3D reconstruction of spine image from 2D MRI slices along one axis
- Author(s): Somoballi Ghoshal 1 ; Sourav Banu 1 ; Amlan Chakrabarti 1 ; Susmita Sur-Kolay 2 ; Alok Pandit 3
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View affiliations
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Affiliations:
1:
A. K. Choudhury School of Information Technology , University of Calcutta , Kolkata , India ;
2: A.C.M.U. , Indian Statistical Institute , Kolkata , India ;
3: Bangur Institute of Neurosciences , Kolkata , India
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Affiliations:
1:
A. K. Choudhury School of Information Technology , University of Calcutta , Kolkata , India ;
- Source:
Volume 14, Issue 12,
16
October
2020,
p.
2746 – 2755
DOI: 10.1049/iet-ipr.2019.0800 , Print ISSN 1751-9659, Online ISSN 1751-9667
Magnetic resonance imaging (MRI) is a very effective method for identifying any abnormality in the structure and physiology of the spine. However, MRI is time consuming as well as costly. In this work, the authors propose an algorithm which can reduce the time of MRI and thus the cost, with minimal compromise on accuracy. They reconstruct a three-dimensional (3D) image of the spine from a sequence of 2D MRI slices along any one axis with reasonable slice gap. In order to preserve the image at the edges properly, they regenerate the 3D image by using a combination of bicubic and bilinear interpolation along the orthogonal axis. From the reconstructed 3D, they use a simple geometric method to slice out any possible location along any axis and get the information in that region. They have tested their algorithm on real data, and found that their algorithm reduces the time by 80%, with high internal data preservation accuracy of about 96%.
Inspec keywords: medical image processing; biomedical MRI; interpolation; image reconstruction
Other keywords: spine image; three-dimensional image; MRI; orthogonal axis; magnetic resonance imaging; reasonable slice gap
Subjects: Computer vision and image processing techniques; Biology and medical computing; Medical magnetic resonance imaging and spectroscopy; Optical, image and video signal processing; Biomedical magnetic resonance imaging and spectroscopy; Patient diagnostic methods and instrumentation
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