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研究生:吳哲皓
研究生(外文):Wu, Che-Hao
論文名稱:深度學習校正扭曲與反光大腸鏡影像以偵測息肉
論文名稱(外文):Distortive and reflective colonoscopy images calibration for polyp detection by deep learning
指導教授:許見章
指導教授(外文):Hsu,Chien-Chang
口試委員:許見章楊勝源蔣榮先段裘慶
口試委員(外文):Hsu, Chien-ChangYang, Sheng-YuanChiang, Jung-HsienTuan, Chyon-Ching
口試日期:2022-07-25
學位類別:碩士
校院名稱:輔仁大學
系所名稱:資訊工程學系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2022
畢業學年度:110
語文別:中文
論文頁數:29
中文關鍵詞:電腦輔助大腸息肉診斷及偵測扭曲與反光校正兩階段深度學習模型生成對抗網路卷積類神經網
外文關鍵詞:Computer-aided colorectal polyp detection and classification systemsreflective colonoscopy images calibrationtwo-stage deep learning modelgenerative adversarial networkconvolutional neural network
相關次數:
  • 被引用被引用:0
  • 點閱點閱:183
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
摘要 I
Abstract II
目錄 IV
表目錄 V
圖目錄 VI
第一章 前言 1
第二章 材料與方法 6
第三章 實驗與結果 11
3.1 校正前後影像比例分析 11
3.2 校正前後息肉偵測效能分析 12
3.3 使用校正前後的資料集偵測縮小10%圖片 15
3.4 校正前後去白光資料集進行偵測 17
3.5 兩階段偵測 19
3.6 Kvasir-sessile 20
第四章 結果與討論 22
參考文獻 24
[1] F. A. Foss, K. P. West, and A. H. McGregor, “Pathology of polyps detected in the bowel cancer screening programme,” Diagnostic Histopathology, 2011, pp. 495-504.
[2] M. Liedlgruber, and A. Uhl, “Computer-aided decision support systems for endoscopy in the gastrointestinal tract: a review,” IEEE reviews in biomedical engineering, 2011, 73-88.
[3] A. Anaya-Isaza, L. Mera-Jiménez, and M. Zequera-Diaz, “An overview of deep learning in medical imaging,” Informatics in Medicine Unlocked, 2011, pp. 100723.
[4] H. P. Chan, R. K. Samala, L. M. Hadjiiski, and C. Zhou, “Deep learning in medical image analysis,” Deep Learning in Medical Image Analysis, 2020, pp. 3-21.
[5] L. Lu, Y. Zheng, G. Carneiro, and L. Yang, “Deep learning and convolutional neural networks for medical image computing,” Advances in computer vision and pattern recognition, 2017, pp. 978-3.
[6] G. Litjens, T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, …, and C. I. Sánchez, “A survey on deep learning in medical image analysis,” Medical image analysis, 2017, pp. 60-88.
[7] L. A. Alexandre, J. Casteleiro, & N. Nobreinst, “Polyp detection in endoscopic video using svms,” In European Conference on Principles of Data Mining and Knowledge Discovery, 2007, pp. 358-365.
[8] D. C. Cheng, W. C. Ting, Y. F. Chen, Q. Pu, and X. Jiang, “Colorectal polyps detection using texture features and support vector machine,” In International Conference on Mass Data Analysis of Images and Signals in Medicine, Biotechnology, and Chemistry, 2008, pp. 62-72.
[9] Y. Zheng, X. Yang, and G. Beddoe, “Reduction of false positives in polyp detection using weighted support vector machines,” In 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, pp. 4433-4436
[10] A. Ratheesh, P. Soman, M. R. Nair, R. G. Devika, and R. P. Aneesh, “Advanced algorithm for polyp detection using depth segmentation in colon endoscopy,” In 2016 International Conference on Communication Systems and Networks (ComNet), 2016, pp. 179-183.
[11] A. Nogueira-Rodríguez, R. Dominguez-Carbajales, F. Campos-Tato, J. Herrero, M. Puga, D. Remedios, ... and D. Glez-Pena, “Real-time polyp detection model using convolutional neural networks,” Neural Computing and Applications, 2022, pp. 10375-10396.
[12] R. Zhang, Y. Zheng, C. C. Poon, D. Shen, and J. Y. Lau, “Polyp detection during colonoscopy using a regression-based convolutional neural network with a tracker,” Pattern recognition, 2018, pp. 209-219.
[13] D. Butler, Y. Zhang, T. Chen, S. H. Shin, R. Singh, and G. Carneiro, “In Defense of Kalman Filtering for Polyp Tracking from Colonoscopy Videos,” In 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 2022, pp. 1-5.
[14] K. Li, M. I. Fathan, K. Patel, T. Zhang, C. Zhong, A. Bansal, ... and G. Wang, “Colonoscopy polyp detection and classification: Dataset creation and comparative evaluations,” Plos one, 2021, e0255809.
[15] J. Y. Lee, J. Jeong, E. M. Song, C. Ha, H. J. Lee, J. E. Koo, ... and J. S. Byeon, “Real-time detection of colon polyps during colonoscopy using deep learning: systematic validation with four independent datasets,” Scientific reports, 2020, pp. 1-9.
[16] P. Sasmal, A. Paul, M. K. Bhuyan, Y. Iwahori, N. Ogasawara, and K. Kasugai, “An Automated Framework for Detection, Localization, and Classification of Colonic Polyp using Deep Learning,” 2021.
[17] D. Jha, S. Ali, Tomar, N. K., Johansen, H. D., Johansen, D., Rittscher, J., ... & Halvorsen, P. Real-time polyp detection, localization and segmentation in colonoscopy using deep learning. Ieee Access, 2021, pp. 40496-40510.
[18] Y. Guo, J. Bernal, and B. J Matuszewski, “Polyp segmentation with fully convolutional deep neural networks—extended evaluation study,” Journal of Imaging, 2020, pp. 69.
[19] C. M. Hsu, C. C. Hsu, Z. M. Hsu, F. Y. Shih, M. L. Chang, & T. H. Chen, “Colorectal polyp image detection and classification through grayscale images and deep learning,” Sensors, 2021, pp. 5995.
[20] R. Li, J. Pan, Y. Si, B. Yan, Y. Hu, & H. Qin, “Specular reflections removal for endoscopic image sequences with adaptive-RPCA decomposition,” IEEE transactions on medical imaging, 2019, pp. 328-340.
[21] Y. Gao, J. Yang, S. Ma, D. Ai, T. Lin, S. Tang, and Y. Wang, “Dynamic searching and classification for highlight removal on endoscopic image,” Procedia Computer Science, 2017, pp. 762-767.
[22] M. Arnold, A. Ghosh, S. Ameling, and G. Lacey, “Automatic segmentation and inpainting of specular highlights for endoscopic imaging,” EURASIP Journal on Image and Video Processing, 2010, pp. 1-12.
[23] F. J. Sánchez, J. Bernal, C. Sánchez-Montes, C. R. de Miguel, and G. Fernández-Esparrach, “Bright spot regions segmentation and classification for specular highlights detection in colonoscopy videos,” Machine Vision and Applications, 2017, pp. 917-936.
[24] C. A. Saint-Pierre, J. Boisvert, G. Grimard, and F. Cheriet, “Detection and correction of specular reflections for automatic surgical tool segmentation in thoracoscopic images,” Machine Vision and Applications, 2011, pp. 171-180.
[25] I. Funke, S. Bodenstedt, C. Riediger, J. Weitz, and S. Speidel, “Generative adversarial networks for specular highlight removal in endoscopic images,” In Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 2018, pp. 8-16
[26] S. M. Alsaleh, A. I. Aviles-Rivero, J. K. and Hahn, “ReTouchImg: Fusioning from-local-to-global context detection and graph data structures for fully-automatic specular reflection removal for endoscopic images,” Computerized Medical Imaging and Graphics, 2019, pp. 39-48.
[27] J. Langr, and V. Bok.”GANs in Action (Audiobook),” Manning Publications, 2019.
[28] D. Pathak, P. Krahenbuhl, J. Donahue, T. Darrell, and A. A. Efros, “Context encoders: Feature learning by inpainting,” In Proceedings of the IEEE conference on computer vision and pattern recognition, 2016, pp. 2536-2544.
[29] S. Iizuka, E. Simo-Serra, and “Ishikawa, H. Globally and locally consistent image completion,” ACM Transactions on Graphics (ToG), 2017, pp. 1-14.
[30] Z. Yan, X. Li, M. Li, W. Zuo, and S. Shan, “Shift-net: Image inpainting via deep feature rearrangement,” In Proceedings of the European conference on computer vision, 2018, pp. 1-17.
[31] C. Yang X., Lu, Z. Lin, E. Shechtman, O. Wang, and H. Li, “High-resolution image inpainting using multi-scale neural patch synthesis,” In Proceedings of the IEEE conference on computer vision and pattern recognition, 2017, pp. 6721-6729.
[32] U. Demir, and G. Unal, ”Patch-based image inpainting with generative adversarial networks,” arXiv preprint arXiv , 2018, 1803.07422.
[33] J. Yu, Z. Lin, J. Yang, X. Shen, X. Lu, and T. S. Huang, “Generative image inpainting with contextual attention,” In Proceedings of the IEEE conference on computer vision and pattern recognition, 2018, pp. 5505-5514.
[34] M. Afifi, K. G. Derpanis, B. Ommer, and M. S. Brown, “Learning multi-scale photo exposure correction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition”, 2021, pp. 9157-9167.
[35] T. Mertens, J. Kautz, and F. V. Reeth. “Exposure Fusion.” Pacific Graphics 2007: Proceedings of the Pacific Conference on Computer Graphics and Applications. Maui, HI, 2007, pp. 382–390.
[36] G. Dougherty, ”Digital image processing for medical applications,” Cambridge University Press , 2009.
[37] K. Yao, T. Matsui, H. Furukawa, T. Yao, T. Sakurai, and T. Mitsuyasu, “A new stereoscopic endoscopy system: accurate 3-dimensional measurement in vitro and in vivo with distortion-correction function,” Gastrointestinal endoscopy, 2002, pp. 412-420.
[38] H. Usami, Y. Iwahori, M. K. Bhuyan, A. Wang, N. Ogasawara, and K. Kasugai, “Polyp Shape Recovery using Vascular Border from Single Colonoscopy Image,” In BIOIMAGING, 2019, pp. 104-111.
[39] B. Flood, L. Rai, and W. E. Higgins, “System for robust bronchoscopic video distortion correction,” In Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 2011, pp. 474-489.
[40] N. A. Kallemeyn, N. M. Grosland, V. A. Magnotta, J. A. Martin, and D. R. Pedersen, “Arthroscopic lens distortion correction applied to dynamic cartilage loading,” The Iowa orthopaedic journal, 2007, pp. 52.
[41] D. Scaramuzza, A. Martinelli, and R. Siegwart, “A toolbox for easily calibrating omnidirectional cameras,” In 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006, pp. 5695-5701.
[42] Yang Ling, and Cheng Yun. “Design method of fisheye image correction using latitude and longitude mapping” Chinese Journal of Engineering Graphics, 2010, pp. 19-22.
[43] W. Guiping, W. Wei, W. Cheng, and B. Kun, “A fisheye image correction method based on bilinear interpolation,” Computer Applications and Software, 2012, pp. 122-126.
[44] “A Flexible Architecture for Fisheye Correction in Automotive Rear-View Cameras” [cited 2022 5/18]:http://www.altera.com/literature/wp/wp-01073-flexible-architecture-fisheye-correction-automotive-rear-view-cameras.pdf.
[45] T. N. Mundhenk, M. J. Rivett, X. Liao, and E. L. Hall, “Techniques for fisheye lens calibration using a minimal number of measurements,” In Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision, 2000, pp. 181-190.
[46] OLYMPUSCF-H290L/I [cited20225/18];Availablefrom:
https://www.yuanyu.tw/medical/upload/doc/products_1446022805.pdf
[47] J. Bernal, N. Tajkbaksh, F. J. Sanchez, B. J. Matuszewski, H. Chen, L. Yu, ... and A. Histace, “Comparative validation of polyp detection methods in video colonoscopy: results from the MICCAI 2015 endoscopic vision challenge,” IEEE transactions on medical imaging, 2017, pp. 1231-1249.
[48] Z Zhou, M. M. Rahman Siddiquee, N. Tajbakhsh, and J. Liang, "Unet++: A nested u-net architecture for medical image segmentation,” In Deep learning in medical image analysis and multimodal learning for clinical decision support, 2018, pp. 3-11.
[49] O. Ronneberger, P. Fischer, and T. Brox, “U-net: Convolutional networks for biomedical image segmentation,” In International Conference on Medical image computing and computer-assisted intervention, 2015, pp. 234-241.
[50] D. Jha, P. H. Smedsrud, M. A Riegler, D. Johansen, T. De Lange, P. Halvorsen, and H. D. Johansen, “Resunet++: An advanced architecture for medical image segmentation,” In 2019 IEEE International Symposium on Multimedia, 2019, pp. 225-2255.
[51] Y. Fang, C. Chen, Y. Yuan, and K. Y. Tong, “Selective feature aggregation network with area-boundary constraints for polyp segmentation,” In International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019, pp. 302-310.
[52] C. M. Hsu, “Colonoscopy polyp detection using grayscale image,” Master's Thesis, Department of Information Engineering, Fu Jen Catholic University, 2022.

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