protons which cause blurred images. The gap is one of the major obstacles in image analysis, particularly in various modern computer aided diagnosis applications because the data in those inter-slice gaps disappear. In this paper, an inter-slice interpolation algorithm based on the projection on convex curve set (POCS) is proposed to reconstruct MRI voxels and fill inter-slice gaps by using joint information provided by different MRI viewing planes including axial, coronal and sagittal planes. Difference of pixel spacing of these sequences has been transformed and matched to the reference frame. Pixels from different planes are then located together in a unit voxel space matrix. They are then interpolated to create gapless MRI data. The proposed algorithm has been tested with five MRI datasets of bone tumor. The interpolated results are then compared with that of frequently used interpolation techniques including nearest neighbor, linear, and cubic interpolation. Interpolation results from these algorithms have been measured in terms of signal to noise ratio which represents image similarity to the original one. The comparison results showed that the proposed algorithm is superior to the others in which average similarity between the interpolated images and the original MRI images is highest.