:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies
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ISSN 2228-9860
eISSN 1906-9642
CODEN: ITJEA8
FEATURE PEER-REVIEWED ARTICLE
Vol.12(5) (2021) |
A Novel Method of 3D Image Reconstruction Using ACO-based TVR-DART
AnanthaLakshmi Muthuraj, Yamuna Govindarajan (Department of Electronics and Communication Engineering, Annamalai University, Annamalainagar, 608002, Tamilnadu, INDIA),
Sanjeevi Kumar Aiyannar (Department of Electronics and Communication Engineering, Meenakshi Academy of Higher Education and Research, Mangadu, Tamilnadu, INDIA).
Disciplinary: Medical & Health Technology, Electronics Engineering, Applied Mathematics.
doi: 10.14456/ITJEMAST.2021.99
Keywords: 3D reconstruction; Phantom's Sinogram; Ant colony optimization (ACO); 3D visualization; ACO-based TVR-DART; TVR-DART algorithm; Image segmentation; Modified fuzzy c-means (MFCM); Brain tumor; 2D slice; Brain image; MFCM clustering algorithm; PDM-DART.
AbstractThe article provides a theoretical substantiation of the technological platform for ensuring the biological safety of raw milk by the method of controlled thermal cleaning before technological processing. Investigated alternative options for bacterial purification of raw milk by heating, with exposure to a soft regime, improved its microbiological, physicochemical, and technological properties. The technology of low-temperature heat treatment of whey has been substantiated, making it possible to achieve microbiological purification, stabilization, and preservation of the quality of raw materials, with the possibility of its preservation further use in obtaining functional food products and feed means of a new generation.Paper ID: 12A5O
Cite this article:
Muthuraj, A., Govindarajan, Y., Aiyannar, S. K. (2021). A Novel Method of 3D Image Reconstruction Using ACO-based TVR-DART. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 12(5), 12A5O, 1-10. http://doi.org/10.14456/ITJEMAST.2021.99
References
- Levinski, K., Sourin, A. and Zagorodnov, V., 2009. 3D Visualization and Segmentation of Brain MRI Data. In International Conference on Computer Graphics Theory and Applications (GRAPP), (pp. 111-118).
- Birkbeck, N., Cobzas, D., Jagersand, M., Murtha, A. and Kesztyues, T., 2009, December. An interactive graph cut method for brain tumor segmentation. In 2009 Workshop on applications of computer vision (WACV), (pp. 1-7). IEEE.
- Sindhushree, K.S., Manjula, T.R. and Ramesha, K., 2013. Detection and 3D reconstruction of Brain Tumor from Brain MRI images. International Journal of Engineering Research & Technology, 2(8), pp.528-534.
- Batenburg, K.J. and Sijbers, J., 2011. DART: a practical reconstruction algorithm for discrete tomography. IEEE Transactions on Image Processing, 20(9), pp.2542-2553.
- Mecheter, I., Alic, L., Abbod, M., Amira, A. and Ji, J., 2020. MR Image-Based Attenuation Correction of Brain PET Imaging: Review of Literature on Machine Learning Approaches for Segmentation. Journal of Digital Imaging, pp.1-18.
- Wei, Z., Liu, B., Dong, B. and Wei, L., 2018. A joint reconstruction and segmentation method for limited-angle X-Ray tomography. IEEE Access, 6, pp.7780-7791.
- Van Aarle, W., Batenburg, K.J. and Sijbers, J., 2012. Automatic parameter estimation for the discrete algebraic reconstruction technique (DART). IEEE Transactions on Image Processing, 21(11), pp.4608-4621.
- Gopinath, A., Xu, G., Ress, D., Oktem, O., Subramaniam, S. and Bajaj, C., 2012. Shape-based regularization of electron tomographic reconstruction. IEEE transactions on medical imaging, 31(12), pp.2241-2252.
- Pelt, D.M. and Batenburg, K.J., 2013. Fast tomographic reconstruction from limited data using artificial neural networks. IEEE Transactions on Image Processing, 22(12), pp.5238-5251.
- Pelt, D.M. and Batenburg, K.J., 2014. Improving filtered backprojection reconstruction by data-dependent filtering. IEEE Transactions on Image Processing, 23(11), pp.4750-4762.
- Izakian, H. and Abraham, A., 2011. Fuzzy C-means and fuzzy swarm for fuzzy clustering problem. Expert Systems with Applications, 38(3), pp.1835-1838.
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