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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/86951完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 傅楸善 | zh_TW |
| dc.contributor.advisor | Chiou-Shann Fuh | en |
| dc.contributor.author | 游亞力 | zh_TW |
| dc.contributor.author | Alexander Yurusov | en |
| dc.date.accessioned | 2023-05-02T17:01:41Z | - |
| dc.date.available | 2023-11-09 | - |
| dc.date.copyright | 2023-05-02 | - |
| dc.date.issued | 2022 | - |
| dc.date.submitted | 2022-12-30 | - |
| dc.identifier.citation | [1] Aswatha, Shashaank M., Jayanta Mukhopadhyay, and Partha Bhowmick. "Image denoising by scaled bilateral filtering." In 2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, pp. 122-125. IEEE, 2011.
[2] L. Ma and B. W. Fei, “Comprehensive Review of Surgical Microscopes: Technology Development and Medical Applications,” J Biomed Opt., Vol. 26, No. 1, pp. 10901-1-74, DOI: 10.1117/1.JBO.26.1.010901. PMID: 33398948; PMCID: PMC7780882, 2021. [3] World Health Organization, Global Strategy on Digital Health 2020-2025, Geneva, 2021. [4] G. Healey and R. Kondepudy, “Radiometric CCD Camera Calibration and Noise Estimation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, No. 3, pp. 267-276, 1994. [5] Y. H. Tsin, V. Ramesh, and T. Kanade, “Statistical Calibration of CCD Imaging Process,” Proceedings of International Conference on Computer Vision, Vancouver, BC, Canada, pp. 1-8, 2001. [6] R. Szeliski, Computer Vision: Algorithms and Applications, 2nd Edition, Springer, New York, 2021. [7] Richard Wolf GmbH., Equipment Carts, https://www.richard-wolf.com/en-uk/solutions/imaging/equipment-carts, 2022. [8] I. Pitas and A.N. Venetsanopoulos, Nonlinear Digital Filters: Principles and Applications, Kluwer, Boston, 1990, https://doi.org/10.1007/978-1-4757-6017-0 [9] Z. Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli, "Image Quality Assessment: From Error Visibility to Structural Similarity," IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600-612, 2004. [10] Alander, Jarmo T., Ilkka Kaartinen, Aki Laakso, Tommi Pätilä, Thomas Spillmann, Valery V. Tuchin, Maarit Venermo, and Petri Välisuo. "A review of indocyanine green fluorescent imaging in surgery." International Journal of Biomedical Imaging 2012. [11] Buades, Antoni, Bartomeu Coll, and Jean-Michel Morel. "Non-local means denoising." Image Processing On Line 1 (2011): 208-212. [12] Tomasi, Carlo, and Roberto Manduchi. "Bilateral filtering for gray and color images." In Sixth International Conference on Computer Vision (IEEE Cat. No. 98CH36271), pp. 839-846. IEEE, 1998. [13] Bilateral filter. (2022, March 18). In Wikipedia. https://en.wikipedia.org/wiki/Bilateral_filter [14] Tukey, John W. Exploratory data analysis. Vol. 2. 1977. [15] Oulhaj, Hind, Aouatif Amine, Mohammed Rziza, and Driss Aboutajdine. "Noise Reduction in Medical Images-comparison of noise removal algorithms." In 2012 International Conference on Multimedia Computing and Systems, pp. 344-349. IEEE, 2012. [16] Obukhova, Natalia, Alexandr Motyko, Alexandr Pozdeev, and Boris Timofeev. "Review of noise reduction methods and estimation of their effectiveness for medical endoscopic images processing." In 2018 22nd Conference of Open Innovations Association (FRUCT), pp. 204-210. IEEE, 2018. [17] He, Kaiming, Jian Sun, and Xiaoou Tang. "Guided image filtering." In European Conference on Computer Vision, pp. 1-14. Springer, Berlin, Heidelberg, 2010. [18] He, Kaiming, Jian Sun, and Xiaoou Tang. "Guided image filtering." IEEE Transactions on Pattern Analysis and Machine Intelligence 35, no. 6 (2012): 1397-1409. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/86951 | - |
| dc.description.abstract | 數位影像是數位醫療資訊的重要組成部分。 由於手術錄影機設計的性質，輸出影片訊號會受到靜止影像中可見噪聲的影響。 電腦視覺中開發了各種降噪方法，其中許多已在數位相機和智慧型手機中實作。 本研究旨在定義來自手術錄影機的噪聲，並實作適合臨床使用的降噪系統，以更小的儲存容量提供更好的視覺品質圖片以用於文件記錄。 | zh_TW |
| dc.description.abstract | Digital imaging is essential to the Digital Health Initiative, defined by the World Health Organization (WHO). Due to the nature of the design of the surgical camera, the output video signal is affected by the noise visible in still images. Various noise reduction methods are developed in Computer Vision, with many implemented in consumer digital cameras and smartphones. This research aims to characterize noise from a surgical camera and implement a noise reduction feature for a medical video recording device, capturing still images of better visual quality and smaller file size with the purpose of documentation, record keeping, presentation, personal research, or dataset. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-05-02T17:01:41Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2023-05-02T17:01:41Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Acknowledgements I
中文摘要 II ABSTRACT III CONTENTS IV LIST OF FIGURES V LIST OF TABLES VI Chapter 1 Introduction 1 1.1 Overview 1 1.2 Thesis Organization 2 Chapter 2 Related Works 3 Chapter 3 Background 5 3.1 Overview of Surgical Imaging 5 3.2 Configuration of endoscopic tower 6 3.3 Recording and Documentation System 7 3.4 RDS and Digital Health Initiative 8 3.5 Noise Problem Overview 9 Chapter 4 Methodology 13 4.1. Experimental Setup 13 4.2 Radiometric Response Calibration 15 4.3 Noise Level Calibration 17 4.4 Spatial Resolution Measurement 19 4.5 Testing Image Set 22 4.6 Objective Quality Metrics 23 4.7 Noise Filtering Methods 25 Chapter 5 Experimental Results 27 5.1 Analysis of the Noise Reduction Methods 27 5.1.1 Median Filter 27 5.1.2 Non-Local Means Denoising 28 5.1.3 Bilateral Filter 29 5.1.4 Comparison of Filters 31 5.1.5 Noise and Data Size 34 5.2 Metod Verification Using Actual Surgical Images 35 5.3 Conclusion about the Noise Reduction Method 38 5.4 Details on the Bilateral Filter 38 5.5 Noise Reduction Implementation on the Actual Recording and Documentation System 39 5.6 Validation of the Noise Reduction implementation 41 5.7 Surgical Image Set for the Subjective Evaluation 43 6. Future Directions 49 References 50 | - |
| dc.language.iso | en | - |
| dc.title | YuruLowNoise: 手術攝像機記錄系統的降噪 | zh_TW |
| dc.title | YuruLowNoise: Noise Reduction for Surgical Camera Recording System | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 111-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 廖振焜;郭冠良 | zh_TW |
| dc.contributor.oralexamcommittee | Chen-Kun Liaw;Kuan-Liang Kuo | en |
| dc.subject.keyword | 降噪,手術錄影機,手術成像,手術記錄系統,雙邊濾波器, | zh_TW |
| dc.subject.keyword | Noise Reduction,Surgical Camera,Surgical Imaging,Surgical Recording System,Bilateral Filter, | en |
| dc.relation.page | 52 | - |
| dc.identifier.doi | 10.6342/NTU202210186 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2023-01-04 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 生醫電子與資訊學研究所 | - |
| 顯示於系所單位： | 生醫電子與資訊學研究所 | |
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|---|---|---|---|
| ntu-111-1.pdf | 43.56 MB | Adobe PDF | 檢視/開啟 |
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