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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 電信工程學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/59127
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dc.contributor.advisor陳宏銘(Homer H. Chen)
dc.contributor.authorPin-Hsien Leeen
dc.contributor.author李品賢zh_TW
dc.date.accessioned2021-06-16T09:16:26Z-
dc.date.available2017-07-21
dc.date.copyright2017-07-21
dc.date.issued2017
dc.date.submitted2017-07-14
dc.identifier.citation[1] D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science, vol. 254, no. 5035, pp. 1178–1181, 1991.
[2] J. A. Izatt and M. A. Choma, “Theory of optical coherence tomography,” in Optical Coherence Tomography: Technology and Applications, W. Drexler and J. G. Fujimoto Ed. New York: Springer; 2008.
[3] W. Drexler, M. Liu, A. Kumar, T. Kamali, A. Unterhuber, and R. A. Leitgeb, “Optical coherence tomography today: speed, contrast, and multimodality,” J. Biomed. Opt., vol. 19, no. 7, pp. 071412-1–071412-34, 2014.
[4] T. E. de Carlo, A. Romano, N. K. Waheed, and J. S. Duker, “A review of optical coherence tomography angiography (OCTA),” Int. J. Retina Vitreous, vol. 1, no. 1, pp. 1–15, 2015.
[5] C. Blatter, J. Weingast, A. Alex, B. Grajciar, W. Wieser, W. Drexler, R. Huber, and R. A. Leitgeb 'In situ structural and microangiographic assessment of human skin lesions with high-speed OCT,' Biomed. Opt. Express, vol. 3, no. 10, pp. 2636–2646, 2012.
[6] M. Mogensen, L. Thrane, T. M. Jørgensen, P. E. Andersen, and G. B. E. Jemec, “OCT imaging of skin cancer and other dermatological diseases,” J. Biophotonics, vol. 2, no. 6–7, pp. 442–451, 2009.
[7] J. Qin, J. Jiang, L. An, D. Gareau, and R. K. Wang, “In vivo volumetric imaging of microcirculation within human skin under psoriatic conditions using optical microangiography,” Lasers Surg. Med., vol. 43, nol. 2, pp. 122–129, 2011.
[8] E. Dalimier and D. Salomon, “Full-field optical coherence tomography: a new technology for 3D high-resolution skin imaging,” Dermatology, vol. 224, no. 1, pp. 84–92, 2012.
[9] A. Dubois and A. C. Boccara, “Full-Field Optical Coherence Tomography,” in Optical Coherence Tomography: Technology and Applications, W. Drexler and J. G. Fujimoto Ed. New York: Springer; 2008.
[10] C.-C. Tsai, C.-K. Chang, K.-Y. Hsu, T.-S. Ho, M.-Y. Lin, J.-W. Tjiu, and S.-L. Huang, “Full-depth epidermis tomography using a Mirau-based full-field optical coherence tomography,” Biomed. Opt. Express, vol. 5, no. 9, pp. 3001–3010, 2014.
[11] M. Rajadhyaksha, M. Grossman, D. Esterowitz, and R. H. Webb, “In-vivo confocal scanning laser microscopy of human skin—Melanin provides strong contrast,” J. Invest. Dermatol., vol. 104, no. 6, pp. 946–952, 1995.
[12] R. A. Leitgeb, R. M. Werkmeister, C. Blatter, and L. Schmetterer, “Doppler Optical Coherence Tomography,” Progress in Retinal and Eye Research, vol. 41, no. 100, pp. 26–43, 2014.
[13] S. Huang, M. Shen, D. Zhu, Q. Chen, C. Shi, Z. Chen, and F. Lu, “In vivo imaging of retinal hemodynamics with OCT angiography and Doppler OCT,” Biomed. Opt. Express, vol. 7, no. 2, pp. 663–676, 2016.
[14] A. Bouwens, D. Szlag, M. Szkulmowski, T. Bolmont, M. Wojtkowski, and T. Lasser, “Quantitative lateral and axial flow imaging with optical coherence microscopy and tomography,” Opt. Express, vol. 21, no. 15, pp. 17711–17729, 2013.
[15] D. M. Schwartz, J. Fingler, D. Y. Kim, R. J. Zawadzki, L. S. Morse, S. S. Park, S. E. Fraser, and J. S. Werner, “Phase-variance optical coherence tomography: A technique for noninvasive angiography,” Ophthalmology, vol. 121, no. 1, pp. 180–187, 2014.
[16] J. Fingler, R. J. Zawadzki, J. S. Werner, D. Schwartz, and S. E. Fraser, “Volumetric microvascular imaging of human retina using optical coherence tomography with a novel motion contrast technique,” Opt. Express, vol. 17, no. 24, pp. 22190–22200, 2009.
[17] J. Enfield, E. Jonathan, and M. Leahy, “In vivo imaging of the microcirculation of the volar forearm using correlation mapping optical coherence tomography (cmOCT),” Biomed. Opt. Express, vol. 2, no. 5, pp. 1184–1193, 2011.
[18] P. M. McNamara, M. Hrebresh, and M. J. Leahy, “In vivo full-field en face correlation mapping optical coherence tomography,” J. Biomed. Opt., vol. 18, no. 12, pp. 126008-1–126008-4, 2013.
[19] Y. Jia, O. Tan, J. Tokayer, B. Potsaid, Y. Wang, J. J. Liu, M. F. Kraus, H. Subhash, J. G. Fujimoto, J. Hornegger, and D. Huang, “Split-spectrum amplitude-decorrelation angiography with optical coherence tomography,” Opt. Express, vol. 20, no. 4, pp. 4710–4725, 2012.
[20] M. S. Mahmud, D. W. Cadotte, B. Vuong, C. Sun, T. W. H. Luk, A. Mariampillai, and V. X. D. Yang, “Review of speckle and phase variance optical coherence tomography to visualize microvascular networks,” J. Biomed. Opt., vol. 18, no. 5, pp. 050901-1–050901-13, 2013.
[21] I. Gorczynsk, J. V. Migacz, R. J. Zawadzki, A. G. Capps, and J. S. Werner, 'Comparison of amplitude-decorrelation, speckle-variance and phase-variance OCT angiography methods for imaging the human retina and choroid,' Biomed. Opt. Express, vol. 7, no. 3, pp. 911–942, 2016.
[22] E. Amaldi and V. Kann, “On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems,” Theoretical Computer Science, vol. 209, no. 1, pp. 237–260, 1998.
[23] J. Wright, A. Ganesh, S. Rao, Y. Peng, and Y. Ma, “Robust principal component analysis: Exact recovery of corrupted low-rank matrices via convex optimization,” in Advances in Neural Information Processing Systems, pp. 2080–2088, 2009.
[24] Z. Lin, R. Liu, and Z. Su, “Linearized alternating direction method with adaptive penalty for low rank representation,” in Advances in Neural Information Processing Systems, pp. 612–620, 2011.
[25] C. Guyon, T. Bouwmans, and E. Zahzah, “Foreground detection based on low-rank and block-sparse matrix decomposition,” in Proc. IEEE International Conference on Image Processing, pp. 1225–1228, 2012.
[26] X. Zhou, C. Yang, and W. Yu, “Moving object detection by detecting contiguous outliers in the low-rank representation,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 3, pp. 597–610, 2013.
[27] S. Javed, S. Andrews, T. Bouwmans, and S. K. Jung, “OR-PCA with dynamic feature selection for robust background subtraction,” in Proceedings of the 30th Annual ACM Symposium on Applied Computing, pp. 86–91, 2015.
[28] T. Bouwmans and E. H. Zahzah, “Robust PCA via Principal Component Pursuit: A review for a comparative evaluation in video surveillance,” Computer Vision and Image Understanding, vol. 122, pp. 22–34, 2014.
[29] P.-H. Lee, C.-C. Chan, S.-L. Huang, A. Chen, and H. H. Chen, “Blood vessel extraction from OCT data by short-time RPCA,” in Proc. IEEE International Conference on Image Processing, pp. 394–398, 2016.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/59127-
dc.description.abstract光學同調斷層掃描(optical coherence tomography, OCT)的血管造影術能為診斷人體皮膚疾病提供有用資訊。我們在此論文中使用強固主成分分析(robust principal component analysis, RPCA)技術偵測全域式(full-field) OCT影像下的人體皮膚微血管。此外,為了對抗該類影像中的背景變化,我們提出短距強固主成分分析方法(short-time RPCA)。此方法將一全域式OCT影像作短距分割,從每個分割中找出流動的紅血球,最後將各分割的結果組合成血管影像。實驗結果證明我們的方法比其他方法有更佳的準確率,在影像成像品質較差的情況下也能夠擷取出血管。最後,我們也嘗試將短時距的概念套用至其他物體偵測方式,並證明其對偵測血管有所幫助。zh_TW
dc.description.abstractRecent advances in optical coherence tomography (OCT) lead to the development of OCT angiography to provide additional helpful information for diagnosis of diseases like basal cell carcinoma. In this thesis, we investigate how to extract blood vessels of human skin from full-field OCT data using the robust principal component analysis (RPCA) technique. Specifically, we propose a short-time RPCA method that divides the full-field OCT data into segments and decomposes each segment into a low-rank structure representing the relatively static tissues of human skin and a sparse matrix representing the blood vessels. The method mitigates the problem associated with the slow varying background and is free of the detection error that RPCA may have when dealing with FF-OCT data. We evaluate the performance of the proposed method by comparing the extracted blood vessels with the ground truth vessels labeled by dermatologist and show that the proposed method works equally well for FF-OCT volumes of different quality. The average accuracy improvements over the correlation-mapping OCT method and the amplitude-decorrelation OCT angiography method, respectively, are 18.35% and 10.32%. We also show that the idea of short-time analysis behind the proposed method can also be applied to improve the performance of DECOLOR, a related technique for foreground object detection.en
dc.description.provenanceMade available in DSpace on 2021-06-16T09:16:26Z (GMT). No. of bitstreams: 1
ntu-106-R04942041-1.pdf: 2966021 bytes, checksum: 50787931249169e4abfe0586bf8fde90 (MD5)
Previous issue date: 2017
en
dc.description.tableofcontents誌謝 ....................................................... i
中文摘要 ................................................... ii
ABSTRACT .................................................. iii
CONTENTS .................................................. iv
LIST OF FIGURES ........................................... vi
LIST OF TABLES ............................................ viii
Chapter 1 Introduction .................................... 1
Chapter 2 Background ...................................... 3
Chapter 3 Methods ......................................... 8
Chapter 4 Experiments ..................................... 14
4.1 Description of Experiments .......................... 14
4.1.1 AD-OCTA ......................................... 14
4.1.2 cmOCT ........................................... 15
4.2 Evaluation Metrics .................................. 15
4.3 Comparison Based on Extracted Blood Vessels ......... 17
4.3.1 High-Mean-CNR Subvolumes ........................ 17
4.3.2 Low-Mean-CNR Subvolumes ......................... 19
4.3.3 Melanin ......................................... 19
4.4 Comparison Based on Binary Blood Vessels ............ 20
4.5 Sparsity Penalty Factor ............................. 23
4.6 Comparison of Computation Time ...................... 25
Chapter 5 Improvement of DECOLOR by Short-Time Analysis ... 26
Chapter 6 Conclusion ...................................... 27
REFERENCE ................................................. 28
dc.language.isoen
dc.subject皮膚血管偵測zh_TW
dc.subject強固主成分分析zh_TW
dc.subject光學同調斷層掃描zh_TW
dc.subjectoptical coherence tomographyen
dc.subjectrobust principal component analysisen
dc.subjecthuman skinen
dc.subjectblood vessel detectionen
dc.title利用短距強固主成分分析方法從光學同調斷層掃描資料擷取血管zh_TW
dc.titleBlood Vessel Extraction from Full-Field OCT Data of Human Skin by Short-Time RPCAen
dc.typeThesis
dc.date.schoolyear105-2
dc.description.degree碩士
dc.contributor.oralexamcommittee黃升龍(Sheng-Lung Huang),李翔傑(Hsiang-Chieh Lee),王鈺強(Yu-Chiang Frank Wang)
dc.subject.keyword強固主成分分析,光學同調斷層掃描,皮膚血管偵測,zh_TW
dc.subject.keywordrobust principal component analysis,optical coherence tomography,blood vessel detection,human skin,en
dc.relation.page31
dc.identifier.doi10.6342/NTU201701397
dc.rights.note有償授權
dc.date.accepted2017-07-14
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept電信工程學研究所zh_TW
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