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Sparse Coding Super-Resolution Scheme for Chest Computed Tomography
https://repo.qst.go.jp/records/49151
https://repo.qst.go.jp/records/49151ff2df719-4008-4c64-80cd-bd0709cdf1b5
| Item type | 学術雑誌論文 / Journal Article(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2018-06-29 | |||||
| タイトル | ||||||
| タイトル | Sparse Coding Super-Resolution Scheme for Chest Computed Tomography | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | journal article | |||||
| アクセス権 | ||||||
| アクセス権 | metadata only access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
| 著者 |
Ota, Junko
× Ota, Junko× Umehara, Kensuke× Ishimaru, Naoki× Ohno, Shunsuke× Okamoto, Kentaro× Suzuki, Takanori× Ishida, Takayuki× Ota, Junko× Umehara, Kensuke× Ishida, Takayuki |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | High-resolution chest computed tomography images now has a great importance in the diagnosis. However, this modality requires using a higher radiation dose and a longer scanning time compared to low-resolution computed tomography. In this study, we applied the sparse coding super-resolution method to reconstruct high-resolution images without increasing the radiation dose. We prepared an over-complete dictionary by mapping between low- and high-resolution patches and represented this as a sparse linear combination of each patch of the low-resolution input. These coefficients were used to reconstruct the high-resolution output. In our experiments, 89 computed tomography scans were analyzed. We up-sampled the images 2 or 4 times and compared the image quality of the sparse coding super-resolution scheme with those of the nearest neighbor and bilinear interpolations, which are the traditional interpolation schemes. The image quality was evaluated by measuring the peak signal-to-noise ratio and structure similarity. The differences in the peak signal-to-noise ratios and structure similarities between the sparse coding super-resolution method and the nearest neighbor or bilinear method were statistically significant. Visual assessment confirmed that the sparse coding super-resolution method generated high-resolution images, whereas the conventional interpolation methods generated over-smoothed images. Taken together, these results suggest that the sparse coding super-resolution approach is a robust method for up-sampling computed tomography images and that it yields images with markedly high resolution when magnifying chest computed tomography scans. | |||||
| 書誌情報 |
Journal of Medical Imaging and Health Informatics 巻 8, 号 5, p. 1043-1050, 発行日 2018-06 |
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| 出版者 | ||||||
| 出版者 | AMERICAN SCIENTIFIC PUBLISHERS | |||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 2156-7026 | |||||
| DOI | ||||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | 10.1166/jmihi.2018.2399 | |||||
| 関連サイト | ||||||
| 識別子タイプ | URI | |||||
| 関連識別子 | https://www.ingentaconnect.com/content/asp/jmihi/2018/00000008/00000005/art00025 | |||||
