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A Tensor Factorization Method for 3-D Super Resolution With Application to Dental CT
- Source :
- IEEE Transactions on Medical Imaging, IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2019, 38 (6), pp.1524-1531. ⟨10.1109/TMI.2018.2883517⟩
- Publication Year :
- 2019
- Publisher :
- HAL CCSD, 2019.
-
Abstract
- Available super-resolution techniques for 3D images are either computationally inefficient prior-knowledge-based iterative techniques or deep learning methods which require a large database of known low- and high-resolution image pairs. A recently introduced tensor-factorization-based approach offers a fast solution without the use of known image pairs or strict prior assumptions. In this article this factorization framework is investigated for single image resolution enhancement with an off-line estimate of the system point spread function. The technique is applied to 3D cone beam computed tomography for dental image resolution enhancement. To demonstrate the efficiency of our method, it is compared to a recent state-of-the-art iterative technique using low-rank and total variation regularizations. In contrast to this comparative technique, the proposed reconstruction technique gives a 2-order-of-magnitude improvement in running time -- 2 minutes compared to 2 hours for a dental volume of 282$\times$266$\times$392 voxels. Furthermore, it also offers slightly improved quantitative results (peak signal-to-noise ratio, segmentation quality). Another advantage of the presented technique is the low number of hyperparameters. As demonstrated in this paper, the framework is not sensitive to small changes of its parameters, proposing an ease of use.<br />This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
- Subjects :
- FOS: Computer and information sciences
Point spread function
Cone beam computed tomography
Databases, Factual
Computer science
Computer Vision and Pattern Recognition (cs.CV)
Computer Science - Computer Vision and Pattern Recognition
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Dental application
computer.software_genre
030218 nuclear medicine & medical imaging
Image (mathematics)
03 medical and health sciences
Imaging, Three-Dimensional
0302 clinical medicine
Factorization
Voxel
Radiography, Dental
[INFO.INFO-IM]Computer Science [cs]/Medical Imaging
Humans
Segmentation
Electrical and Electronic Engineering
Image resolution
Imagerie médicale
Hyperparameter
3D super-resolution
Radiological and Ultrasound Technology
Tensor factorization
Cone-Beam Computed Tomography
Superresolution
Computer Science Applications
Single image super
Resolution
Tooth
Algorithm
computer
Algorithms
Software
Subjects
Details
- Language :
- English
- ISSN :
- 02780062
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Medical Imaging, IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2019, 38 (6), pp.1524-1531. ⟨10.1109/TMI.2018.2883517⟩
- Accession number :
- edsair.doi.dedup.....56a7ccb422bf2c8d26c3a745fb24a9d4