1. Image quality improvement in cone-beam CT using the super-resolution technique
- Author
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Shinobu Kumagai, Kenshiro Shiraishi, Jun'ichi Kotoku, Asuka Oyama, Takeshi Takata, Yusuke Saikawa, Takenori Kobayashi, and Norikazu Arai
- Subjects
Cone beam computed tomography ,Mean squared error ,sparse coding ,Computer science ,Image quality ,Health, Toxicology and Mutagenesis ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,super-resolution ,Pelvis ,030218 nuclear medicine & medical imaging ,Image (mathematics) ,03 medical and health sciences ,0302 clinical medicine ,Regular Paper ,Humans ,Radiology, Nuclear Medicine and imaging ,Computer vision ,deformable image registration ,Linear combination ,Cone beam ct ,Radiation ,business.industry ,Cone-Beam Computed Tomography ,Superresolution ,Radiographic Image Enhancement ,Computer Science::Computer Vision and Pattern Recognition ,030220 oncology & carcinogenesis ,cone-beam CT ,Artificial intelligence ,dictionary learning ,business ,Algorithms - Abstract
This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-called dictionaries, constructed respectively from high-resolution and low-resolution image bases. For this study, a CBCT image, as a low-resolution image, is represented as a linear combination of atoms, the image bases in the low-resolution dictionary. The corresponding super-resolution image was inferred by multiplying the coefficients and the high-resolution dictionary atoms extracted from planning CT images. To evaluate the proposed method, we computed the root mean square error (RMSE) and structural similarity (SSIM). The resulting RMSE and SSIM between the super-resolution images and the planning CT images were, respectively, as much as 0.81 and 1.29 times better than those obtained without using the super-resolution technique. We used super-resolution technique to improve the CBCT image quality.
- Published
- 2018
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